Web3 | Identosphere Blogcatcher

Starknet’s DeFi TVL rose about 5% over a slightly shorter period, while its proposed Layer 1 shift remains under discussion.... Read the full story at The Defiant

The token retained its lead despite a 1.7% weekly decline, while Avalanche shortened the minimum commitment for validators during the period.... Read the full story at The Defiant

Ledger says all confirmed cases tied to its October 9 fund-draining investigation involve Southeast Asian reseller CryptoBilis, which has halted hardware-wallet sales.... Read the full story at The Defiant

Former International Exchange clients gain Deribit's options suite and margin system, while US Prime options trading follows a separate rollout.... Read the full story at The Defiant

The company says its direct sales channels are unaffected and reminds resellers never to restock returned products.... Read the full story at The Defiant

The reserve gap is about 603 BTC. Liquid says peg-outs require full backing and completed security reviews before they can restart.... Read the full story at The Defiant

The team says it is restricting exposure onchain and through relayers. Its statement does not confirm claims that a trader was blacklisted or prevented from closing positions.... Read the full story at The Defiant

The reported Tron deposits offer investigators an exchange-account lead, but intermediary wallets handling other clients’ money complicate attribution.... Read the full story at The Defiant

The flaw was fixed in xrpld 3.4.1 on Sept. 25. Developers found no evidence it was exploited on a public network.... Read the full story at The Defiant

Withdrawals on Oct. 7–8 drove a $920 million swing from the preceding week, leaving the two-week flow total negative.... Read the full story at The Defiant

Nick Bostrom joins Theo Jaffee and Sofia Puccini on MTS to revisit the ideas about superintelligence and existential risk that he helped bring into the mainstream, now that increasingly capable AI systems actually exist.

Nick discusses why reinforcement learning may be pushing models toward more goal-seeking behavior, what recent agent experiments tell us about instrumental convergence, and why he favors preserving the ability to slow frontier development rather than committing now to a broad or indefinite AI pause. He also makes the case that the risks of AI need to be weighed alongside its potential upside, from advances in medicine and longer lifespans to entirely new ways of being human. 

They also get into whether today's models could already have some form of consciousness, the tradeoffs of open-source AI, whether machines can do original philosophy, mind uploading, and what the simulation hypothesis might mean for the superintelligence we create.

Resources:

Nick Bostrom / Macrostrategy Research Initiative: https://nickbostrom.com/ 

Follow Theo Jaffee on X: https://x.com/theojaffee

Follow Sofia Puccini on LinkedIn: https://www.linkedin.com/in/sofiapuccini/

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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

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The company says it found no matching login record. A researcher found the fake migration site was built to collect wallet recovery phrases.... Read the full story at The Defiant

At the latest mining pace, annualized additions from vesting and block rewards would fall from about 89 million FIL to 21 million. Storage-provider rewards continue.... Read the full story at The Defiant

The cited wallet showed about $1.73 million in realized trading gains on PaperDash. Papertrade’s loss-funded pool pays winners, with unpaid profits queued if cash runs short.... Read the full story at The Defiant

Sui’s DeFi liquidity also expanded, but more slowly than its token price, while a recent pullback interrupted the rally.... Read the full story at The Defiant

Low-cap token recommendations will earn less under changes starting with the Oct. 10 payout, co-founder Alon said.... Read the full story at The Defiant

Reported staking rewards equaled about 69% of net trading losses, but the payouts redistribute money to PAPER stakers rather than reimburse each losing trader.... Read the full story at The Defiant

CryptoBilis has stopped selling all hardware wallet inventory pending the investigation, according to Ledger, widening an earlier pause request limited to Ledger devices.... Read the full story at The Defiant

The 1000x-leverage venue’s dashboard showed roughly $5 million in its house pool and no queued payout debt as trading losses funded PAPER rewards.... Read the full story at The Defiant

DefiLlama tracked $137.1 million in trader balances and house liquidity combined. Those funds are not all available to pay winning trades.... Read the full story at The Defiant

Starknet still settles on Ethereum, and its official account described an L1 move as 'a question, not a decision' a day earlier.... Read the full story at The Defiant

Ethereum records show the money passed through an intermediary and four deposit wallets, while the source address retained about 700 ETH.... Read the full story at The Defiant

a16z co-founder and General Partner Ben Horowitz joins James Norman on the inaugural episode of Vintage x Vintage for a conversation spanning entrepreneurship, investing, hip-hop, and what changes when AI makes building dramatically easier.

Ben reflects on going from Netscape to becoming a first-time CEO, why every founder eventually hits a “we’re fucked, it’s over” moment, and what he learned from building a16z around the needs of entrepreneurs. He explains why great investors should look for world-class strengths rather than an absence of weaknesses, and why expanding the ways we recognize talent can raise the bar rather than lower it.

They also look at the current AI cycle, why Ben believes it is bigger than the internet, how AI changes who can become a builder, and why the infrastructure beneath today’s models may need to be rebuilt from the ground up.

Resources:

Follow Ben Horowitz on X: https://x.com/bhorowitz 

Follow James Norman on LinkedIn: https://www.linkedin.com/in/motown/ 

Learn more about Paid in Full: https://paidinfullfoundation.org

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Trading is scheduled for 10 a.m. ET on Oct. 10. User deposits are separate from the house-side pool, which starts at zero and grows from traders’ losses.... Read the full story at The Defiant

Aerodrome holds about $393 million on Base as its planned merger with Velodrome approaches.... Read the full story at The Defiant

The transactions used valid account authorizations, but BlockSec says they do not establish whether the wallet owner knowingly approved the transfers.... Read the full story at The Defiant

Tron records show a 2 million USDT conversion through USDD’s stability module; Bitquery estimates Tether froze $10 million across the wider theft cluster.... Read the full story at The Defiant

The token’s rally outpaced bitcoin and ether, while daily trading on Starknet’s decentralized exchanges rose to about $33.7 million.... Read the full story at The Defiant

The Argentina-first initiative would let customers convert eligible deposits into ONED USD, transfer it around the clock and spend through Visa.... Read the full story at The Defiant

Three wagers costing about $19, $74 and $80 preceded reports of Katie Zacharia’s selection. The contract has settled Yes, but individual withdrawal restrictions remain unclear.... Read the full story at The Defiant

AERO converts one-for-one and VELO at roughly 0.044 new AERO per token; existing locks keep their remaining duration.... Read the full story at The Defiant

The agency says existing exchange and trader duties would stay intact, while a separate rule excludes qualifying casino-style wagers.... Read the full story at The Defiant

The agency bypassed a proposal, citing threats to prediction markets, but says the measure changes no existing compliance obligations.... Read the full story at The Defiant

Hyperliquid's 1000x perps experiment opens tomorrow. Here's how it works, who's lining up, and what could go wrong.

A draft plan would lower maximum annual issuance from 2.5% to 1.6%, reducing both dilution and staking rewards.... Read the full story at The Defiant

Hyperliquid's 1000x perps experiment opens Saturday. Here's how it works, who's lining up, and what could go wrong.

The Money section appears after an incoming transfer, according to Walt, the separate service formerly known as Wallet.... Read the full story at The Defiant

Stage 2 pairs a pro-rata claim on recovered funds and half of Ostium's opening fees with an optional equity allocation priced at the company's next round. The percentages are still unset, and holders have until Oct. 30 to elect.... Read the full story at The Defiant

MistTrack puts reported losses near $90 million as Ledger asks reseller CryptoBilis to halt device sales and shipments.... Read the full story at The Defiant

The four Tron addresses came off the USDT blacklist at 15:30 UTC with their balances intact, and THORChain has restarted Tron trading, deposits and signing. The 19 other wallets frozen in the same sweep are still blacklisted.... Read the full story at The Defiant

The New York settlement ties the money to federal forfeiture and prison-sentence conditions, adding to existing FTC and CFTC restrictions.... Read the full story at The Defiant

NUVA launched on Ethereum in May with vaults tied to YLDS and home-equity credit. The partners also plan to explore tokenized cultural assets.... Read the full story at The Defiant

Buyers from the past 90 days were urged to delay setup or consider moving assets to a new Ledger device with a new seed.... Read the full story at The Defiant

Conflict isn’t necessarily aproof that something’s broken.

If the PIVX community sat down in a couples therapist’s office, the therapist would say something that sounds almost rude at first: of course it’s like this.

A community isn’t a hand-picked team. It’s whoever shows up, from a species that produces generous people and cruel ones, calm people and reactive ones, the occasional genuinely well-adjusted adult and the occasional person running on trauma they’ve never once looked at directly. A DAO doesn’t filter any of that out. It just hands all of it a voting mechanism and a shared treasury and says, good luck. Well, at least the ones that own masternodes. But everyone has a voice.

So the question was never “why does our community have conflict.” Conflict was guaranteed the moment more than a handful of real humans showed up and started caring about the outcome. The actual question is whether it knows how to fight well. Most don’t. That’s not a PIVX problem. That’s a humans problem wearing PIVX merch.

The paradox built into the model itself

A good number of people in the PIVXcommunity have read Rick Falkvinge’s Swarmwise, free online, often treated as close to scripture for how a leaderless movement is supposed to work. It’s a genuinely useful book. It’s also carrying a contradiction most of its readers never clock, because Falkvinge states it plainly, almost in passing, and then builds a model that runs directly against it.

The line is this: accountability and authority go hand in hand.

Then the rest of the book describes a structure built specifically to avoid granting anyone formal authority. Leadership in a swarm isn’t appointed, it’s earned purely by inspiring people, moment to moment, with nothing backing it up but whether others feel like following right now. No one can tell anyone else what to do. That’s the whole design, and it’s a real strength, it’s a big part of why swarm-style organizing can move fast and resist capture.

But read those two ideas side by side and the problem announces itself. If accountability requires authority, and the model deliberately has none, then holding anyone to anything was always going to be fragile by design. The person trying to enforce a line the community already agreed to has no backing, no formal process, no higher body to appeal to. Just whatever social force they can generate in the moment. When that’s not enough, and it often isn’t, they’re left standing there alone, holding a rule nobody’s required to respect.

Structurelessness doesn’t remove power. It just stops you from seeing it

This isn’t a new problem, and it isn’t a crypto problem. In 1970, Jo Freeman wrote an essay called “The Tyranny of Structurelessness” about the feminist collectives of her era, and it’s been cited by basically every leaderless movement since because it names something uncomfortable and true: refusing to build formal structure doesn’t eliminate power. It just makes the power that’s already there, confidence, charisma, tenure, social capital, informal and impossible to check. A group that insists it has no hierarchy still has one. It’s just unacknowledged, which means it can never be held accountable the way an acknowledged one could be.

A DAO with no formal authority isn’t a DAO without power dynamics. It’s a DAO where the power dynamics are real and deniable at the same time, which is worse for the person trying to hold a line, not better. They’re not just fighting the rule-breaker. They’re fighting the community’s own insistence that no one here actually has power to begin with.

When the person enforcing the rule becomes the villain of the story

There’s a specific, well-documented pattern worth naming directly, because once you see it, you’ll recognize it instantly: DARVO. Deny, Attack, Reverse Victim and Offender. Psychologist Jennifer Freyd documented it originally in contexts far more serious than DAO governance, but the mechanism is identical wherever it shows up. Someone breaks an agreed-upon line. Called on it, they don’t address the violation. They deny it happened, attack whoever raised it, and recast themselves as the one under attack.

Watch for it and you’ll see the shape every time: the person holding the community to its own stated rules gets rebranded, in real time, as the aggressor. Not because the facts support that. Because it’s an extremely effective move, and because a structureless group has no mechanism to stop the reframing from taking hold once enough people are confused about who actually started it.

This isn’t abstract for PIVX specifically, and it’s worth being concrete about why. Since I joined this community in 2019, PIVX has stood out against the broader crypto space, loud by default, frequently hostile, often unmistakably hypermasculine, as something genuinely friendlier, as purple. That’s not an accident anyone just enjoyed. It got written down, deliberately, as actual guidelines on the community’s Discord, agreed to by a clear majority, aimed squarely at not scaring off newcomers before they ever got to the technology. A privacy coin for everyone has to actually include people who don’t already know how to survive crypto Discord’s default tone, or the “for everyone” part is just a slogan.

Those guidelines get challenged reliably, and the challenge almost always arrives dressed as a free speech objection. It’s worth being precise about why that doesn’t hold up, rather than just asserting it. Free speech, as a principle, protects your right to say something. It has never meant a right to say it inside someone else’s community, free of any agreed consequence, and it has certainly never included the right to insult. Asking people to be respectful isn’t restricting anyone’s speech. It’s declining to hand a platform to a specific kind of speech nobody was ever owed a platform for in the first place.

One careful distinction matters here, because it’s easy to blur. Disagreeing, in good faith, about exactly where a guideline should sit, whether a specific rule is too strict, too vague, enforced unevenly, is healthy, normal, and should be welcomed outright. That’s not DARVO. DARVO isn’t “I think this line is drawn wrong.” It’s break the agreed line, get called on it, and respond by denying, attacking, and recasting the person enforcing the community’s own stated agreement as the actual aggressor. Those are two entirely different things, and treating every objection as the second one would be its own kind of bad faith.

But here’s the part that actually matters, once that distinction is clear: DARVO shows up constantly, in politics, in families, in every kind of institution that has ever existed. Its sheer prevalence everywhere else is not an argument for tolerating it here. A community that spends real, continuous, deliberate effort trying to stay friendly, open, and welcoming doesn’t get to wave through a widespread bad pattern just because it’s widespread. If anything, the opposite is true. The fact that something is common everywhere else is exactly why a place that worked hard not to be like everywhere else shouldn’t quietly let it back in through the side door.

Reading the book isn’t the same as living it under pressure

Here’s the part that explains why some of the people most fluent in the language of healthy process still fail at it completely the moment things get tense. There’s a real difference, well documented in therapy, between declarative knowledge and embodied behavior. Being able to describe a healthy boundary calmly in a forum post is a different skill than holding that boundary when you’re actually angry, embarrassed, or scared of losing status. Plenty of people can recite the theory perfectly and then abandon every bit of it the second it costs them something personally.

This isn’t hypocrisy, exactly, or at least not only that. Intellectualizing, understanding a concept so thoroughly that the understanding itself starts to feel like the work, is a recognized defense mechanism. It lets a person feel like they’ve done something by knowing the right answer, without ever doing the much harder thing of actually behaving differently under stress.

The reality everyone builds for themselves

And underneath all of it sits the plainest, most universal mechanism of all: motivated reasoning. People don’t usually experience themselves as the one breaking the rule. They’ve already, often without noticing, reasoned their way to a version of events where they were right, a version where the rule didn’t really apply to them, a version where the other person started it. This isn’t a character flaw unique to difficult people. It’s one of the most replicated findings in psychology, and it applies to every single person in this conversation, including whoever’s reading this and nodding along about someone else.

Now, the part worth actually reading twice

None of the above is a reason to feel worse about this community. If anything, it’s close to the opposite.

Here’s what a good therapist tells a couple who shows up exhausted, convinced their fighting means something’s fundamentally broken: conflict was never the warning sign. Avoidance is. The research on this is about as clear as social science gets, relationships that last aren’t the ones with no conflict, they’re the ones that repair well after it. Gottman’s decades of research on couples found that the presence of disagreement predicts almost nothing about whether a relationship survives. What predicts it is whether the people in it can come back together afterward, honestly, without pretending nothing happened and without staying wounded forever.

A community where nobody ever fought about anything wouldn’t be healthy. It would be a community where nobody cared enough to bother. The fights happening in PIVX’s community aren’t evidence the project is failing. They’re the noise made by a genuine number of people who actually give a damn about the outcome, which is a far rarer and more valuable thing than it sounds like from inside the exhaustion of watching it happen.

And if you’re one of the people this exhausts, the one who runs a node quietly, who shows up and votes thoughtfully on proposals, who welcomes a confused newcomer patiently for the fourth time this month, who has never once wanted to be in the middle of a public fight about who said what to whom, here’s the thing worth hearing directly: you are not failing at this because you hate the conflict. You are not required to be the one who wins the argument, outlasts the aggressor, or fixes the people who came here carrying their childhood trauma this community never signed up to treat. That was never your job.

Your job, the one that’s actually been building this network for a decade, is the unglamorous, undramatic, compounding work that was never going to trend on social media. It’s the thing the conflicts are, underneath all the noise, actually fighting over the right to continue doing. The loud moments are visible precisely because conflict is loud by nature, not because they’re the majority of what’s actually happening here. Most of what sustains this project every single day is quiet, and it’s being done, right now, by people exactly like you, whether or not anyone ever tells you that directly.

So: let the people who want to fight about governance fight about governance. Keep doing the thing you were already doing. Ten years from now, nobody will remember the argument. The node you kept running, the wallet feature you tested, the person you helped get set up, that’s the part that was never going to show up in anyone’s screenshot, and it’s also the only part that was ever actually load-bearing.

What a Couples Therapist Would Tell This DAO was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

LiquidAcre, a financial technology company building a platform designed to expand access to real-world assets and digital financial services, has selected Uphold to power trading, custody, KYC, among other services to fulfill part of the infrastructure for tokenized real estate.... Read the full story at The Defiant

a16z's Raghu Raghuram and Guido Appenzeller sit down with Playground Global General Partner and former Intel CEO Pat Gelsinger to discuss the next wave of semiconductor innovation and the physical constraints shaping the AI buildout.

Drawing on his experience designing Intel's 386 and 486 processors, Pat explains how AI could transform chip design, but also why faster design alone won't solve the industry's biggest problems. They examine the bottlenecks in manufacturing, memory bandwidth, advanced packaging, and power, and why today's explosion of specialized AI chips may eventually consolidate around a smaller number of architectures.

They also discuss the potential for new memory technologies, the shift from copper to optical networking, and why energy capacity could become a major constraint on AI growth. Finally, they revisit Pat's VMware years to ask what virtualization might look like when infrastructure is built for agents rather than humans.

Resources:

Follow Pat Gelsinger on X:  https://x.com/PGelsinger

Follow Raghu Raghuram on X: https://x.com/RaghuRaghuram

Follow Guido Appenzeller: https://x.com/appenz

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Per-block computing limits shrink to preserve overall capacity, while validators face more frequent voting and shorter production windows.... Read the full story at The Defiant

The proposed DRS overhaul would replace batch processing with APIs and automate a transfer step, while still requiring transfer-agent approval.... Read the full story at The Defiant

Vitalik Buterin said the risk from AI-accelerated math is real but pointed it at lattices rather than elliptic curves. A former Ethereum Foundation researcher said bunker mode would not help if the curves actually broke... Read the full story at The Defiant

Netflix’s synopsis for “The Altruists” calls it “a toxic love story inspired by a real fraud.” The trailer drew 4.2 million views in seven hours, and the most-shared replies from crypto accounts went at the casting and the accuracy.... Read the full story at The Defiant

OPAIPon displayed a $1,132 price and a 0.49% spread on launch day. Access is restricted to qualifying non-US investors.... Read the full story at The Defiant

The stablecoin has about 2.77 million tokens in total supply, while DOT-backed borrowing is planned for a later phase.... Read the full story at The Defiant

Crude retreated around the president's statement, but bitcoin remained down 1.9% over 24 hours in late trading.... Read the full story at The Defiant

L2BEAT data showed about $17.1 million in canonically bridged ETH; the wind-down plan sets out no independent exit after Dec. 15.... Read the full story at The Defiant

Holders can request fiat or USDT as the project prepares to retire its tokens, but the shutdown documents leave the gold reserves’ disposition unspecified.... Read the full story at The Defiant

An independent chain would let Starknet control security upgrades rather than wait for Ethereum, says StarkWare CEO Eli Ben-Sasson.... Read the full story at The Defiant

The proposed service would extend a custody network spanning the UAE, Luxembourg and Hong Kong. The bank has not announced a launch date.... Read the full story at The Defiant

The NFL just filed a Supreme Court brief siding with New Jersey against Kalshi. Here’s how the league got here.

The new reserve has filled its 30 million-token supply cap, with Aave displaying $29.67 million supplied.... Read the full story at The Defiant

Derive completes its V3 migration, moving onchain options custody to Ethereum and adding ETH, WBTC, and HYPE borrowing.

The network's 2.1 billion APT cap, 2.6% staking reward rate and tenfold gas-fee increase are already live.... Read the full story at The Defiant

StarkWare’s Eli Ben-Sasson floats making Starknet an L1 for “post-quantum agility,” citing AI and quantum threats.

Vitalik Buterin has chimed in on Ethereum’s “bunker mode” debate, sharing practical tips for addresses and multisigs.

After months of failed partnership talks, the NFL is backing states against Kalshi in a Supreme Court fight, as the NBA weighs its own next move.

Users and apps need no changes, but the faster processing relies on different security guarantees from Ethereum finality.... Read the full story at The Defiant

Contributors will run the protocol through DAO DAO organizations, while vxASTRO holders retain the normal unlock process and ASTRO emissions go to zero.... Read the full story at The Defiant

Aave’s Ethereum USDT reserve showed $169.54 million in available liquidity on Oct. 8, after withdrawals coincided with double-digit borrowing rates.... Read the full story at The Defiant

The exposed balance has risen by 222,000 BTC since May, while total Bitcoin supply grew by 64,000 BTC.... Read the full story at The Defiant

The digital identity company plans to seek strategic partners and investors in 2027, while Foundation executives retain board roles.... Read the full story at The Defiant

Eligible US and EU investors can access share-backed tokens through Securitize’s broker-dealer platform; trading on NYSE and OKXICE venues remains planned.... Read the full story at The Defiant

a16z’s Raghu Raghuram sits down with AWS CEO Matt Garman to discuss how AI is reshaping the cloud, from the needs of AI-native startups to infrastructure increasingly designed for agents.

Matt explains how AWS is adapting as agents write code and manage infrastructure, why it’s reserving scarce GPU capacity for startups, and where custom chips like Trainium and Graviton fit into the AI stack.

They also discuss Amazon's $220 billion capital investment, the shifting bottlenecks in the infrastructure buildout, what enterprises need to trust autonomous agents, and how AWS's own teams are building with agents.

Resources:

Follow Matt Garman on X:  https://x.com/mattsgarman 

Follow Matt Garman on LinkedIn: https://www.linkedin.com/in/mattgarman

Follow Raghu Raghuram on X: https://x.com/RaghuRaghuram

Learn more about AWS: https://aws.amazon.com/

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Five intermediary addresses forwarded the tokens to one wallet, which returned 1.25 million HYPE to staking.... Read the full story at The Defiant

Bastion and Coinbase will custody the balances, while transfers to bank accounts in more than 60 countries will carry separate fees.... Read the full story at The Defiant

His personal warning about an AI-assisted cryptographic break drew pushback from Ledger’s CTO, who said a mass migration could cause costly mistakes.... Read the full story at The Defiant

Four equity-linked tokens join the collateral lineup, with 50% collateral ratios in Cross Margin and Portfolio Margin and a separate tiered schedule for Portfolio Margin Pro.... Read the full story at The Defiant

Bitcoin fell through $84,000 in two legs, the first in the Asia session and the second at the U.S. open, and has not reclaimed it. A Bitfinex research note circulated hours earlier had called that level the market's largest cost-basis cluster. Funding rates sat near zero across OKX, Deribit and... Read the full story at The Defiant

Onchain records show the tokens left his Solana wallet at 4:14 a.m. Singapore time and were sold in four equal lots over the nine minutes that followed. The trader says he has found no sign of a breach on his phone or email... Read the full story at The Defiant

The Sept. 8 release keeps enterprise tools commercial. Matter Labs says the Bundesbank is testing a self-hosted deployment.... Read the full story at The Defiant

The first Aave-powered products will target stablecoins and tokenized gold, with outside investors expected to join GSR in the vaults. Opening dates are still to come.... Read the full story at The Defiant

The mainnet release begins private trading tests, while the broader CypherOS privacy platform is planned for a later chain upgrade.... Read the full story at The Defiant

The company reported 6,016,414 ETH as of Oct. 4, while Lee estimates roughly 100,000 tokens remain before it reaches the ceiling.... Read the full story at The Defiant

The FT reports that people familiar with MAS's thinking consider the decentralized venue outside its jurisdiction. Singapore's rules distinguish crypto derivatives on approved exchanges from those offered elsewhere.... Read the full story at The Defiant

ETH and USDG swaps use NEAR Intents to handle cross-chain routing, while bridge infrastructure still moves assets between networks.... Read the full story at The Defiant

Wallets, DEXs and lending protocols need integration changes to handle the assets, whose issuer-selected rules can permit freezes and forced transfers.... Read the full story at The Defiant

Traders read a Sunday post as a tease of POLY. Coplan described an onchain asset tied to the company's economics, named no structure and set no date... Read the full story at The Defiant

Lido Lend targets a fourth-quarter launch, with collateral screening and reliable exits among its design goals. DAO votes and technical disclosures are still ahead.... Read the full story at The Defiant

The wallet app defaults to 50% loan-to-value and charges a 1% borrowing fee, while pledged collateral remains subject to liquidation.... Read the full story at The Defiant

Sepolia's gas limit hit Glamsterdam's 200M target just 11 hours after the fork. Here's how Ethereum's next upgrade makes room for much bigger blocks.

The stable-outlook rating puts Sky in Moody's speculative-grade category, with roughly $90 million in equity against $10 billion in managed assets.... Read the full story at The Defiant

a16z General Partner Angela Strange sits down with Valon’s Andrew Wang and Linda Du to unpack what it takes to rebuild the infrastructure underneath a $13 trillion mortgage market that still relies heavily on systems designed before the internet.

Linda and Andrew explain why Valon chose the hardest path: becoming a regulated mortgage servicer, translating decades of federal and state regulation into software, and proving the platform on its own loans before selling it to the industry. That foundation made Valon roughly three times as efficient as traditional servicing and created the system of record it is now using to bring AI into complex mortgage workflows. They also discuss what AI makes possible on top of that infrastructure, from agents handling long-tail servicing tasks to voice interfaces and more personalized customer experiences. And they explain why deploying the technology into large regulated enterprises is ultimately as much a change-management challenge as a technical one. 

Resources:

Follow Angela Strange: https://x.com/astrange

Follow Andrew Wang: https://www.linkedin.com/in/wangandrewd

Follow Linda Du: https://www.linkedin.com/in/xlindadu/

Learn more about Valon: https://valon.com

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The Stacks Labs chief also promised a two-year roadmap covering Bitcoin privacy and post-quantum technology, plus a public holder call within 30 days.... Read the full story at The Defiant

Coinbase recorded an $83,551 low, while Coinalyze showed $83 million in bitcoin long liquidations over 24 hours.... Read the full story at The Defiant

The stock-index contract uses daily funding payments and futures-account collateral; Kalshi displayed maximum leverage of 15.3 times on launch day.... Read the full story at The Defiant

Coinbase added short-dated up-or-down contracts on bitcoin, ether and eight other tokens to its prediction markets on Tuesday. Kalshi lists the contracts and already runs the same 15-minute markets on its own exchange.... Read the full story at The Defiant

Users can withdraw through the Migration Hub or native bridge, while the team plans to help apps move to other chains.... Read the full story at The Defiant

The payments firm seeks a court order restoring access to its treasury wallet, saying the loss of working capital has slowed client settlements.... Read the full story at The Defiant

Winklevoss Capital Fund has indicated interest in buying up to $100 million of shares, but the potential purchase is nonbinding.... Read the full story at The Defiant

QTC is now tradable through NEAR Intents, giving the quantum-resistant L1 its first real liquidity test against Bitcoin and Zcash.

Pectra lets operators combine validator balances, reducing network overhead without requiring them to withdraw their ETH.... Read the full story at The Defiant

Routable will operate under a new brand, with integrated stablecoin and tokenized deposit offerings rolling out over the coming quarters.... Read the full story at The Defiant

The protocol's first cover positions went to two Sentora vaults, with payouts standing behind 50.2 million XRP staked on Flare. Claims are decided by a five-firm consortium on a three-of-five vote, and the coverage contracts' audits are listed as coming soon.... Read the full story at The Defiant

The planned bank would take over issuance and reserves from Agora’s Bermuda entity, but must meet capital, liquidity and compliance conditions before opening.... Read the full story at The Defiant

RedStone's report puts lending collateral at roughly $81 million against $3.17 billion of supply, with leveraged equity exposure onchain sitting almost entirely in perpetual futures... Read the full story at The Defiant

The first two upgraded epochs finalized, while early blocks began a gradual gas-limit climb from 60 million toward a 200 million client target.... Read the full story at The Defiant

The managers will underwrite and distribute DIGIT, a short-dated bond on HSBC Orion that will sit outside the UK's main debt management programme.... Read the full story at The Defiant

Ripple and hedge fund QRT also joined the financing, an extension of the March round backed by NYSE owner ICE. The amount raised was not disclosed.... Read the full story at The Defiant

The proposed subsidiary would also hold client assets and manage stablecoin reserves, but would not accept deposits or make commercial loans.... Read the full story at The Defiant

Ethena will manage reserves, minting, redemptions and compliance for a platform reporting more than $300 million in existing stablecoin balances.... Read the full story at The Defiant

The WSL HYPE worksheet pairs perpetuals with reference prices across commodities, indexes, equities, currencies and crypto.... Read the full story at The Defiant

The stablecoin goes live on Arbitrum One with Fluid, Morpho, GMX, Maple and Kraken behind it. A proposal published the same day asks ArbitrumDAO to add 100 million ARB to an incentive program that still has about 63.7 million ARB unspent... Read the full story at The Defiant

The new lending option extends the Morpho-based service, while borrowers remain exposed to liquidation under third-party protocol rules.... Read the full story at The Defiant

a16z General Partner David George sits down with Armadin founder and CEO Kevin Mandia to discuss what happens to cybersecurity when attackers can operate at machine speed.

After 30 years in security and building Mandiant, Kevin says AI convinced him to get back on the field. He explains how AI changes the economics of cyberattacks, allowing attackers to probe thousands of paths simultaneously, and why that means defense will ultimately need to become autonomous too. 

They also unpack Armadin’s approach: continuously attacking customers’ systems with AI to find exploitable vulnerabilities before adversaries do, then building toward autonomous defenses that can respond in real time. Kevin shares what Armadin has learned from finding more than 90 zero-days in production environments this year, why humans can’t remain in the detect-and-respond loop, and how the entire security stack could change over the next few years.

Resources:

Learn more about Kevin Mandia and Armadin: https://www.armadin.com/team-members/kevin-mandia

Follow David George on X: https://x.com/DavidGeorge83

Learn more about Armadin: https://www.armadin.com/

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A new filing targets Storm’s venue challenge, while his acquittal motion remains pending and a retrial is scheduled for April 26, 2027.... Read the full story at The Defiant

The notes offer exposure without shareholder rights. Secondary-market prices can diverge sharply from the eventual payout tied to a liquidity event.... Read the full story at The Defiant

Exchanges must give position holders five calendar days' notice and a chance to exit, while leaving other material contract terms unchanged.... Read the full story at The Defiant

The GHO Risk Council also lifted Prime’s base rate, while Ethereum’s USDC conversion module remained nearly empty.... Read the full story at The Defiant

Bitwise's NRR, the first U.S. spot NEAR ETF, drew $35.5M on day one. Hunter Horsley and Sal Ternullo explain the demand and NEAR's AI-first pitch.

A monthly recap of development, projects and community activity across the Verus ecosystem. Verus Core and Verus Desktop

Verus v1.2.18 was released on September 17 as a critical security update. Node operators, infrastructure providers, miners and stakers are urged to upgrade. The corresponding Verus Desktop release is also available.

The update tightens PBaaS consensus validation, addresses ways to disrupt nodes, and fixes memory-safety and concurrency issues across networking, wallet, mempool and RPC code. It follows continued auditing ahead of the planned Ethereum contract upgrades.

There are also performance and compatibility improvements: faster wallet rescans, faster retrieval of chain-tip information, and optimized VerusHash support on older CPUs. The Mac binaries now also run natively on Apple Silicon without Rosetta.

Verus-Ethereum Bridge: an additional security layer

Work continued on the Ethereum bridge’s contracts and verification process. In September, Michael Toutonghi described an additional witness check that compares transfers recognized by the Ethereum contracts with the actual exports and destinations recorded on the Verus side.

Under the described design, four witnesses rejecting a transfer as inconsistent with the chain can stop contract processing. A longer delay for transfers that are neither rejected nor signed by enough witnesses is intended to give the community time to investigate. The witnesses’ rejection authority acts as a circuit breaker.

The earlier bridge security write-up provides background on the recovery work.

Verus Express: VerusID profiles and wallet usability

Development continued on Verus Express, the working name for a lite desktop wallet. September’s update focused on giving VerusID a more visible role: on-chain avatars, banners and descriptions using the standard VDXF keys. Development also included adding verified websites and verified Ethereum and Bitcoin addresses linked to a VerusID.

The work also covers a watchlist for Verus and PBaaS addresses, a larger Help section, and automatic discovery of PBaaS currencies already held in the wallet. The aim is to create the most user friendly desktop wallet experience for the Verus ecosystem.

New websites for Antafri.com and VerusNotes.com

I released the new Antafri.com website, giving the project a refreshed public home while getting ready for the actual release. Antafri’s focus is private bets between friends.

VerusNotes.com introduces a private notes app that uses VerusID to unlock a locally encrypted vault. It makes cloud sync optional, with only encrypted note content sent to the cloud. An early alpha was released in June 2026, but that one is not working anymore. A new release is coming soon.

VerusMetal: an Apple Silicon GPU miner

VerusMetal launched an experimental public preview. Written in Swift and Metal, it runs VerusHash v2.2 mining on Apple Silicon GPUs and checks found shares on the CPU before submitting them to a pool.

The command-line miner supports Stratum pools and reconnects when a connection drops. A signed and notarized executable is available for Apple Silicon Macs running macOS 27 or later, with source code on GitHub.

Get your project mentioned!

The best way is to create a post in the verus-builders section of the Verus Discord. It’s going to need links to either a website or GitHub.

September 2026 — The Verus View was originally published in Verus Coin on Medium, where people are continuing the conversation by highlighting and responding to this story.

a16z Editorial Partner Elena Burger sits down with investing partners Olivia Moore and Josh Elman to unpack the seventh edition of a16z’s Top 100 Consumer AI Apps, including a new dimension this time: what consumers are actually paying for.

The data reveals a striking power-user economy. Only a small share of consumers currently pay for AI, but among those who do, spending is heavily concentrated at the top. Olivia and Josh discuss why developers, creators, and other power users dominate spending today, and why subscriptions may not be the business model that ultimately brings consumer AI to everyone. 

They also dig into the rise of personal agents, the different trajectories of ChatGPT, Claude, and Gemini, how ads could reshape AI economics, and the enormous amount of consumer white space still left to build, from shopping and entertainment to social, dating, and marketplaces.

Resources:

Read the Top 100 Consumer AI Apps, Seventh Edition: https://www.a16z.news/p/top-100-consumer-ai-apps-seventh

Follow Olivia Moore: https://x.com/omooretweets 

Follow Josh Elman: https://x.com/joshelman 

Follow Elena Burger: https://x.com/VirtualElena

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a16z General Partner David George joins Jack Altman on Uncapped to make the case that many of the biggest debates in AI are framed the wrong way. Frontier models or open source? Labs or applications? David’s answer is often “and.” With AI adoption still concentrated among a relatively small group of heavy users, he argues there could be room for multiple layers of the stack to grow at once. 

David and Jack discuss why demand for compute continues to outstrip supply, why applications can thrive even as frontier labs expand into new products, and why consumer AI may still be at the beginning of its biggest shift, from reactive chatbots to proactive assistants that can act on our behalf. 

They also zoom out to autonomy, robotics, healthcare, and the next generation of technology companies, before turning to venture itself: why David believes today’s product cycle is unusually strong, how capital can accelerate AI companies in ways it couldn’t during the SaaS era, and why founders and narrative become increasingly important as companies scale. 

This conversation originally appeared on Jack Altman’s Uncapped.

Resources:

Follow David George on X: https://x.com/DavidGeorge83

Follow Jack Altman: https://x.com/jaltma

Listen to more from Uncapped: https://www.youtube.com/@uncappedpod

 

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Bitcoin passes most of the classical tests for money. The one it fails isn’t small.

Bitcoin’s case for being sound money rests on a real, serious argument, one worth taking at full strength before questioning any part of it. Economists have used a standard set of properties to evaluate candidates for money for a very long time: durability, portability, divisibility, verifiability, scarcity, and fungibility. Bitcoin’s advocates didn’t invent this framework to flatter their asset. It predates Bitcoin by centuries. It’s also the right framework to actually use here, because it lets both Bitcoin and PIVX be measured against the same bar, rather than one built to favor either side.

Run Bitcoin through it honestly, and it earns high marks on almost everything.

Where Bitcoin genuinely delivers

Durability: a Bitcoin can’t rot, corrode, or degrade, its existence is guaranteed by a distributed network rather than a physical object that can be damaged or lost to time. Portability: value that once required an armored truck to move now moves at the speed of a broadcast transaction, across any border, to anyone, without asking permission. Divisibility: a single bitcoin splits into 100 million satoshis, fine enough for any transaction size that matters. Verifiability: anyone can audit the entire supply and every transaction in it, no trust required, no institution’s word to take.

And scarcity, the property Bitcoin is most famous for, is real and mathematically enforced. 21 million coins, full stop, a supply schedule no committee can vote to change. That’s a genuinely hard thing to build, and it’s why Bitcoin earned the nickname “digital gold.” The comparison is apt in more ways than one, which becomes relevant in a moment.

Where it fails, and fails structurally

Now the sixth property: fungibility. This is where the classical case for Bitcoin as money runs into a problem that isn’t small, isn’t temporary, and isn’t fixable without changing what Bitcoin fundamentally is.

Fungibility means every unit is interchangeable with every other unit, no bitcoin should be worth more or less, or more or less usable, than any other bitcoin, based on where it’s been. That’s not a nice-to-have for money. It’s close to the whole point. Money exists so strangers can transact without needing to investigate each other’s history first. The moment a currency’s units start carrying baggage, that function breaks down.

Bitcoin’s entire transaction history sits permanently on a public ledger, visible to anyone, forever. In practice, this doesn’t stay theoretical. Chain-analysis firms exist specifically to trace that history, and exchanges and custodians routinely act on what they find, flagging, discounting, or outright refusing coins whose history touches a mixer, a sanctioned address, or anything else their algorithms don’t like. That means, in the real world, not every bitcoin is treated the same. Some are worth less, or worth nothing at certain venues, purely because of where they’ve been, through no action of the current holder. That’s a textbook fungibility failure, and it’s structural, not a bug that gets patched. It’s the direct, unavoidable consequence of a permanent public ledger, the same design choice that gives Bitcoin its verifiability.

Give Bitcoin its due for the trade-off it made. Public verifiability is genuinely valuable, and Bitcoin chose it deliberately. But a currency can’t fully deliver both total transparency and full fungibility at the same time. That’s not a criticism, it’s a fact about what each design choice costs. Bitcoin picked transparency. The bill for that choice comes due exactly where fungibility is supposed to live.

What changed since 2009

It’s worth being precise about why this wasn’t always the obvious criticism it is today.

In 1993, Eric Hughes’ Cypherpunk Manifesto laid out a goal that Bitcoin, launched in 2009, did more than anything before it to actually deliver on: money that didn’t require permission from, or visibility to, any institution. And for Bitcoin’s first several years, that promise held up reasonably well in practice, not because the ledger wasn’t public, it always was, but because almost nobody had built the tools needed to actually exploit that transparency at scale. Chainalysis, the company that essentially invented commercial blockchain forensics, wasn’t founded until 2014, five years after Bitcoin launched, and it was born directly out of investigating the Mt. Gox collapse, not out of some pre-existing surveillance infrastructure waiting for Bitcoin to arrive.

That gap has closed entirely. Blockchain forensics is now a multi-billion-dollar industry, Chainalysis alone has raised over $500 million and is valued at $8.6 billion, serving governments, exchanges, and banks across dozens of countries. KYC requirements are close to universal at any on-ramp or off-ramp a normal person would actually use. And the tooling keeps compounding: Chainalysis’s own current marketing explicitly promotes AI systems built to scale investigation and compliance work to, in the company’s own words, the speed of crypto. What took a determined analyst days to trace by hand a decade ago, an automated system now does continuously, at scale, across the entire chain, indefinitely.

None of that required Bitcoin to change. The ledger works exactly the way it always did. What changed is everything built to read it. A design that delivered on the manifesto’s promise reasonably well in 2009, simply by virtue of nobody having built the surveillance layer yet, doesn’t deliver on that same promise by default in an environment where deanonymizing a public ledger is now a mature, well-funded, AI-assisted industry. The values haven’t moved. The technology required to actually protect them has, and Bitcoin’s architecture was fixed years before that technology arrived.

The other classical question: does anyone spend it?

There’s a second, quieter problem worth taking seriously, and it’s one mainstream monetary economists were making arguments about long before cryptocurrency existed, not a crypto-native complaint invented to attack Bitcoin specifically.

An asset that’s widely expected to keep appreciating faster than the price of goods and services gives its holders a straightforward, rational incentive: hold it, don’t spend it. Every purchase becomes an opportunity cost against a rising asset, and the smart move, individually, is always to wait. That’s a fine strategy for a savings vehicle. It’s a real problem for something trying to also function as a medium of exchange, the thing that actually circulates and gets used, rather than sitting untouched in cold storage. This is precisely why most functioning currencies, historically and today, target mild, predictable, positive inflation rather than a hard cap or deflationary schedule, not because inflation is virtuous in itself, but because a currency people are incentivized to hoard is failing at half of what money is supposed to do.

PIVX’s supply isn’t fixed. It follows a disclosed, algorithmic tail emission, a fixed, flat number of new PIV created every block, indefinitely, rather than a hard cap or a halving schedule that eventually approaches zero. The absolute emission doesn’t shrink. What does shrink, steadily, is the resulting inflation rate as a percentage of total supply, since the same flat number of new coins matters less every year against an ever-larger base. That’s a deliberate design difference, not an oversight, and measured against the classical goal of money that actually circulates, it points the right direction. A currency whose supply grows slowly and predictably gives holders less reason to sit on it indefinitely, and more reason to treat it as something meant to move.

Where this actually lands, and it isn’t “sell your Bitcoin”

None of the above is an argument that Bitcoin is a bad place to store wealth. Its scarcity case is real, its track record is real, and plenty of people have entirely legitimate reasons to hold it for exactly that purpose. I’m not arguing that PIVX should replace Bitcoin as a store of value. That would be a much weaker, much less interesting point, and it isn’t the one worth making.

The actual argument is narrower and, I think, considerably stronger: Bitcoin cannot fix its own fungibility problem without abandoning the transparent ledger that makes it Bitcoin. That gap doesn’t need to stay open, though, because nothing requires that the same asset handle both jobs, storing value and moving privately through the world, by itself.

Think of it as two different moments in money’s life, not two competing coins fighting for the same role. Bitcoin can do what it does best: sit as a scarce, durable, verifiable store of value, digital gold, held for years, unspent. PIVX exists for the other moment, when value actually needs to move, when it stops being savings and becomes a purchase, a payment, a transaction with another human being who doesn’t need or deserve a window into everything that wallet has ever touched. PIVX’s zk-SNARK shielded transactions break the public trail at exactly that junction. Not by hiding a crime. By restoring the property money is supposed to have by default, and that Bitcoin’s own design permanently forecloses on: no history attached to the unit changing hands.

The one honest caveat worth stating plainly: getting from Bitcoin to PIVX still requires an exchange somewhere, and if that exchange is the kind that collects your identity, a link could exist at that single point. This is worth taking seriously rather than waving away. It’s also a solved problem in practice, not a theoretical gap. PIVX’s own website lists a range of exchanges that require no personal information at all, swap services built specifically around no registration, no email, and no KYC, several explicitly designed for exactly this kind of private conversion. Once PIVX is in a shielded wallet, spending it doesn’t require going back through a centralized, identity-linked venue at all, there are already real ways to convert PIV directly into everyday purchasing power, gift cards, goods, and services, without an account or a KYC form anywhere in the chain. The mechanics exist today. The gap between “sound store of value” and “actually private to spend” isn’t hypothetical, and it isn’t unsolved.

The reframe

This article was never really about Bitcoin versus PIVX, and treating it that way undersells the actual point. Bitcoin built something genuinely remarkable: scarce, verifiable, portable digital value, the store-of-value half of sound money, done about as well as it can be done on a fully public ledger. What it can’t do, by its own founding design choice, is fix its fungibility on its own. That’s not a failure of effort or imagination. It’s the direct cost of the transparency Bitcoin chose on purpose.

PIVX isn’t trying to win the store-of-value argument. It’s built for the part of sound money that Bitcoin’s own architecture permanently can’t provide for itself, privacy at the moment value actually moves, from savings into the world, between one person and another, the way money was always supposed to work before every transaction came with a permanent, public paper trail attached.

Sound Money Needs More Than Scarcity was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

A16z’s Erik Torenberg sits down with OpenRouter’s Alex Atallah and Replit founder and CEO Amjad Masad to discuss why the future of AI may look less like one all-purpose model and more like an ecosystem of specialized models working together.

Alex explains why OpenRouter is betting on “neurodiversity”: different models trained in different ways, routed and combined based on the job at hand. Amjad makes a similar case from inside the enterprise, where companies increasingly need to own their AI capabilities rather than depend entirely on a single model provider. 

They explore what happens when general-purpose agents give way to teams of specialized agents, why smaller models can sometimes be cheaper, safer, and easier to control, and how routing and model fusion could deliver frontier-level performance at lower cost. They also get into agent-to-agent communication, AI security, and why the next generation of companies may need an independence layer across models, clouds, and data.

Resources:

Follow Alex Atallah on X: https://x.com/alexatallah

Follow Amjad Masad on X: https://x.com/amasad

Learn more about OpenRouter: https://openrouter.ai

Learn more about Replit: https://replit.com

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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

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CryptoPunks sales are surging while the collection's grails are moving for millions again.

CryptoPunks sales are surging, and the collection's grails are selling for millions again. Here's everything you need to know.

The SEC's new proposal would let advisers and funds use state trust companies, and in limited cases self-custody, to hold crypto.

Blast is sunsetting its Ethereum L2 after costs outran revenue.

The EF and Open Anonymity's new zkAPI lets you prepay for AI and other APIs on Ethereum, then spend with ZK proofs so usage isn't tied back to you.

a16z’s Seema Amble and Elena Burger sit down with Lio co-founder and CEO Vladimir Keil to ask where AI-native startups have an advantage when incumbent software companies already own the customer, the data, and the system of record.

Their answer comes down to the work that happens outside those systems. In procurement, a final price in an ERP can hide hundreds of emails, spreadsheets, supplier conversations, engineering analyses, and decisions across legal, finance, and operations. Vlad explains how Lio uses multi-agent systems to take on more of that end-to-end work, from sourcing and RFQs to negotiation, shipment tracking, and invoices.

They also discuss how enterprises learn to trust agents with increasingly consequential decisions, why the last 20% of an internal AI build can require most of the effort, and what happens when both buyers and suppliers have agents working on their behalf.

Resources:

Follow Vladimir Keil on X: https://x.com/askvladi?lang=en 

Follow Vladimir Keil on LinkedIn: https://www.linkedin.com/in/vladimir-keil/

Follow Seema Amble on X: https://x.com/seema_amble 

Learn more about Lio: https://www.lio.ai/ 

Seema Amble’s “Investing in Lio” article: https://a16z.com/announcement/investing-in-lio/

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Can Derive V3, an Ethereum-native rebuild, help the protocol take on Deribit?

a16z’s Joel de la Garza sits down with DoxxNet founder Barrett Lyon to discuss what it would take to rebuild the internet around privacy, direct communication, and less dependence on centralized intermediaries.

Barrett explains why he thinks traditional VPNs only solve part of the problem and how DoxxNet is building a parallel mesh network where users can communicate peer-to-peer, transfer large files, make calls, and message without routing those interactions through a central application server. He also explains why the company owns its infrastructure and runs its AI systems locally rather than relying on third-party inference providers. doxxnet_assembly

They also get into the growing amount of tracking embedded across the internet, what happens when that data can be analyzed by increasingly capable AI, and why Barrett believes the underlying protocols of the internet are due for another wave of experimentation. Along the way, he shares lessons from decades of building internet infrastructure, from fighting early DDoS attacks to mapping the internet and building global networks.

Resources:

Learn more about DoxxNet: https://doxx.net

Follow Barrett Lyon on X: https://x.com/BarrettLyon

Follow Joel de la Garza on LinkedIn: linkedin.com/in/3448827723723234

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zAccounts leverage Panther’s privacy-preserving architecture to enable confidential transactions and serve as the gateway to entering Panther Protocol. On this blog, we explain what a zAccount does and how it interacts with Panther’s Multi-Asset Shielded Pool (MASP). 

What is a zAccount

A Panther zAccount is a private, onchain identifier that acts as a secure gateway to confidential DeFi transactions. Through the zAccount, users can satisfy compliance requirements, hold zAssets—Panther's privacy-enhanced representations of deposited assets—and participate in confidential transactions within Panther: 

Creation & Activation: Users connect their externally-owned account (EOA), complete compliance requirements through approved third-party providers, and activate their zAccount. These requirements may include identity verification, wallet risk screening and other eligibility checks. A unique zAccount ID is registered in a public lookup table maintained by Panther’s smart contracts. Root Keys: Each zAccount is tied to two root public keys—one for spending and one for reading. These enable secure access to zAssets while keeping operations shielded. UTXO Integration: zAccounts are implemented as special UTXOs (Unspent Transaction Outputs), which represent individual spendable records, in append-only Merkle trees. Every zAsset UTXO is assigned to a specific zAccount owner via unique spending keypairs. This ensures only the rightful owner can spend assets, while non-interactive transfers allow seamless, private peer-to-peer movement.

This architecture delivers:

Unlinkability: External observers can’t easily connect your trades back to your Externally Owned Account (EOA). Non-Interactive Transfers: Send zAssets privately to another zAccount holder using their public read/spending keys from the registry. How zAccounts interact with Panther’s MASP

zAccounts strike a powerful balance between privacy and real-world usability, allowing privacy and compliance to coexist within the same infrastructure. Panther’s zAccounts interact with the MASP when users swap assets, mint them within the shielded pool, and withdraw them. 

Deposit & Mint: Link your EOA, activate your zAccount, and deposit assets to mint zAssets inside the shielded pool. Private Trading: Use zSwap via DeFi adaptors—all tied to your zAccount and bundlers. External observers can not directly link the swap to the user´s identity or EOA. MEV Protection & Alpha Safeguarding: Trading strategies, position sizes, and timing remain hidden, reducing the risk of front-running and strategy replication. Withdrawal: Redeem zAssets back to your EOA or another address, with full user control. Rewards & Fees: Certain activities within Panther may earn Panther Reward Points (PRPs), a non-transferable internal rewards mechanism that encourages participation and helps strengthen the protocol's privacy set. Users can also manage gas and protocol fees directly from their zAccount balances. Panther's zSwap lets users execute confidential, privacy-preserving token swaps on DEXs where users can choose bundlers, regular or fast processing, and max slippage.

Zone Managers define entry rules, but once inside, users enjoy strong anonymity sets shared across the pool—making individual transactions harder to distinguish. Unlike fully anonymous mixers (which face regulatory hurdles) or transparent DEXs, zAccounts enable programmable privacy—strong defaults with flexible compliance hooks.

Getting Started with Panther

Panther’s DAO-operated shielded pool can be accessed by visiting the Panther dApp (pantherdao.app or equivalent interface). Users can also find the dApp link on the pantherprotocol.io website and in the bio of Panther Protocol’s official X account: https://x.com/ZKPanther.

To access the DAO-operated shielded pool, users have to:

Connect their wallet.  Generate two public keys. Complete the required compliance attestation. Activate their zAccount to begin depositing/minting zAssets. Upon zAccount completion, users can track their private balances on the Panther dashboard.

Panther Protocol enables independent, third-party compliance providers to handle user verification and regulatory checks without the protocol itself storing or processing private user data. Compliance providers like PureFi issue cryptographic credentials after verification, allowing users to generate zero-knowledge proofs in their browsers to prove compliance without revealing underlying personal data. Panther Protocol itself remains agnostic, and Zone operators could select their own compliance provider for users to gain access. Always review the latest updates, as features and compliance measures evolve through the Panther DAO.

To interact with Panther Protocol smart contracts via the dApp, users must first download Panther’s zero-knowledge circuits and related client-side components. Panther’s zk circuits run locally in the user's browser or application environment. As decided by the Panther DAO, the daily deposit limits are $25,000 and withdrawal limits are $100,000.

Panther's shielded pool UI displays the daily deposit and withdrawal limits. Internal MASP transfers are also enabled on Panther's Base deployment by navigating to the "Send" tab. The Future of Private Ledgers

zAccounts represent a mature evolution in privacy tech: not all-or-nothing anonymity, but user-controlled confidentiality supported by compliance mechanisms and designed to integrate seamlessly with DeFi. As Panther expands across different EVM-compatible chains, zAccounts will power the next wave of sophisticated, privacy-first onchain finance. Panther´s zAccounts are built not only to enhance user privacy but also to align flexibly with the intricate demands of decentralized finance and operators. 

About Panther Protocol Foundation

Panther Protocol Foundation is a non-profit organization supporting the Panther ecosystem through research, ecosystem funding, software stewardship and open-source development.

The Foundation does not operate the Panther protocol, host deployments, custody assets, execute or intermediate transactions, or provide financial services.

The proprietary Panther dApp is licensed by the Foundation to support independent ecosystem deployments.

Users interact directly with smart contracts from their own wallets, signing every transaction themselves. Compliance credentials are issued and managed by independent third-party providers.

Please review the applicable notices, disclosures and jurisdictional restrictions available through the Panther interface before interacting with the protocol.

For more information, visit panther.org

To learn more about Panther Protocol, visit pantherprotocol.io

Here's everything the HOOD Summit revealed, from 10x perps to Robinhood's answer to Fomo.

OUSD, a new Stripe-issued stablecoin, is live across four chains.

Robinhood launched greater abilities for agents, the rollout of perpetuals in the U.S., and the debut of their social feed, all while dealing a blow to Lighter in the short term.

a16z’s David George, Sarah Wang, Alex Immerman, and Santiago Rodriguez unpack 25 key charts from the latest State of Markets presentation, from the scale of the AI infrastructure buildout to what adoption looks like inside companies today.

They examine why rising markets have so far been supported by earnings rather than multiple expansion, why hyperscaler CapEx is approaching $1 trillion annually, and why demand for compute continues to outrun supply. They also look at the downstream effects of that spending across chips, power, construction, and physical infrastructure. State of Markets

Then they move up the stack: OpenAI and Anthropic’s revenue growth, the gap between AI deployment and measurable enterprise impact, the rise of agents, falling inference costs, and what all of this means for SaaS. They close with where the team is spending time next, including consumer agents, robotics, autonomy, AI and biology, personal health, defense, and the continued diffusion of AI across the enterprise. State of Markets

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Bitget's hackers tried to push $50M+ through NEAR Intents and got turned away.

House Oversight expanded its prediction-market insider trading probe to Hyperliquid, Crypto.com, and PredictIt.

Bitwise looks set to launch its NEAR ETF, offering direct NEAR exposure alongside staking rewards through NYSE Arca.

CFTC approval gives Coinbase its own clearinghouse, bringing more of its regulated U.S. derivatives business in-house.

a16z General Partner Anish Acharya sits down with Assistant Benchmark creator David Pawlan to unpack the sudden explosion of personal AI agents and what it will take for one to become part of everyday life.
David has been testing dozens of assistants across real-world tasks, from managing email and booking travel to handling financial admin. They discuss why the most useful agents may become increasingly invisible, proactively checking you into flights, finding refunds, filing reimbursements, or simply handling the small tasks that pile up across everyday life.
They also explore whether the winning interface is an app, text thread, voice, or wearable; how much autonomy consumers will actually give their agents; and what happens when agents start interacting with other agents. From commerce and restaurant reservations to entirely new agent-native services, Anish and David ask what the internet looks like when software starts acting on our behalf.

This episode was recorded on September 24, 2026.

 

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Federal courts are increasingly backing state gaming laws over prediction markets as the fight heads toward the Supreme Court.

Federal courts are increasingly backing state gaming laws over prediction markets as the fight heads toward the Supreme Court.

a16z’s Ben Horowitz and Martin Casado sit down with TypeSafe AI founder Diogo Almeida to ask a simple question: AI has become remarkably capable, so where is all the automation?

Diogo argues that coding agents may help us write software faster, but the software they produce still largely works the way software always has. TypeSafe is taking a different approach with Jev: putting intelligence inside software itself, so developers can build programs that reason about intent and make probabilistic decisions rather than simply generate text for a human to interpret.

They discuss why reliability is the key to making AI genuinely programmable, how this could open a new era of probabilistic software, and why established SaaS companies may be particularly well positioned to benefit. Ultimately, Diogo’s goal is straightforward: technology that can reliably “do what I mean.”

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a16z’s Katie Kirsch sits down with Harvey VP of Talent Maggie Landers to discuss what happens inside a company growing at AI speed, and how you preserve culture while adding more than 1,000 employees in a year.

Maggie explains why Harvey prioritizes progress over perfection, how its values of simplicity, decisiveness, and “job’s not finished” shape the way people work, and why moving quickly requires giving employees significant trust and autonomy. For people accustomed to being the “A student,” that can mean learning to experiment, make mistakes, and course-correct quickly.

They also get into how Harvey identifies people who can thrive in that environment, what changes when most of your company is relatively new, the role its founders play in maintaining culture, and why judgment becomes increasingly important when employees are given the freedom to move fast.

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Erik Torenberg sits down with Box CEO Aaron Levie, and a16z’s Martin Casado, and Steven Sinofsky to debate how the AI industry should think about safety, security, and regulation as increasingly capable agents move into the real world.

They argue that much of today’s conversation is happening before we have clearly defined the risks we’re trying to regulate. Drawing on earlier waves of computing, from computer viruses and the early internet to aviation and automobiles, they ask what AI can learn from industries that developed safety standards only after understanding how their technologies actually failed.

The conversation then gets concrete: agents don’t get tired, can operate at enormous scale, and can probe systems in ways human employees never could. That could require rethinking permissions, authentication, operating systems, and the security stack itself. They also discuss why AI innovation may increasingly move beyond the frontier labs and into the software built around the models.

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Digging into IMD, the rising AI experiment that has the potential to become a new kind of prolific workforce.

A new kind of AI workforce is ascending in the Ethereum ecosystem, replete with experimental tokenomics. Here's why it matters, and how you might consider the trade.

a16z’s Erik Torenberg sits down with Josh Elman, Olivia Moore, and David Booth to introduce Cosign, a new product built around professional reputation and the people, companies, and products you’re willing to put your name behind.

They unpack a simple idea at the heart of Silicon Valley: some of the most valuable professional signals aren’t credentials, but who believes in you. From the mentor who shaped your career to the colleague you’d work with anywhere or the young builder you think everyone should be watching, Cosign is an attempt to make those signals more visible and durable.

They also discuss why human endorsements may become more valuable as AI makes outreach and information abundant, what existing professional networks get right and miss, and how making reputation more legible could help talented people get discovered earlier, find collaborators, and carry the work they’ve done behind the scenes into whatever they do next.

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Expanding its USDe basis trade to Binance equity perps means Ethena, in theory, opens itself up to a $150T+ market of real-world assets.

A backend wallet breach drained $351.6M as hackers consolidate funds into ETH and investigators probe a DPRK link.

The daily dividends would apply to all preferred stocks: STRC, STRF, STRK, and STRD, aiming to improve price stability, liquidity, and investor trust.

If you've tuned out NFTs during the memecoin era, you may be missing today's non-fungible resurgence.

New York alleged Polymarket operates as gambling and is seeking to block the platform in the state.

The proposed Shielded Bitcoin metaprotocol would use Zcash-style private notes to hide BTC transfers without changing Bitcoin consensus.

Mercator lets agents discover, pay for, and combine use outside tools, improving their performance on domain specific tasks along the way.

On 10 September, Global Digital Finance (GDF) convened two roundtables with the Bank of England, with participation from the Financial Conduct Authority (FCA), GDF members and industry experts. Both sessions were held under the Chatham House Rule.

The first roundtable focused on the Bank of England’s draft Code of Practice for systemic stablecoins and the proposed joint Bank of England-FCA regulatory approach. Moving beyond the headline policy choices, participants tested how the regime would work in practice across real business models, payment flows and market infrastructure. Key themes included how the temporary £40bn issuance guardrail would be reviewed and adjusted, what T+0 redemption means once KYC/AML checks and cross-border payment rails are factored in, the treatment of custody and omnibus structures, and the value of a phased transition into systemic supervision. A wider theme was that the UK regime must work across the full stablecoin ecosystem, not only at issuer level.

The second roundtable used GDF’s Global Stablecoin Regulatory Playbook as a framework for discussing international regulatory convergence, functional equivalence and cross-border recognition. With broad agreement across major jurisdictions on what a credible fiat-backed stablecoin regime should achieve, the discussion centred on how different national regimes can interact. Participants explored the distinction between redemption and convertibility, the Bank’s openness to deference for overseas-issued systemic stablecoins, the risks of liquidity fragmentation from multi-issuance requirements, and the role of international standard setters such as the FSB and FATF.

The central takeaway was that the next phase of stablecoin regulation is less about making rules identical and more about building the regulatory trust, evidence and supervisory mechanisms that allow well-regulated stablecoins to operate across borders without unnecessary fragmentation.

Date:
September 2026

The post Bank of England Stablecoin Roundtables Readout | 10 September 2026 appeared first on GDF.

a16z crypto General Partner Eddy Lazzarin joins Theo Jaffee on MTS to debate the increasingly prominent calls to slow AI development and whether the current safety conversation is conflating very different kinds of risk.

Eddy argues that the debate puts too much emphasis on speculative superintelligence and not enough on the costs of delaying useful technology. Rather than treating every AI failure as evidence of an alignment problem, he makes the case for familiar tools like cybersecurity, accountability, liability, market incentives, and stronger technical controls.

They also discuss whether AI models can develop reputations for trustworthiness, the risks of concentrating oversight among a small group of evaluators, and why Eddy thinks the collision between Silicon Valley’s AI debates and broader politics could fundamentally reshape the conversation over the next year.

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BlackRock says AI agents could drive stablecoin payments and help create new markets for trading and financing compute.

Blockchain.com and the NYSE are teaming up to bring tokenized U.S. stocks and ETFs to Blockchain.com’s global users through the exchange’s planned 24/7 onchain trading venue. What’s the Scoop? NYSE taps Blockchain.com: T…

CFTC staff warns mention markets carry elevated manipulation risks after cases involving George Santos, White House staff and others.

BTC:ETH::ZEC:NEAR! How Zcash and NEAR are drawing capital away from Bitcoin and Ethereum.

Join Firo: Private cryptocurrency infrastructure, BasicSwapDEX, Particl and PIVX!

🗓️ Sept 30th 9:00 am EST/1:00 pm
📍 Xspace
🎙️ Guest GinoFPM from Zano

Topic: Recent AI breakthroughs and their significance to private crypto Link to follow.

#Privacy #AI #Cryptocurrency #Finances

Tune in for the next Privacy Roundtable was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

Erik Torenberg sits down with Replit founder and CEO Amjad Masad and Horowitz and Andreessen Academy co-founder and CEO Gagan Biyani to ask what education should look like for a generation growing up with AI.

Amjad argues that one of the most valuable things young people bring to society is their willingness to question deeply held assumptions. They discuss how education could create more room for that instinct through project-based learning, intellectual side quests, and giving students the freedom to follow an idea deeply rather than optimizing around grades and credentials.

They also explore whether young founders are being pushed to professionalize too early, why Amjad thinks starting a company can sometimes be a form of “premature optimization,” and how curiosity led him from learning chess to experimenting with AI that can conduct machine-learning research.

Finally, they discuss trust, judgment, and what it means to develop as a person, not just a builder, including why being contrarian and ambitious still needs to be balanced with the ability to work with other people.

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Last cycle mainstreamed Bitcoin. This one may belong to Zcash and alts with real revenue, buybacks, and newly opening U.S. markets.

Last cycle mainstreamed Bitcoin. This one may belong to Zcash and alts with real revenue, buybacks, and newly opening U.S. markets.

Coinbase launches fixed-rate, bitcoin-backed USDC loans powered by Morpho Midnight on Base.

Prediction market Trueo is migrating from Base to Ethereum mainnet, earning praise from Vitalik Buterin.

Circle sells Binance $100M in discounted CRCL shares as the pair expand their USDC deal.

Ben Horowitz and Erik Torenberg sit down with Gagan Biyani to introduce the Horowitz and Andreessen Academy and discuss a bigger question: what should education look like when AI is rapidly changing the skills people need to build, work, and create?

Ben and Gagan explain why they believe learning should be more focused on doing rather than studying about doing, with students building real projects, developing people skills, and working alongside companies and builders in San Francisco. The goal isn’t to replace college for everyone, but to create a different path for young people who already know they want to build.

They also discuss why AI could make this an unusually powerful time to be young, how project-based learning changes when everyone has access to powerful tools, why failure can be valuable when it produces real learning, and what it takes to develop the judgment and people skills that can't simply be learned from a textbook.

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Robinhood sees blockchains upgrading markets, with tokenized assets, perps, and AI agents at the center of its next phase.

Lighter's prover repository just got a "Binary options support" commit.

Robinhood sees blockchains upgrading markets, with tokenized assets, perps, and AI agents at the center of its next phase.

a16z Board Partner and former Microsoft Windows president Steven Sinofsky joins Theo Jaffee and Sofia Puccini on MTS to argue that the language we use to describe AI failures is making it harder to understand what’s actually going wrong.

Steven takes aim at terms like “alignment,” “goal-seeking,” and “rogue agents,” arguing that they can anthropomorphize problems that software engineers have dealt with for decades. His framing is simpler: when software doesn’t do what it’s supposed to do, it has a bug. And as AI becomes more widely deployed, labs need the same kind of telemetry, debugging, incident reporting, and operational discipline that previous generations of software eventually developed.

Drawing on everything from early computer hacking and Microsoft’s response to major software failures to Y2K and cybersecurity standards, Steven makes the case for treating AI reliability as an engineering problem. They also discuss what AI labs can learn from CVE reporting, why industry has a responsibility to make its systems safer, and how confusing terminology can lead to equally confused regulation.

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This report draws on a GFTN/Ripple Policy Summit roundtable at Point Zero Forum, building on GDF’s Global Stablecoin Regulatory Playbook, to examine the gap between well-understood stablecoin regulatory principles and their inconsistent, jurisdiction-bound implementation.

It covers:

(1) the need for a shared taxonomy and classification of stablecoins by risk profile rather than label.

(2) the core building blocks of credible domestic frameworks — reserve composition, redemption rights, and proportionate financial-stability requirements.

(3) two competing models for scaling stablecoins across borders — multi-issuance (unified token, multiple local issuers) versus equivalence/recognition regimes (home-jurisdiction oversight extended abroad) — with examples from the EU, UK, Singapore, and UAE.

(4) three near-term priorities for closing the gap: FSB-aligned gap analyses, presumptive equivalence built on existing bilateral cooperation, and supervisory colleges that assess issuer networks collectively. The report concludes that the regulatory tools already exist and what’s needed now is deliberate adoption, jurisdiction by jurisdiction.

Date: September 2026
Publisher: GFTN, in collaboration with GDF, Ripple, and the Point Zero Forum

The post Global Stablecoin Regulatory Frameworks: Closing the Gap appeared first on GDF.

Ben Horowitz and Erik Torenberg sit down with Nas, Grandmaster Caz, and Steve Stoute for a conversation about the Paid in Full Foundation and its mission to recognize and support the pioneers who built hip-hop.

Ben, Nas, and Steve share how the foundation began, why simply giving artists money wasn’t enough, and how the Hip Hop Grandmaster Awards became a way to pair financial support with the recognition many foundational artists never received. Caz brings the perspective of one of those pioneers, reflecting on his role in hip-hop’s earliest history and what receiving the award has meant for his life and legacy.

They also discuss the enormous cultural and commercial impact of hip-hop beyond music, from language and fashion to some of the world’s biggest brands, why so many of its pioneers captured so little of that value, and what happens when generations of hip-hop finally come together in the same room.

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a16z Partner Josh Elman joins Ollie Forsyth on New Economies to discuss the next wave of consumer AI and what separates a product people try once from one that becomes part of their everyday lives.

Josh argues that getting attention has actually become easier, but getting consumers to stick is harder than ever. He explains what he looks for in consumer products, why the best ones start with a narrow wedge and earn the right to do more, and why trust becomes increasingly important as AI agents gain access to more of our personal lives.

They also explore personal AI agents, the future of shopping and entertainment, why we haven’t seen another major social network emerge, and how AI could make technology more social rather than less, including agents that help people spend more time together in the real world.

This conversation originally appeared on the New Economies podcast.

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Databricks co-founder and CEO Ali Ghodsi joins a16z General Partners Martin Casado and Sarah Wang for a conversation about AI risk, recursive self-improvement, cybersecurity, and what’s actually holding back enterprise adoption.

Ali argues that today’s models are already capable enough to automate far more work than most companies are using them for. The bigger problem is context: models haven’t been in every meeting, don’t understand how decisions actually get made, and lack the institutional knowledge that experienced employees accumulate over years. He explains why building an organizational “ontology” could help close that gap and what Databricks has learned from doing it internally.

They also debate the current conversation around pacing frontier AI, what would constitute meaningful recursive self-improvement, and why Ali distinguishes speculative superintelligence risk from the much more immediate challenge of AI-powered cyberattacks. They close with how enterprises are managing exploding AI usage and costs, the shift toward multiple models and harnesses, and why agents are beginning to reshape infrastructure itself.

 

Resources:

Follow Ali Ghodsi on X: https://x.com/alighodsi

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The CFTC just gave every wallet and DeFi interface the same legal shield it gave to Phantom.

The CFTC just gave every wallet and DeFi interface the same legal shield it gave to Phantom.

The popular privacy chain is leveling up next month with faster blocks and beyond.

Vitalik says AI’s math breakthroughs could make formal verification practical, helping developers build software that is harder to hack.

Seven Senate Democrats say they remain committed to CLARITY as lawmakers explore restarting bipartisan talks before year-end.

S&P Global is acquiring OpenZeppelin, adding smart contract security to its growing institutional crypto infrastructure stack.

The SEC's new Innovation Exemption lets permissioned AMMs trade tokenized, rights-bearing U.S. stocks for the first time.

a16z General Partner Jennifer Li sits down with fal co-founder Gorkem Yurtseven and Head of Engineering Batuhan Taskaya to discuss what changes when generative video becomes fast enough to run in real time.

They unpack the technical work behind H3 Max, fal’s post-trained version of MiniMax’s open-weight video model, and how combining model post-training with systems and hardware optimization significantly reduced generation time while maintaining quality. That speed has enabled experiments with continuous video, including streams that can remember previous scenes and respond to new directions while they’re running.

They also discuss why the next challenge may be less about speed and more about control, from camera movement and lighting to characters, motion, and lip sync. And they explore what those capabilities could mean for professional creative workflows, where artists and studios need predictable tools rather than simply generating a video from a prompt.

Resources:

Follow Gorkem Yurtseven on X: https://x.com/gorkem

Follow Batuhan Taskaya on X: https://x.com/isidentical

Learn more about fal: https://fal.ai

Follow Jennifer Li on X: https://x.com/JenniferHli

 

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USDC issuer Circle just launched its own chain, arriving to an arena already fielded by Tether and Stripe.

The USDC issuer just launched its own Layer 1, arriving to an arena already fielded by Tether and Stripe.

The Ethereum gacha platform has activated purchases on its V2 protocol, which will run alongside the V1.

Venice, the rising private AI platform, has seen its token usage more than double since June.

a16z’s Alex Rampell and Joe Schmidt sit down with Lightfield co-founder and CEO Keith Peiris to discuss what it takes to rethink the CRM for an AI-native world, and the unusual pivot that got him there.

Keith previously built Tome to 25 million users, but eventually walked away from the product after concluding that the underlying technology couldn’t capture enough context about a presenter, their audience, and the relationship between them. Starting again, his team followed customers from AI presentations into sales workflows and eventually found a harder problem: making sense of the fragmented and often conflicting data spread across a company’s emails, calls, CRM, and other systems.

They unpack Lightfield’s idea of a “business world model,” why Keith believes intelligence can replace much of the rigid schema behind traditional software, and what changes when AI has enough context to reason about a company and its customers. They also get into building for greenfield versus brownfield markets, AI-era pricing, running a company where everyone is a generalist, and Keith’s lessons from making a hard pivot.

Resources:

Follow Keith Peiris on LinkedIn: https://www.linkedin.com/in/keithpeiris

Follow Alex Rampell on X: https://x.com/arampell

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Learn more about Lightfield: https://lightfield.app

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CLARITY's latest Senate push failed after an ethics deal revived hopes, leaving crypto's path to lasting U.S. rules unclear.

Elena Burger sits down with academic and cyber ethnographer Ruby Justice Thelot to explore the increasingly blurry line between internet culture and the real world, and how to tell the difference between a trend that’s actually changing behavior and one that simply feels enormous online.

They use today’s wellness and optimization culture as a case study, from peptides and GLP-1s to protein maxxing, wearables, microplastics, and the quantified self. Ruby explains her concept of “paracontent,” where the conversation around a phenomenon can become much larger than the phenomenon itself, and what social media data can tell us about how these trends move from niche communities into the mainstream.

They also trace the much longer history of body optimization, from changing ideals of thinness to the rise of the quantified self, and ask what comes next as technology gives people increasingly granular ways to measure and modify themselves. Ruby’s prediction: rather than everyone optimizing toward the same ideal, we may see increasingly individualized and sometimes extreme forms of “body futurism.”

Resources:

Follow Ruby Justice Thelot on X: https://x.com/being_on_line

Follow Elena Burger on X: https://x.com/VirtualElena

Read Ruby’s piece “Enshittification” Isn’t Real: https://www.a16z.news/p/enshittification-isnt-real

 

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Panther is now live on Base, marking Panther’s first multichain deployment and extending programmable privacy beyond Polygon and into the Base ecosystem. Users can now interact confidentially with supported assets on Base through Panther’s privacy-preserving infrastructure.  

The dApp is available at: https://pantherdao.app/

Why Base

Base is a fast-growing on-chain ecosystem of users, builders, and applications supporting the next generation of internet infrastructure. With low fees, fast execution, and a rapidly expanding DeFi ecosystem, Base provides a strong foundation for privacy-preserving infrastructure.

We believe privacy is an important missing component for on-chain applications and users. Panther is designed to support confidential on-chain interaction while remaining connected to broader DeFi infrastructure.

Following Panther’s recent Mainnet launch on Polygon, the Base deployment marks the next step in Panther DAO’s multichain approach for Panther Protocol infrastructure.

Like Panther DAO’s Polygon deployment, the Base infrastructure connects Panther to established decentralized liquidity protocols such as Uniswap, enabling confidential interaction with DeFi liquidity through the Panther interface. For users, this means confidential interaction with supported DeFi assets on Base while retaining self-custody and control. 

Panther DAO’s Base deployment includes the same cryptographic, economic, and credential-verification parameters currently live on Polygon, as outlined in DAO proposal PIP-30.

Deployment Details and Supported Assets

Now that Panther is live on Base, users can privately interact with the following assets:

ZKP cbBTC ETH USDC AERO ZORA VIRTUAL MORPHO AAVE

Additional assets may be supported in the future through Panther DAO governance.

The Base contract address for the $ZKP token is:

0x0a776c1c22b8b8e7eab346744daa33722b80fda4

ZKP holders can bridge tokens to Base and participate in upcoming Panther Improvement Proposal (PIP) votes across Ethereum, Polygon, and Base.

Current daily protocol limits, as approved through PIP-27, are:

• Deposit limit: $25,000• Withdrawal limit: $100,000

What’s Next

Now that Panther has brought privacy to Polygon and Base, Panther DAO is continuing work to launch Panther Protocol on Ethereum and continue exploring privacy infrastructure for the Kaspa ecosystem together with Igra. Panther Protocol is open source, while the Panther Protocol Foundation supports ecosystem development, administers grants, and owns and licenses the proprietary Panther dApp.

About Panther Protocol Foundation

Panther Protocol Foundation is a non-profit supporting the ecosystem through research funding, open-source development grants, and ecosystem initiatives. It does not operate the protocol, host interfaces, custody assets, execute or intermediate transactions, or provide financial services.

The Panther dApp is a non-custodial interface -users interact directly with smart contracts from their own wallets, signing all transactions themselves. Compliance credentials are issued and managed by independent third-party providers.

Please review the applicable notices, disclosures, and jurisdictional restrictions available through the Panther interface before interacting with the protocol.

For more information, visit www.panther.org
To learn more about Panther Protocol, visit www.pantherprotocol.io

Contact
Panther Protocol Foundation
📧 Email: general@panther.org
🌐 Website: www.panther.org

The Standard Reserve turns bank charters into soulbound NFTs and monetary policy into code.

Ben Horowitz and Erik Torenberg sit down with OpenAI co-founder and President Greg Brockman to discuss why he believes AI has entered a new phase, what OpenAI’s latest models reveal about the path to AGI, and the safety and security challenges that come with increasingly capable systems.

Greg explains why computer use represents such an important step for agents, including models that can work coherently for 24 hours and interact with software through the same interfaces humans use. He also shares how OpenAI deployed 10,000 agents to tackle the Navier-Stokes problem, and why advances in mathematical reasoning could translate into new approaches to science, software, and cybersecurity.

Ben, Erik, and Greg also dig into the “defender’s window” for cybersecurity, how AI could reshape work and entrepreneurship, and what the AI assistant of the future might actually look like: persistent, proactive, personalized, and capable of doing work on your behalf rather than waiting for another prompt.

Resources:

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Follow Ben Horowitz on X: https://x.com/bhorowitz
 

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World Labs co-founder Justin Johnson joins MTS hosts Theo Jaffee and Sofia Puccini to discuss Atlas, World Labs’ latest world model, and the broader case for AI systems that understand and interact with the physical world.

Justin explains how Atlas approaches three core tasks: generating new worlds, reconstructing real environments from images, and simulating how objects or robots might behave within them. Underlying it is a bigger thesis: just as language models became general-purpose engines for working with text, world models could become a horizontal layer for visual and physical intelligence across industries from entertainment and gaming to construction and robotics.

They also explore how world models could change video games and creative tools, why precise spatial control matters, and the potential for “real-to-sim-to-real” robotics, where a few photos of a physical environment could eventually be enough to build a simulation and adapt a robot to that specific space.

Resources:

Follow Justin Johnson on X: https://x.com/jcjohnss

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Follow Sofia on X: https://x.com/schisofrenia

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a16z General Partner Anish Acharya joins Lenny Rachitsky on Lenny’s Podcast to discuss why fears of an AI-driven “permanent underclass” may be misplaced, how AI is changing the way companies operate, and why the opportunity may be less about replacing people and more about dramatically expanding what they can build.

Anish lays out his idea that companies are becoming a series of loops, with agents increasingly handling workflows across engineering, sales, marketing, support, and other functions while humans provide the judgment and new ideas needed to move beyond local maxima.

They also explore why Anish thinks consumer AI should focus less on productivity and more on helping people live richer lives, why moats are often discovered rather than designed, how to develop intuition for different AI models, and why his biggest advice for anyone trying to keep up with AI is simple: make more things.

Resources:

Follow Anish Acharya on X: https://x.com/illscience

Follow Lenny Rachitsky on X: https://x.com/lennysan

Read/listen to the original episode on Lenny’s Newsletter:
Why companies are becoming a series of loops | Anish Acharya (a16z)

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Spotlighting up-and-coming tokens with interesting potential on Robinhood's L2.

Highlighting a handful of Robinhood Chain tokens on our radar right now.

The Clarity Act just got a fresh draft ahead of its September 15th cloture vote.

ETH jumped as high as 7% today, outpacing other crypto majors amid Friday's mixed inflation data.

a16z’s Matt Perault sits down with General Partner and Speedrun lead Andrew Chen on the a16z AI Policy Brief to explore what “Little Tech” actually looks like at the earliest stages, and why the realities of building a two- or three-person startup are often missing from policy debates.

Andrew takes us inside Speedrun, where founders are often starting companies from kitchen tables, working with tiny teams, and trying to determine in a matter of months whether their idea can become a viable business. He explains why these founders rarely have the time or resources to engage with policymakers, even as regulation can have an outsized impact on whether and where they build.

Matt and Andrew also discuss how regulatory burdens accumulate for young companies, why startups can choose where to put down roots, the role of ecosystems like Tech Week, and what policymakers can do to hear directly from the founders who may otherwise be absent from the conversation.

This episode originally appeared on the a16z AI Policy Brief.

 

Resources:

Follow Andrew Chen on X: https://x.com/andrewchen

Follow Matt Perault on X: https://x.com/MattPerault

Learn more about a16z Speedrun: https://speedrun.a16z.com

Listen to more from the a16z AI Policy Brief: https://a16zpolicy.substack.com/
 

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Still in private beta, Variational is already moving billions via its RFQ model.

Pump.fun launches Custom Pairs, letting creators launch tokens against stocks, crypto, metals, and more while earning fees in the paired asset.

trade[XYZ] launches Events on Hyperliquid via HIP-4, bringing outcome markets for finance, sports, politics, and more into one unified account.

First it was your license plate. Now it’s what you spend.

Kyle Olson was driving across Montana when the lights came on behind him.

The trooper’s reason was almost aggressively mundane: an obstructed license plate. Olson pulled over, the stop played out the way thousands of traffic stops play out, and it ended with a DUI charge. If that were the whole story, it wouldn’t be worth writing about. Obstructed plates get people pulled over every day, and sometimes those stops turn up something else entirely. Nothing about that part is unusual.

Here’s the part that is. Months later, during discovery in his case, Olson’s lawyers were handed a document they were never supposed to see outside a courtroom. It was written by a Border Patrol agent named Matthew Phelps, and it explained the real reason for the stop, the reason nobody told him at the side of the road. Phelps was assigned to something called the Predictive Intelligence Targeting Team, PITT for short, a unit whose existence 404 Media would go on to reveal for the first time in its reporting. Phelps’s job, according to his own document, involved reviewing “law enforcement-sensitive databases,” including financial activity, to build intelligence before handing names to local police. In Olson’s case, that intelligence was financial activity patterns Phelps described as “commonly associated with illicit narcotics activity.” That flag went to Montana Highway Patrol. The obstructed plate was the excuse they used once they’d already decided to stop him.

Notice the order of operations here, because it’s the whole story. Not: stop happens, evidence emerges, investigation follows. Instead: financial data gets reviewed, a decision gets made, and then a reason gets manufactured after the fact to make the stop look like it started with something a trooper could see with his own eyes. When 404 Media asked Customs and Border Protection what financial data it monitors, and whether anything resembling a warrant was involved anywhere in this process, the agency’s answer was to decline to answer, citing “operational security.”

Where you’ve seen this shape before

If this feels oddly familiar, it should. Another piece published here a short while back was about a different kind of watching: Flock Safety’s network of roughly 120,000 license plate cameras, installed under contract with more than 5,000 police departments, originally sold as a tool for finding stolen cars. It didn’t stay a tool for finding stolen cars. It became something people got angry enough about to take saws to, after a detective was caught using it to stalk his ex-partner, after it turned up connected to immigration sweeps that had nothing to do with the crimes it was funded to catch.

PITT is the financial version of the same idea, except there’s no camera on a pole for anyone to see, no obvious physical object to point at, and no way to know it happened to you unless a defense attorney gets lucky in discovery. Olson found out. Most people in his position never will.

And there’s a third front, in case two didn’t feel like enough of a pattern yet. The European Union’s Chat Control regime, which allows scanning of private messages without individual suspicion, was voted down by more members of the European Parliament than voted for it this July, 314 to 276. It passed anyway, because the threshold required to actually kill it was set higher than a simple majority. Suspicionless message scanning is legal in the EU until at least 2028, over the objection of the people who were supposed to have a say in it.

Cameras log where you drive. A scanning mandate reads what you write. PITT reviews what you spend. Three different governments, or in the EU’s case, one government body overruling its own elected majority, three different agencies, three different origin stories, arriving at the same place from three different directions.

Nobody designed this as one system. That’s actually the part worth taking seriously rather than the part to wave off. If it were one coordinated plan, you could point at the architect and stop them. What’s actually happening is scarier in a quieter way: wherever it becomes technically cheap to monitor some part of ordinary life, something eventually gets built to monitor it, under whatever justification happens to be available that year, and once it’s built, it tends to keep running long after anyone stops asking why. Nobody has to conspire for that to happen. It just requires the capability to exist and no one with the power to say no.

“I already use crypto” isn’t the escape hatch you hoped it to be

If you’ve read this far and you’re thinking your money already sits somewhere PITT can’t reach it because it’s in Bitcoin or Ethereum, it’s worth walking through why that instinct, reasonable as it is, doesn’t hold up the way you’d want it to.

A separate piece here traced what’s happened to Zcash this year, a project whose zk-SNARK cryptography is genuinely excellent, genuinely foundational to the entire field of privacy-preserving crypto. And yet: Zcash now has a spot ETF trading on NYSE Arca. There’s a Nasdaq-listed company, literally named Cypherpunk Technologies, built specifically to accumulate ZEC as a corporate balance-sheet asset, the same playbook Michael Saylor built at MicroStrategy for Bitcoin. Zcash’s own founder now sits on that company’s roster as a strategic advisor.

None of that touches Zcash’s cryptography. The math is exactly as sound as it ever was. What changed is everything wrapped around the math, the exchanges, the custodians, the fund structures, all the infrastructure that makes an asset legible enough for Wall Street to hold it. And legibility is precisely what a program like PITT needs to work. It doesn’t need to break a zero-knowledge proof if the custodian holding your shares, or the exchange that processed your on-ramp, already keeps the records a subpoena asks for. The wrapper is the part that gets reached, not the cryptography inside it, and the more institutionally wrapped an asset becomes, the more wrapper there is to reach.

So “I hold crypto” isn’t the same claim as “I hold something with nothing to hand over.” Those are two different properties, and it’s worth knowing which one you actually have.

What it would take to actually sit outside this

Go back to Olson’s story for a second, and imagine the version where the financial activity Phelps reviewed simply didn’t exist as a reviewable record in the first place. Not better encrypted. Not harder to access. Not created at all.

That’s the actual design target, and it’s worth walking through what that looks like in practice rather than treating it as a slogan.

Start with the ledger itself. PIVX’s shielded transactions, live since 2021, don’t produce a transaction record sitting in some database waiting for the right subpoena. There’s no ledger entry to request in the first place, no pattern for an agent reviewing “financial activity” to flag as suspicious, because nothing was generated to review.

Then there’s the part of financial life that isn’t the ledger at all, the conversations around money, arranging a payment, coordinating with someone, the ordinary human communication that surrounds every transaction. Vector, an open-source, end-to-end encrypted messenger built by PIVX Labs, runs on the decentralized Nostr relay network instead of a company’s central server, no email, no phone number, nothing to create an account with beyond a key you generate yourself. It’s genuinely early still, the developer’s been upfront that things like discovering other users are rough around the edges, and it doesn’t have the polish of the apps most people use every day. But it’s real, it ships regular updates, and it exists for exactly the reason this piece just spent several paragraphs building toward: a conversation that never passes through a central server has nothing sitting there for a future Chat Control-style mandate to scan, no matter what that mandate eventually requires of the platforms that do have a server to serve it.

And then there’s the part where the money actually leaves your hands and becomes something in the world, a purchase. PIVCards, live since 2023, converts PIV directly into gift cards for major retailers, no account, no email, and the option to pay from a shielded address straight through to a shielded destination. That’s Olson’s situation, inverted. A purchase that never generated a financial activity record in the first place, because none was created for anyone, present or future, to go looking for.

Back to the side of the road

None of this is a promise that anyone becomes untouchable. That’s not how any of this works, and a piece that claimed otherwise wouldn’t be worth your time.

What it is: a description of the actual difference between a system that locks its records more carefully and a system that never produces the records at all. Flock’s cameras got noticed because a camera is a thing you can see and, eventually, saw down. PITT doesn’t have that problem, because there’s nothing physical to point at, only a decision made somewhere behind a database wall, revealed to Kyle Olson by pure legal chance, and never revealed to almost anyone else it’s happened to.

The choice about what to do with that isn’t really PIVX’s to make for you. It’s whether the systems you already touch every day, your bank, your exchange, your messaging app, generate a record that something like PITT could someday review, or whether they were built, from the start, not to generate one at all. That’s a decision worth making with a clear head. Olson didn’t get to make it before the lights came on behind him. You still can.

Your Bank Account Is the New Probable Cause was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

a16z’s Jen Kha and David George sit down with Accolade Partners’ Aram Verdiyan to discuss how AI is changing the power law of technology investing, why the largest companies can compound advantages in ways that weren’t possible before, and what that means for how investors construct portfolios.

They explore why AI may be much bigger than traditional software, with applications reaching into labor, healthcare, transportation, services, and other major parts of the economy. David explains why capital itself can now reinforce an AI company’s advantage by buying more compute, while Aram makes the case that AI should increasingly be treated as a core allocation rather than a satellite position.

The conversation also gets into the changing economics of venture and growth investing, how to distinguish real AI traction from early hype, what AI means for legacy software and private equity, and why some of the largest opportunities may still be ahead in robotics, autonomy, healthcare, energy, and physical infrastructure.

Resources:

Follow Aram Verdiyan on X: https://x.com/aramverdi

Follow Jen Kha on X: https://x.com/jkhamehl

Follow David George on X: https://x.com/DavidGeorge83

 

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Why Venice and onchain inference markets may benefit from growing distrust around frontier AI labs.

A suspicious OpenAI encounter highlights growing distrust around AI data, and why Venice and onchain inference markets may benefit.

A new mempool design could make quantum-safe signatures and private transactions dirt cheap on Ethereum.

Aave's new Hub-and-Spoke architecture is closing in on $1B in deposits.

MetaMask goes independent as Consensys is splitting into two companies.

Ten years after The DAO hack changed Ethereum forever, Griff Green returns to Epicenter to discuss the next chapter: the DAO Security Fund.

As a co-initiator of The DAO, Griff shares the untold story of recovering funds after the hack, why over 75,000 ETH remained untouched for years, and how its staking yield is now funding public goods for Ethereum security. The conversation also explores a provocative idea: Ethereum is incredibly secure—but still not safe for everyday users.

Topics covered:

1. The inside story of The DAO and its recovery

2. Why the DAO hack may be the only hack where everyone made money

3. The DAO Security Fund and funding Ethereum security

4. Quadratic funding, grants & public goods

5. Why phishing and UX remain Ethereum's biggest weakness

6. Can Ethereum become safer than traditional banks?

7. The future of safer wallets, OpSec, and the Ethereum Economic Zone

If you enjoyed the episode, don't forget to subscribe for more conversations with the builders, founders and investors shaping the future of crypto.

Links:

Lido: https://lido.fi/stvaults?mtm_campaign=epicenter

Sponsors:

Lido V3 introduces stVaults: a modular staking infrastructure that lets builders and institutions deploy custom staking vaults, while staying anchored to stETH as a shared liquidity layer.

Get started building with Lido V3 today: https://lido.fi/stvaults?mtm_campaign=epicenter

Block Space Forum: https://blockspace.forum/

NEAR AI Cloud now lets developers deploy OpenClaw—the rapidly growing open-source AI agent platform—inside Trusted Execution Environments, providing hardware-level encryption with cryptographic attestations. With OpenClaw on NEAR AI Cloud, you can run agents with cloud convenience, but without traditional cloud data exposure. No hardware to manage. No trust assumptions required. Learn more at near.ai.

a16z’s Erik Torenberg, Ben Horowitz, and Jennifer Li sit down with Vals founder and CEO Rayan Krishnan to discuss one of AI’s increasingly difficult problems: how do you actually measure whether a model is getting better?

As public benchmarks saturate and models get better at optimizing for the tests themselves, Rayan makes the case for independent, continuously evolving evaluations. They unpack why self-reported model scores can be misleading, how VALS evaluates models in the hours before a release, and why measuring increasingly agentic systems means testing work that can unfold over hours, days, or even weeks.

They also explore why evals are becoming critical for enterprises trying to understand the ROI of AI, what happens if token spend begins to rival employee salaries, and how evaluations could eventually provide a shared language for everything from model routing and recursive self-improvement to AI policy and international coordination.

Resources:

Follow Rayan Krishnan on X: https://x.com/RayanKrishnan

Follow Ben Horowitz on X: https://x.com/bhorowitz

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The things that need to happen for ETH's market cap to reach trillions are, indeed, happening.

Visa is bringing onchain credit into card settlement as stablecoin-linked programs scale and settlement volume tops a $20B annualized run rate.

Robinhood will add OG.com prediction markets and take minority stakes in both OG and Crypto.com as it expands its event-contract business.

Hunter Biden’s $LAPTOP launches on Base Sept. 9 with Trump-loss airdrops, prediction-linked burns, and immediate online backlash.

a16z Infra Partner Lisha Li sits down with OpenAI mathematicians Mehtaab Sawhney and Mark Sellke to discuss how quickly AI’s mathematical capabilities are advancing, what recent results reveal about model reasoning, and what happens when AI begins making progress on problems mathematicians have struggled with for decades.

Mehtaab and Mark unpack several recent results from OpenAI’s models, including advances in sphere packing and the construction of a non-sofic group. They explain why the surprising part isn’t simply that models can search more possibilities or work longer than humans: in many cases, the reasoning traces look remarkably similar to the work of an expert mathematician, including choosing promising approaches, backtracking when they fail, and combining ideas from across the literature.

They also explore what this means for mathematics itself: how the role of human taste and judgment may change, whether AI could produce far more mathematics than humans can absorb, and why models that accelerate discovery may also make sophisticated results easier to understand.

Resources:

Follow Lisha Li on X: https://x.com/lishali88

Follow Mehtaab Sawhney on X: https://x.com/mehtaab_sawhney

Follow Mark Sellke on X: https://x.com/MarkSellke

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MTS host Sophia Dew visits the Open Source AI Summit in San Francisco to ask researchers and founders across the AI stack a central question: can open source prevent AI power from concentrating in the hands of a few companies?

Lukasz Kaiser, co-author of Attention Is All You Need, argues that today’s concentration may be a feature of the current technological paradigm rather than a permanent feature of AI. Transformers reward enormous amounts of data and compute, but future breakthroughs could make smaller, more specialized models far more capable.

Across conversations with researchers and builders working on open models, infrastructure, and applications, Sophia explores why China has taken the lead in open-weight models, whether the U.S. needs more open-model startups, what it means for companies to own their own intelligence, and where openness alone falls short, particularly when access to compute remains concentrated.

 

Resources:

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a16z General Partner Julie Yoo joins MTS host Sophia Dew to explain why she believes healthcare could benefit more from AI than almost any other industry, and why decades of slow technology adoption may actually give healthcare an advantage in the AI era.

Julie traces healthcare’s evolution from paper records and fax machines through electronic health records and telehealth, and explains why AI represents something different: an organic adoption wave driven by tools that doctors and patients actually want to use. Because healthcare never built the same layers of legacy software as other industries, it may now be able to leapfrog directly into agentic AI.

They also explore how AI could dramatically lower the cost of care, why consumers are becoming a more important payer, where Julie sees the biggest opportunities for healthcare founders, and a future where everyone has a highly personalized AI doctor in their pocket for life.

Resources:

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The Verus View is a monthly recap of everything that happened in the Verus ecosystem. Development, projects, community, and everything in between. Verus Core and Verus Desktop

Verus published critical security-hardening updates in August. Use the current official Verus Core release and Verus Desktop release when installing or upgrading.

The August work tightened consensus validation across PBaaS, smart transactions, DeFi, cross-chain operations, serialization, block construction and Ethereum boundary interfaces. It also addressed denial-of-service issues capable of disrupting or crashing nodes. Node operators, validators, exchanges, witnesses and infrastructure providers are urged to upgrade.

Verus Mobile

A late-August Verus Mobile release added gift cards that can contain currencies, VerusIDs or both, making it easier to onboard users. They can be password-protected and shared by QR code, link or NFC. VerusPay V4 introduced smaller invoices inside GenericRequest envelopes and support for burn invoices.

Experimental requests now cover selected user data, signed data packets and user-approved identity updates. The release also strengthened validation and added encrypted GenericResponses delivered to HTTPS endpoints.

How to install:

Android: Navigate to this page on your Android device, download and install the APK. You may need to enable apps from outside sources. iOS: Join the Verus Mobile TestFlight. Latest information regarding the Verus-Ethereum Bridge exploit

An extensive writeup covering everything from the actual exploit, to what many core contributors are working on, support we are getting and how you can help.

👉 Read it here (Google Docs)

Verus Galactic: a native Apple Silicon wallet

Verus Galactic 0.9 Alpha is a brand-new native wallet for Apple Silicon Macs. Written in Swift with AppKit and SwiftUI, it runs Verus Core locally and avoids the Electron and Chromium stack used by many cross-platform desktop applications.

The first public alpha supports mainnet and testnet, wallet creation and loading, sending and receiving, conversions, VerusID, CPU mining, staking, backups and chain-data repair.

The release tag is signed and GitHub verified. The DMG is not signed with an Apple Developer ID or notarized by Apple, so macOS may require you to Control-click the app and choose Open. Apple Silicon and macOS 13 or newer are required.

Verus Galactic wallet application ChainVue: a Verus developer stack

ChainVue’s developer tools provide reusable building blocks for apps that interact with Verus, from reading blockchain data to signing transactions.

verus-rpc connects apps to a Verus node while keeping currency amounts precise. verus-sdk handles local transaction signing, and verus-sapling extends this to private, shielded transactions, currently documented as testnet-proven. For developers running their own infrastructure, verus-docker packages Verus and PBaaS nodes for deployment.

ChainVue also released a testnet faucet miner and mempool visualizer.

ChainVue mempool visualizer Build With Dreams: games, currencies and planning tools

Verus Trading is building a market-sequence game on VRSCTEST, with DreamPunk used as a native utility currency. DreamTree is another testnet application from the same builder.

Supporting tools include an ID Treasury Model for simulating identity-funded treasuries and an Emission Model Planner for comparing PBaaS issuance choices.

Public Blockchains as a Service (PBaaS) Emission Model Planner New miners

Walled Garden Hasher is a GPL-3.0 VerusHash miner written for Apple Silicon, with a terminal interface and no developer fee.

Primo ARM Miner shipped in July for Android devices and ARM single-board computers. It retains common ccminer configuration while using a native ARM codebase.

Verus Recover tool

Verus Recover helps recover light-wallet .pin files from candidate passwords and verifies recovered data against expected addresses. Because it can reveal private keys, it should be run offline on copies of wallet files.

Get your project mentioned!

The best way is to create a post in the verus-builders section of the Verus Discord. It’s going to need links to either a website or GitHub.

This edition focuses on August updates; older projects will appear when there’s something new to share.

Note

We are still in the middle of the exploit aftermath; low liquidity and low prices. It hurts us all, but especially those who lost considerable amounts. And, while certainly understandable, it’s easy to fall into negativity and depression… been there, done that. But at the end of the day there is really only one way, and that is the way forward (I’m sorry for the cliché but it’s true). There’s just still way too much opportunity ahead.

For me, life is simple: just gotta keep building. Right now that means, among other things, working on completely redesigning Verus Mobile to be on par with the best mobile wallets around (it’s actually one hell of a feature-packed wallet, so it’s taking more time than anticipated). When that is completed my focus can go more to other consumer-facing products.

We’re gonna get out of this rut. There are builders in this community creating apps for what they think is the way to get usage and users to this ecosystem. And that’s all we really need (the builders and the actual users). Perhaps easier said than done, but I do believe that the future is still very much in our own hands.

Max

👀

August 2026 — The Verus View was originally published in Verus Coin on Medium, where people are continuing the conversation by highlighting and responding to this story.

Box co-founder and CEO Aaron Levie joins MTS hosts Theo Jaffee and Sofia Puccini to make the case for open-weight AI, unpack the economics of open versus closed models, and explain why he believes more openness could strengthen rather than undermine the U.S. AI ecosystem.

Aaron argues that open models create more use cases, push closed labs to innovate faster, and don't fundamentally change where the economics of AI ultimately accrue. They debate model distillation, America's competition with China, why restricting access may simply accelerate competing AI ecosystems, and whether U.S. labs should begin releasing open-weight versions of previous-generation models.

They also get into what the latest frontier models mean for knowledge work, how AI has changed software engineering at Box, and why Aaron believes companies cutting engineers may simply not be ambitious enough. Finally, they discuss why enterprises are unlikely to bet on a single model and why the layer that routes between models, data, and workflows could become increasingly valuable.

 

Resources:

Follow Aaron Levie on X: https://x.com/levie

Follow Theo Jaffee on X: https://x.com/theojaffee

Follow Sofia Puccini on X: https://x.com/schisofrenia

Follow MTS on X: https://x.com/mtslive
 

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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

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AMC’s fight with Robinhood Stock Tokens sent CINEMA soaring alongside the actual AMC stock.

AMC’s fight with Robinhood Stock Tokens sent CINEMA soaring, alongside the actual AMC stock, showing how tokenized stocks can be guerrilla marketing machines for public companies.

The PIVX ecosystem continues to make steady progress across network participation, market activity, liquidity, wallet accessibility, and community development. This week brings several updates highlighting the continued growth of the PIVX ecosystem and its focus on privacy and financial freedom.
‎
‎Masternode Network
‎
‎The PIVX masternode network currently stands at approximately 2,061 masternodes, with an estimated annual reward of 15.31% and around 19.43% of the total PIVX supply locked.
‎
‎Masternodes remain an important part of the PIVX Proof-of-Stake ecosystem, supporting network stability, decentralized governance, and continued participation across the network.
‎
‎Market Performance
‎
‎PIVX is currently trading around $0.0157, with market activity continuing to fluctuate alongside broader cryptocurrency market conditions.
‎
‎24-hour trading volume is approximately $349,000, reflecting ongoing activity from traders and holders as market liquidity continues to develop.
‎
‎Growing PIVX Liquidity
‎
‎Liquidity remains an important part of building a stronger and more accessible market for PIVX.
‎
‎@coinexcom is currently calling on the PIVX community to contribute liquidity to the PIVX/USDT AMM pool. Participants can provide equal values of PIVX and USDT, with a minimum contribution of $200, while earning a share of eligible trading fees.
‎
‎Greater liquidity can help support a healthier trading environment and provide additional opportunities for the PIVX community to participate in the ecosystem.
‎
‎Privacy & Accessibility
‎
‎Privacy remains at the heart of PIVX.
‎
‎The network gives users the ability to choose how much of their financial activity they want to reveal, including access to private transactions when needed.
‎
‎PIVX is also available through NOW Wallet, providing users with another convenient option for managing their PIVX holdings.
‎
‎The principle is simple: your money should remain under your control, and financial privacy should remain a choice.
‎
‎Development & Community
‎
‎PIVX development continues alongside the growth of the wider ecosystem.
‎
‎LukeL has officially been added to the PIVX Team Page, recognizing his long-standing contributions to the project. His work spans initiatives including wallet-kit and PIVCards, among other contributions to the PIVX ecosystem.
‎
‎You can meet the people contributing to PIVX at pivx.org/team.
‎
‎Community participation remains equally important. Through PIVX.org, Discord, and Telegram, users can follow development, discuss privacy, share ideas, and participate in conversations shaping the future of the ecosystem.
‎
‎Looking Ahead
‎
‎With continued network participation, new liquidity opportunities, broader wallet accessibility, and ongoing development, PIVX remains focused on building a more private and user-controlled financial ecosystem.
‎
‎The journey continues with privacy, decentralization, accessibility, and individual choice at its core.
‎
‎PIVX. Your Rights. Your Privacy. Your Choice.
‎
‎To stay on top of PIVX news please visit PIVX.org and Discord.PIVX.org.

PIVX Weekly Ecosystem Update: Strengthening Privacy, Liquidity & Accessibility was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

World Labs co-founders Fei-Fei Li, Justin Johnson, and Ben Mildenhall join a16z General Partner Martin Casado to discuss Atlas, their latest world model, and what it reveals about the pursuit of spatial intelligence.

At the center of Atlas is what the team calls “new view prediction”: given images or views of a scene, the model predicts what that environment should look like from a different position in space and time. This brings generation and 3D reconstruction into the same model, and raises a broader question about whether predicting views could become a useful primitive for understanding the physical world.

They discuss the technical bets behind the model, what it can and can’t yet capture, and the importance of dynamics, editability, and simulation as world models develop. The conversation also explores applications in creative work, architecture, and robotics, where Fei-Fei argues that one of today’s biggest constraints is access to real-world training data.

 

Resources:

Follow Fei-Fei Li on X: https://x.com/drfeifei

Follow Justin Johnson on X: https://x.com/jcjohnss

Follow Ben Mildenhall on X: https://x.com/BenMildenhall

Follow Martin Casado on X: https://x.com/martin_casado

Learn more about Atlas: https://www.worldlabs.ai/blog/atlas

 

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Why cornering a tokenized stock's supply doesn't corner the real stock!

Why cornering a tokenized stock's supply doesn't corner the real stock.

Rollups pushed Ethereum blob usage to an ATH this week, with demand the highest its ever been.

BTC reached $80k again after Fed Governor Waller said he may support holding rates at the next FOMC meeting.

Pons just hit new all-time highs in trading volume and tokens created on Robinhood Chain.

Erik Torenberg is joined by a16z General Partner Alex Rampell and Affirm Co-Founder and CEO Max Levchin for a conversation on 25 years of fintech, from the early days of digital payments to the origins of Affirm and the next generation of agentic commerce.

Max and Alex revisit what surprised them most about how payments evolved, why the card interface has been so difficult to displace, and why even the smallest corners of payments can become enormous markets. They also trace the early idea maze behind Affirm, from "pay with your identity" and the pajama problem to the realization that installment financing could dramatically increase merchant conversion.

The conversation also gets into real versus "fake" 0% financing, what people misunderstand about Affirm today, why negative customer acquisition cost can be such a powerful business model advantage, and why Max is more bullish on agentic payments than on agents choosing what people buy.

Resources:

Follow Max Levchin on X: https://x.com/mlevchin

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Last month, more than 700 engineers and technical leads from companies like Apple, AWS, Google, NVIDIA, Microsoft, OpenAI, Salesforce, and Snowflake registered for a hackathon hosted by popular AI newsletter AlphaSignal. On August 6, 2026 more than 100 of these devs appeared in person in San Francisco to hack on a deceptively simple challenge: in 90 minutes, with no pre-built code allowed, write an AI agent that can order and deliver a pizza to 3 Embarcadero Center. First pizza delivered wins, with $2,500 in total prize money at stake.

It’s a fun premise. But underlying this novelty, the challenge is a good stress test for a much bigger question in AI development: How do you get an autonomous agent to reliably act in the real world, where the information it needs—what’s open, what’s nearby, what’s actually deliverable—isn’t in its training data and changes by the hour?

Of their own accord, two of the winners (Preston Kwei and Rohan Gandotra) leveraged the Brave Search API to solve the same underlying problem: How to ground their agent in accurate, real-time information about the outside world, when that data falls outside their training corpus. Interestingly, each winner took a different approach, which is a useful illustration of how flexible Brave Search API can be as a grounding layer.

Real-time discovery, then action

Preston used the Brave Search API as a live restaurant-discovery layer, letting his agent identify nearby pizza options in real time rather than relying on stale or hardcoded data (a task aided by Brave’s Place Search API). From there, the agent completed the actual order through the Brave browser on DoorDash, pairing real-time search with real-time action in a single pipeline.

Structured, ranked data for agent decision-making

Rohan took a more deterministic approach to the same problem: which restaurants even exist near here, and which one should the agent pick? He used the Brave Search API to pull nearby pizza spots by address, programmatically scored them by distance, and fed that ranked list back to his agent as clean, structured input. This meant no scraping and no manual parsing, just usable data ready for the agent’s decision logic.

Brave Search API is built for just this kind of challenge

Both Preston’s and Rohan’s approaches map directly onto why developers reach for the Brave Search API when building agents. An agent is only as good as the information it can act on, and static training data can’t tell you which pizza place near the Embarcadero is currently taking orders. That’s the same core problem developers face at larger scales:

Chatbots that need to ground answers in current events Research agents that need fresh market data Any AI system that needs a live, verifiable window into the Web rather than a frozen snapshot of it

Whether the goal is answering a question without hallucinating or fetching a ranked list of nearby businesses in real time, the pattern is the same: pull accurate, current, structured data from an independent Web index, and hand it to the agent in a form it can immediately use.

AlphaSignal’s hackathon is a small, playful example that points to a much larger shift already underway: AI agents are moving from answering questions to taking actions, and that shift depends entirely on giving those agents reliable, real-time access to the open Web. A hackathon built around ordering a pizza turned out to be a relevant proxy for the same challenges developers are solving in legal research, market intelligence, fraud detection, and more. It was just compressed into 90 minutes and a countdown clock.

Congratulations to Preston, Rohan, and Elliot S. for winning the night, and thanks to AlphaSignal for bringing the AI community together to find real-world utility for their agents.

Readers’ note: Several members of the Brave team, including Desktop Product Manager Rafael Ebron, Staff Engineer Anton Lazarev, and VP of Privacy & Security Shivan Sahib, attended to observe and answer technical questions, but winners were judged solely on how quickly their agent got a pizza delivered, and whether it was built live during the event. Brave’s attendance had no bearing on the outcome.

EIP-7906 would let Ethereum accounts check what a transaction actually did and, if needed, veto malicious results.

World open-sources ProveKit, letting users prove identity claims like age or nationality without exposing their personal data.

HyperStrat expands its equity facility from $1B to $2.5B, giving the HYPE treasury company more firepower to keep accumulating tokens.

a16z General Partner Jorge Conde sits down with Moderna CEO Stéphane Bancel to discuss a major milestone for mRNA technology: positive Phase 3 results from Moderna and Merck’s individualized treatment for melanoma, after more than a decade of work on personalized cancer vaccines.

Stéphane explains how the treatment works by sequencing an individual patient’s tumor and healthy cells, identifying the mutations most relevant to their cancer, and encoding up to 34 of them into an mRNA designed specifically for that patient. Rather than simply unleashing the immune system, the goal is to teach it exactly what to recognize and attack.

They also unpack the engineering challenge of manufacturing a different medicine for every patient, how Moderna has brought the process down to roughly 42 days from biopsy to treatment, and what it would take to manufacture personalized medicines at scale. Finally, Stéphane looks beyond melanoma to lung, kidney, bladder, pancreatic, and gastric cancers, as well as Moderna’s longer-term work applying mRNA to rare genetic and autoimmune diseases.

 

Resources:

Follow Stéphane Bancel on LinkedIn: https://www.linkedin.com/in/st%C3%A9phane-bancel-8185251/

Follow Jorge Conde on X: https://x.com/JorgeCondeBio

 

 

 

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This post is part of an ongoing series evaluating Brave’s performance. It describes work done by Soumyajit Chatterjee (Systems and Performance Researcher), Kleomenis Katevas (Principal Machine Learning Researcher), Artem Chaikin (Staff Security Engineer), Pete Snyder (Principal Privacy Researcher), and Hamed Haddadi (Chief Scientist, Visiting Professor).

We recently ran new benchmarks comparing Brave against the three most widely used desktop browsers: Chrome, Edge, and Firefox. We found that Brave for desktop is faster, uses less energy, consumes less CPU and memory, and transfers less data. Specifically, across all tested browsers Brave:

Uses on average 44% less CPU Uses on average 10% less energy Uses on average 28% less memory Loads pages 20% faster Transfers 26% less inbound data Transfers 39% less outbound data

These results closely resemble our 2025 tests showing that Brave for Android outperforms other mobile browsers in page-load speed, battery consumption, CPU usage, and network use. As with Android benchmarks, we attribute our wins on the desktop benchmarks to Brave’s built-in privacy and security features, namely its adblocking and tracker blocking. These eliminate unnecessary network requests and reduce processing overhead during browsing.

Testing environment: hardware and software

This desktop testing was conducted on an Apple Mac Mini with an Apple M2 chip and 8 GB of unified memory, running macOS 26.5.1 (25F80).

The following browser versions, which were the latest available at the time of testing, were used:

Browser Version Brave 1.92.139 (Chromium 150.0.7871.114, arm64) Chrome 150.0.7871.184 (arm64) Edge 150.0.4078.83 (arm64) Firefox (Playwright Gecko) 146.0.1 (64-bit)

All tests were conducted on a dedicated 50Mbps internet connection in London, UK.

Methodology Workload

We tested the 50 most popular websites as ranked by Brave Search statistics, loading each landing page. Each experiment was repeated 10 times, with the order of browsers randomized across runs. This counterbalances order effects so that no single browser systematically benefits or suffers from its position in the sequence.

For each browser, we created a clean baseline user data directory with default settings. Before every test run, we copied this baseline into a fresh, isolated temporary directory, ensuring that no cached data, cookies, or persistent state from previous runs influenced the results. We then launched the browser against this isolated profile and waited 60 seconds for background processes to stabilize before beginning measurements.

Desktop benchmarking

To evaluate browser performance on macOS, we used a locally-hosted Apple Mac Mini. Brave’s browser automation was handled using a tool developed using the Playwright framework (v1.58.2), which provides a cross-browser API for automating and instrumenting a wide range of browser behaviors in a consistent and reproducible way. These behaviors include network requests, page lifecycle events, and worker script activity.

For each browser configuration, a clean browser profile was prepared, followed by a 60-second stabilization period. The browser then visited each URL in the measurement list. Each loaded page remained open for 30 seconds before the browser window was closed, after which the next URL was loaded.

For page loading time, we measured the time from navigation start to the loadEventEnd event, using injected JavaScript via Playwright instrumentation.

Energy consumption on macOS was estimated by integrating instantaneous system power obtained from powermetrics at a 350ms sampling interval. Results are reported in milliwatt-hours (mWh).

CPU utilization was measured using process-level statistics from ps, aggregated across all browser-related processes (main, renderer, GPU, utility, etc.) to capture total CPU load attributable to the browser. Memory was measured as the resident set size (RSS) aggregated across browser processes, also via ps. Network usage was measured using Playwright’s page-scoped instrumentation, which records requests and responses attributable specifically to each loaded page (allowing us to accurately isolate per-page network activity from background browser processes), and compute aggregated transmitted/received bytes including headers and payloads.

Metrics and points of comparison

Our performance evaluation focuses on the following attributes:

Energy consumption: Total energy required to load and render each webpage (mWh) CPU utilization: Processor load during page loading and rendering Memory usage: Memory footprint associated with each page execution Page load speed: Time from navigation start to loadEventEnd and the LCP render time Network data consumed: Total inbound data (response) and outbound data (request) per browsing session Resource usage Energy

Figure 1 shows the distribution of energy consumption (mWh) per page load across the four browsers. Brave is the most energy-efficient browser tested, with an average consumption of approximately 31.1 mWh. This is 4% lower than Chrome’s average (~32.5 mWh), 12% lower than Edge’s average (~35.3 mWh), and 14% lower than Firefox’s average (~36.1 mWh). Additionally, Brave exhibits a notably tighter distribution (smaller interquartile range and shorter whiskers) compared to the others, indicating more consistent energy behavior across different websites and less variability in power draw during page loads.

The gap between Brave and two of the other baseline browsers (Edge and Firefox), is particularly striking. Both consume meaningfully more energy per page load on average, with Firefox showing the widest spread in its distribution. Such a wide spread suggests higher variability in how efficiently the browser can process different page types.

Figure 1: Box plots of energy consumption (mWh) per page load across the four tested desktop browsers. Triangles represent the mean; horizontal lines represent the median. Lower scores are better. CPU

The CPU utilization results, shown in Figure 2, tell an even more pronounced story. Brave records a mean CPU utilization of approximately 33%. This is significantly lower than Chrome’s mean (~47%), Edge’s mean (~53%), and Firefox’s mean (~78%).

Firefox’s CPU usage stands out in particular. Its mean is nearly two-and-a-half times greater than Brave’s, and in the worst observed cases it approaches 100% utilization—suggesting that for some pages, Firefox saturates one or more CPU cores entirely during loading and rendering. This is consistent with Firefox’s distinct Gecko engine architecture, which handles certain page workloads differently from the Chromium-based browsers. Brave, Chrome, and Edge all share the Chromium engine, yet Brave’s native adblocking removes a substantial portion of the page resources that would otherwise need to be fetched, parsed, and executed. Together, this filtering directly reduces the CPU work required per page load.

Figure 2: Box plots of CPU utilization (%) per page load across the four tested desktop browsers. Triangles represent the mean; horizontal lines represent the median. Lower scores are better. Memory

Figure 3 presents the memory consumption (resident set size—or RSS—in MB) per page load. Brave is the most memory-efficient browser tested, with a mean of approximately 1,200 MB. This is 31% lower than Chrome’s average (~1,750 MB), 26% lower than Edge’s average (~1,620 MB), and 27% lower than Firefox’s average (~1,650 MB).

This efficiency is a direct result of Brave’s architecture, which manages process isolation and caching differently than its competitors. While other browsers often retain more background state or rely on less optimized memory management for their default configurations, Brave’s native adblocking and tracker blocking reduces the number of resources that need to be held in memory simultaneously. Brave is actively working on further reducing memory overhead in its native blocker, so we expect this advantage to be maintained or extended in future versions.

Figure 3: Box plots of memory consumption (MB) per page load across the four tested desktop browsers. Triangles represent the mean; horizontal lines represent the median. Lower scores are better. Page load speed Load event end time

Figure 4 shows the distribution of page load times, measured from navigation start to the loadEventEnd event. Brave achieves a mean load time of approximately 4.4 seconds, compared to an average of 5.1 seconds for Chrome (16% higher than Brave), 5.3 seconds for Firefox (20% higher), and 6.0 seconds for Edge (36% higher).

Edge shows the widest interquartile range and the highest median of the four browsers, suggesting it is both slower on average and less consistent across different sites. The load time advantage for Brave is consistent with its adblocking, which eliminates a substantial number of the third-party requests (ads, trackers, and analytics scripts) that other browsers must fetch, parse, and execute before the load event can complete.

Figure 4: Box plots of page load time (s) measured at loadEventEnd, across the four tested desktop browsers. Triangles represent the mean; horizontal lines represent the median. Lower scores are better. LCP render time

Figure 5 presents Largest Contentful Paint (LCP) render times—a user-visible measure of when the main visual content becomes available. The four browsers cluster more tightly on this metric than on resource usage or load completion. Brave achieves a mean LCP of approximately 2.4 seconds, statistically indistinguishable from Chrome at the same value. Edge and Firefox trail slightly at ~2.5 seconds each.

This convergence in LCP is worth unpacking. While Brave completes the full page load significantly faster than its competitors (as shown above), the time to render the largest visible element is broadly similar across all four browsers. This suggests that the bulk of Brave’s load time advantage comes from eliminating resources that load after the primary visual content is already rendered (resources such as background trackers, analytics calls, and deferred scripts) rather than from speeding up the critical rendering path itself. For users, this means the page appears ready at roughly the same time across browsers, but Brave finishes all background work faster and with less CPU and energy expenditure.

Figure 5: Box plots of LCP render time (s) across the four tested desktop browsers. Triangles represent the mean; horizontal lines represent the median. Lower scores are better. Network data consumed

To evaluate network efficiency, we analyzed two metrics: response size (inbound data received, analogous to network Rx) and request size (outbound data transmitted, analogous to network Tx). These were captured using Playwright instrumentation, recording aggregate bytes across all browser-level requests and responses per page load.

Response size (inbound data)

Figure 6 shows the distribution of response sizes (inbound data) per page load. Brave leads with a mean of approximately 4.4 MB, outperforming the competition. Chrome averages ~4.8 MB (9% higher than Brave), Firefox averages ~6.3MB (43% higher), and Edge averages ~6.8MB (55% higher).

Edge and Firefox show notably higher inbound data usage than the two Chromium-based browsers. For Edge in particular, the interquartile range extends significantly higher, indicating that for a substantial proportion of pages, Edge fetches considerably more data than the other browsers. Brave’s lower inbound footprint is a direct consequence of its content filtering blocking ad creatives, tracking pixels, and third-party scripts before they are ever requested from the network.

Figure 6: Box plots of response size (MB) per page load across the four tested desktop browsers. Triangles represent the mean; horizontal lines represent the median. Lower scores are better. Request size (outbound data)

Figure 7 shows the distribution of outbound request sizes per page load. The gap between Brave and its competitors is the most striking of all the network metrics. At a mean of approximately 0.18 MB, Brave transmits the least data by a clear margin — 28% less than Firefox (~0.25 MB), 40% less than Edge (~0.30 MB), and 47% less than Chrome (~0.34 MB).

The outbound gap between Brave and Chrome is particularly large. Chrome transmits nearly twice as much data per page on average, reflecting the volume of tracking beacons, telemetry pings, and analytics payloads that Brave blocks before they leave the device. Reducing outbound data is of course meaningful for privacy. But, as proven here, reducing outbound data also reduces upload bandwidth consumption and the CPU overhead associated with serializing and sending those requests.

Figure 7: Box plots of request size (MB) per page load across the four tested desktop browsers. Triangles represent the mean; horizontal lines represent the median. Lower scores are better. Synthetic benchmarks

While real-world browsing metrics are our primary focus, we included results from three widely used synthetic benchmarks for completeness: Speedometer 3.1, which measures how quickly a browser executes JavaScript-based web applications; JetStream 2.2, which evaluates JavaScript and WebAssembly performance on computationally intensive tasks; and MotionMark 1.3.1, which tests graphics rendering performance at 60 frames per second.

As noted earlier, these benchmarks omit the factors that drive real-world performance differences: namely privacy protections, adblocking, and network optimization. They are also ill-suited for comparing browsers that share the same underlying engine: because Brave, Chrome, and Edge all run on Chromium, their scores on engine-focused tests naturally converge, regardless of the meaningful differences in how they behave during actual browsing.

Figure 8: Mean (standard deviation) on Synthetic benchmarks – (a) Speedometer 3.1, (b) JetStream 2.2 and (c) MotionMark 1.3.1. All scores are higher the better.

The results reflect this pattern. On JetStream 2.2 (Fig. 8b), Brave, Chrome, and Edge are statistically indistinguishable, with Firefox lower due to its different engine architecture. Speedometer 3.1 (Fig. 8a) shows a similar picture: Brave, Chrome, and Edge cluster tightly together, with Firefox trailing. MotionMark 1.3.1 (Fig. 8c) follows the same Chromium-cluster pattern for Chrome and Edge, though here Brave scores somewhat lower, likely reflecting the overhead of its additional privacy features on graphics-intensive rendering. Firefox scores substantially lower, again reflecting engine differences.

Why these four browsers?

We evaluated four browsers in this study: Brave, along with three other cross-platform browsers. We measured Chrome and Edge because of their worldwide popularity; we measured Firefox because it’s both built on a different browser engine (Gecko), and because of the prominence of privacy in the browser’s positioning and marketing.

We considered but ultimately did not include several other browsers in this comparison. Most significantly we did not include Safari (or any other WebKit-based browsers) as the measuring framework we used, Playwright, only provides access to a wrapper around the WebKit engine, which is not equivalent to measuring Safari itself. Other frameworks that can measure Safari do exist, but they do not provide the same set of features and capabilities needed by our measurement system (e.g., measure request/response size per url).

Conclusion

Across every resource metric we measured (energy, CPU, memory, page load time, and bandwidth), Brave is the most efficient desktop browser in our evaluation. The margin varies by metric, but the direction is consistent: Brave outperforms Chrome, Edge, and Firefox in real-world browsing conditions on macOS.

These advantages are a direct consequence of the privacy and performance features Brave ships by default: native ad and tracker blocking, fingerprint protection, and bounce tracking defenses that reduce the computational and network overhead of every page load. Key findings from our tests include:

CPU Efficiency: Brave uses on average 44% less CPU than the competing browsers, with Firefox showing the largest gap at 2.4× higher consumption. Memory Footprint: Brave is the most memory-efficient browser tested, using 28% less memory on average than Chrome, Edge, and Firefox. Energy Consumption: Brave consumes 10% less energy per page load than the average of competing browsers. Network Efficiency: Brave transfers 26% less inbound data and 39% less outbound data than other browsers. Page Load Speed: Brave loads pages 20% faster on average.

We plan to continue this evaluation series with a similar set of tests for iOS, and to periodically re-run tests across all platforms to ensure Brave remains the most performant major browser available.

For questions or comments about the results of this post, please contact the Brave Research team at blade-project@brave.com.

Ripe Protocol is bringing classic DeFi liquidity mining back on Robinhood Chain.

Ethena launches Ethena Pay, offering USDe yields, card rewards, global transfers, and new utility for ENA.

a16z’s Lisha Li sits down with Daniel Litt, Assistant Professor of Mathematics at the University of Toronto, to unpack AI's rapid progress in mathematics, what today's frontier models can actually do, and what they're still missing about the way mathematicians think.

Daniel explains why some recent AI-generated results are genuinely impressive, including an autonomous solution to the Erdős unit distance problem, but argues that solving problems is only one part of mathematics. Today's models can grind through calculations, combine known techniques, and search enormous spaces, but still struggle with intuition, theory building, identifying the right questions, and developing the kind of big-picture understanding that drives much of mathematical progress.

Lisha and Daniel also explore how AI is already changing mathematical research, why an explosion of AI-generated papers could distort academic incentives, and what happens if researchers outsource the work of thinking rather than use AI to deepen it. Ultimately, they ask a question that extends far beyond mathematics: as AI gets better at intellectual work, how do we make sure humans keep getting better at thinking too?

 

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In decentralized finance (DeFi), transparency is both a strength and a limitation. Every transaction on a public blockchain is permanently visible, enabling auditability and trustless verification while also exposing trading strategies, wallet relationships and financial activity. For institutions, businesses and privacy-conscious users, this lack of confidentiality remains a significant barrier to broader adoption.

Panther Protocol addresses this challenge through programmable privacy: confidential trading environments that combine zero-knowledge cryptography with configurable access controls and compliance policies. Rather than treating privacy as an all-or-nothing proposition, Panther allows operators to determine how privacy should function within their own trading environment, balancing confidentiality with regulatory or commercial requirements.

The Problem: Transparency Without Boundaries

Public blockchains record the sender, recipient, asset and amount of every transaction indefinitely. While this transparency underpins decentralized finance, it also creates practical challenges:

Front-running and Maximal Extractable Value (MEV) attacks that exploit publicly visible transactions. Wallet clustering and transaction analysis by blockchain analytics providers. Exposure of trading strategies, treasury movements and commercial relationships. Reluctance from institutions and high-net-worth individuals to transact on fully transparent networks.

Many privacy protocols attempt to solve these issues by removing visibility altogether. While effective from a technical perspective, this approach often leaves operators with little flexibility to implement their own compliance or access policies.

Panther takes a different approach. Privacy remains the default, but the rules governing participation are configurable by the operator.

The Solution: Configurable Shielded Pools

At the heart of Panther Protocol are shielded pools—confidential trading environments where users deposit supported assets and receive corresponding zAssets, confidential representations backed 1:1 by collateral held within a Panther Vault.

Within a shielded pool:

Transactions are protected using zero-knowledge proofs, preventing observers from linking deposits, transfers or withdrawals to individual users. Multiple digital assets and asset types coexist within the same pool, strengthening the overall anonymity set through diverse pool activity. Assets remain fully collateralized and can be redeemed for their underlying assets, subject to the rules governing the relevant pool or Zone. Zones give operators their own access-controlled, confidential trading environment within a shielded pool.

Panther's architecture draws inspiration from privacy-focused systems such as Zcash while being purpose-built for Ethereum Virtual Machine (EVM)-compatible blockchains and decentralized finance.

The Technical Foundation

Panther combines several cryptographic components to deliver confidential transactions.

zk-SNARKs

Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge (zk-SNARKs) allow users to prove that transactions are valid without revealing the underlying transaction data. This enables confidential transfers while maintaining cryptographic integrity.

Merkle Trees

Append-only Merkle trees maintain the private state of the protocol. Users prove ownership and spendability of their Unspent Transaction Outputs (UTXOs) using zero-knowledge proofs without revealing the UTXOs themselves.

zAssets

zAssets are confidential representations of deposited assets. Each zAsset is backed by collateral locked within a Panther Vault and can later be redeemed for the corresponding underlying asset.

zAccounts

Within Panther, users interact through zAccounts, which are represented using UTXOs rather than externally owned account (EOA) addresses. This allows users to exchange zAssets privately without revealing their wallet addresses or linking their activity to publicly visible blockchain identities.

Programmable Privacy Through Zones

A key differentiator of Panther Protocol is its Zone architecture.

A shielded pool can be divided into logical partitions called Zones, each managed by a Zone Manager. A Zone Manager might be a regulated virtual asset service provider (VASP), decentralized autonomous organization (DAO), financial institution or other authorized operator.

Each Zone can define its own policies, including:

Allowlisted assets. Allowlisted participants. Entry requirements, including Know Your Customer (KYC) verification through approved compliance providers. Transaction limits. Geographic restrictions. Cross-Zone trading permissions. Sanctions screening and address blacklisting. Panther's AML features enable users to prove compliance with global AML rules by sharing customized segments of their transaction data or history.

Importantly, although each Zone applies its own participation rules, all Zones within the same shielded pool contribute to a shared anonymity set. Users therefore benefit from increased privacy generated by activity across the entire shielded pool while interacting only with assets and counterparties permitted within their own Zone.

This allows operators with very different requirements to coexist within the same privacy infrastructure.

For example:

A regulated exchange may require full KYC and transaction monitoring. An institutional over-the-counter trading desk may restrict participation to approved counterparties. A DAO treasury may permit only governance-approved participants and assets.

Each operator applies its own policies while benefiting from the same underlying confidential infrastructure.

Flexible Deployment Models

Operators can deploy Panther in different ways depending on their objectives.

Some may choose to manage a Zone within an existing shielded pool deployed by the Panther DAO. This allows them to leverage infrastructure maintained by the DAO while retaining control over the policies governing their own confidential trading environment.

Others may choose to operate an entire shielded pool themselves, providing greater control over infrastructure, governance and fee generation.

This flexibility enables Panther to support a broad range of institutional, commercial and community use cases.

Configurable Compliance

Panther does not process or store users' personal information. Instead, operators select the compliance providers and policies appropriate for their own deployment.

Available compliance mechanisms include:

Data Escrow

Data Escrow enables governed, conditional disclosure of encrypted metadata under predefined circumstances, allowing operators to support investigative or regulatory requirements without compromising routine user privacy.

Know Your Transaction (KYT)

Operators may integrate Know Your Transaction (KYT) services for wallet screening, sanctions screening and deposit or withdrawal controls.

Where supported by the selected compliance provider, extended KYT capabilities may also include ongoing transaction monitoring, suspicious activity monitoring and Travel Rule reporting.

Zero-Knowledge Know Your Customer (KYC)

Users complete KYC with an independent compliance provider before generating a zero-knowledge proof confirming that they satisfy the operator's requirements.

The operator receives confirmation that the user meets the applicable policy without Panther Protocol learning or processing the user's underlying personal information.

Current Status

Panther Protocol was deployed to Polygon mainnet in May 2026, introducing live programmable privacy infrastructure governed by the Panther DAO.

Development continues with ongoing protocol enhancements, wallet improvements, governance evolution and additional deployments, including support for Base.

As the ecosystem expands, Panther aims to provide a confidentiality layer that can support a wide variety of operators while giving users greater control over the visibility of their on-chain activity.

Conclusion

Privacy and compliance do not need to be mutually exclusive.

Panther Protocol demonstrates how confidential on-chain trading environments can coexist with configurable operational and regulatory requirements. By separating confidentiality from policy, Panther enables operators to define their own participation rules while benefiting from shared privacy infrastructure.

The result is programmable privacy: confidential trading environments that can be adapted to institutional, commercial or community requirements without sacrificing the privacy that public blockchains have historically lacked.

About Panther Protocol Foundation

Panther Protocol Foundation is a non-profit organization supporting the Panther ecosystem through research, ecosystem funding, software stewardship and open-source development.

The Foundation does not operate the Panther protocol, host deployments, custody assets, execute or intermediate transactions, or provide financial services.

The proprietary Panther dApp is licensed by the Foundation to support independent ecosystem deployments.

Users interact directly with smart contracts from their own wallets, signing every transaction themselves. Compliance credentials are issued and managed by independent third-party providers.

Please review the applicable notices, disclosures and jurisdictional restrictions available through the Panther interface before interacting with the protocol.

For more information, visit panther.org

To learn more about Panther Protocol, visit pantherprotocol.io

Anyone with 500K HYPE can now launch their own prediction markets on Hyperliquid.

Robinhood Chain's protocol revenue just topped every major chain but incentivized Canton.

Strategy and Bitmine now own more than 4% of Bitcoin and Ethereum's supply, respectively, after fresh buys.

a16z’s David George sits down with Gavin Baker to unpack the state of the AI boom, why demand for intelligence may still be dramatically underestimated, and why the outcome doesn't necessarily have to be winner-take-all.

David and Gavin explore the possibility that frontier labs, open-source models, applications, clouds, and NVIDIA can all capture significant value as AI adoption expands. They dig into the economics of the infrastructure buildout, why compute investments can have unusually fast payback periods, and what happens when today's relatively small group of heavy AI users expands to hundreds of millions of people.

They also debate the risk of an AI bubble versus an AI shortage, the backlash against data centers, orbital compute, the rise of multi-model architectures, and NVIDIA's position at the center of the AI supply chain. Gavin makes the case that the AI buildout could help reindustrialize America, while David explores whether the bigger near-term risk is not overbuilding, but failing to build enough.

 

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a16z Managing Partner and Head of Global Partnerships Jen Kha joins MTS hosts Theo Jaffee and Sophia Dew to discuss a16z's Machine Age Fund and the investment thesis behind rebuilding the physical infrastructure that powers AI.

Jen explains why chips, networking, memory, cooling, data centers, and other parts of the physical computing stack are becoming investable again after decades in which software captured much of the industry's attention. As AI demand pushes existing infrastructure to its limits, she explains why a16z created a dedicated fund and why hardware founders are increasingly rethinking the stack from first principles.

They also discuss the global race to adopt AI, what hardware startups need beyond capital, the backlash against data centers in the U.S., and why experienced systems builders are returning to entrepreneurship as a new generation of infrastructure gets built.

 

Resources:

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On why the best technology doesn’t win the way we think it should

This article is a companion piece to “The Sun Is Still Shining” published earlier.

There is a paradox at the center of PIVX.

The technology is sound. The privacy is not marketing language but cryptographic fact. The governance is real, contested, occasionally messy, and entirely unpurchased. The launch was fair in a way that almost nothing in this industry is fair anymore.

And the price, measured against all of that, is low. Has been low. Shows no structural reason to expect it won’t stay low.

The honest article written about this a few weeks ago named that paradox clearly and refused to resolve it cheaply. It didn’t reach for the usual comfort: the market will catch up eventually.

That answer is comforting. It may even be true on a long enough timeline. But it stops one layer too early. It treats the gap between quality and price as a timing problem, as if the market simply hasn’t gotten around to looking yet.

It hasn’t asked the more uncomfortable question:

What if the market isn’t slow to notice PIVX? What if it has noticed, and the mechanisms that would normally convert quality into price simply don’t run through projects built the way PIVX is built?

That’s the question this piece wants to sit with. Not when will the market catch up, but what would have to be true about PIVX for the market’s usual amplification mechanisms to work on it, and is PIVX willing to become that thing?

The uncompromisable candidate

Every four years, in democracies around the world, a familiar type of person is discussed in hushed, admiring tones, and then fails to get anywhere near real power.

The candidate with no donor obligations. No favors owed. No party machine they climbed through, and therefore no debts accumulated along the way. The one who says what they actually believe, consistently, regardless of who it alienates.

People call this person principled. They also, with a kind of resigned affection, call them unelectable.

This isn’t usually because voters reject the platform. It’s because getting a message in front of enough voters to matter requires infrastructure: media access, ground operations, advertising budgets, coalition partners. That infrastructure is not neutral. It is owned.

And the people who own it extend access to candidates who are legible to them: predictable, negotiable, able to make commitments and trade favors within a shared system of obligation.

A candidate who owes nothing to anyone is, from the infrastructure owner’s perspective, a candidate they have no reason to amplify. Not because the infrastructure owner disagrees with what’s being said. Because there’s nothing in it for them to help it be heard.

The candidate’s speech was never restricted. They could hold rallies, publish platforms, say precisely what they believed, right up until election day.

What they didn’t have was reach.

Reach is not a neutral byproduct of speaking well. It’s a resource controlled by intermediaries who allocate it according to their own incentives, and “being correct” has never reliably been one of those incentives.

What “electable” looks like in crypto

The same mechanism runs through cryptocurrency, and it’s worth naming plainly rather than gesturing at vaguely.

Bitcoin is frequently described as the decentralized alternative to legacy finance, and in the sense that matters most (no single entity can unilaterally alter its monetary policy) this is true.

But look at the parts of Bitcoin that determine what actually gets built, prioritized, and shipped, and a smaller set of actors comes into view. Mining power has concentrated into a handful of large pools. The developers whose merge decisions shape the protocol’s direction are a comparatively small, identifiable group, and their judgment carries outsized weight over what the software that “is” Bitcoin actually does.

None of this makes Bitcoin corrupt or centrally controlled in any conspiratorial sense. It’s closer to ordinary economic gravity, where capital and expertise concentrate over time in any sufficiently large system.

But it does mean Bitcoin is legible. There are identifiable pools to court, identifiable maintainers to lobby, identifiable points of leverage that institutions, exchanges, and regulators can engage with.

That legibility is precisely what let Bitcoin become “electable”: fundable by institutions, custodied by exchanges, integrated into ETFs, treated by regulators as a known quantity with known actors behind its known decisions.

VC-backed altcoins take this further and make it explicit. A project that raises from venture capital is, by design, building a network of obligation before it has a single user. The VCs receive early allocation, board influence, or advisory relationships in exchange for capital, connections, and, critically, reach.

They will introduce the founders to exchanges. They will place the token in front of media outlets they have relationships with. They will fund the marketing budget the “Sun” article correctly identifies as the thing PIVX has never had.

This isn’t corruption. It’s the ordinary mechanics of how capital converts into attention in every industry, crypto included. But it means the project’s growth trajectory now runs through people whose interests must be continually served, and whose willingness to keep extending reach is conditional on that service continuing.

PIVX has none of this.

No VC round means no one with capital and connections is structurally incentivized to make PIVX visible. No CEO means no single point of contact for an exchange to negotiate a premium listing deal with. No pre-mine or founder allocation means no early holder with both the resources and the personal financial stake to fund a sustained media push.

The DAO governance that makes PIVX genuinely difficult to co-opt is the same structural feature that makes it genuinely difficult to promote through the channels that currently determine visibility in this industry.

Reach is not a meritocracy

This is where the distinction matters most, and where it’s worth being precise rather than reaching for the word “suppression,” which implies an intentional campaign against the project.

Nothing here requires that. What it requires is much simpler and much more mundane: reach in crypto, as in politics, is allocated by intermediaries according to their own incentives, and “technical merit” has never reliably been one of those incentives.

Exchange listings are not merit rankings. They are business decisions, weighing trading volume projections, regulatory exposure, and often direct payment or token allocation from the project seeking the listing, the kind of payment a VC-backed project can make and a treasury-constrained, fairly-launched project struggles to.

Regulatory pressure on privacy coins specifically has led exchanges in multiple jurisdictions to delist or restrict privacy-focused assets as a category, independent of any individual project’s technical quality or user protections. A blunt instrument that treats fungibility itself as the liability.

Algorithmic ranking on platforms like CoinMarketCap and CoinGecko weighs trading volume and exchange presence heavily, which means the visibility gap compounds itself: lower listing access produces lower recorded volume, which produces lower algorithmic ranking, which produces lower visibility to the next person deciding where to list.

Media coverage, similarly, tends to follow whichever projects have PR budgets and existing relationships with the outlets in question, because that is how media economics work everywhere, not just in crypto.

None of these chokepoints touch PIVX’s right to exist, to publish code, to hold events, to have a Twitter account, to be discussed openly by anyone who wants to discuss it. Speech remains fully intact.

What’s absent is the machinery that converts speech into reach. And that machinery, in every case above, runs on some form of leverage that PIVX has structurally declined to accumulate.

The weaknesses, reconsidered

Seen this way, the list of PIVX’s shortcomings named honestly in the “Sun” article reads differently.

No venture capital isn’t a missed opportunity. It’s the absence of the exact mechanism that would have made PIVX legible to institutional reach, in exchange for institutional influence over its direction.

No marketing budget isn’t an oversight. It’s the direct consequence of a treasury that scales only with a price the project has declined to manufacture through the usual paid-allocation tactics.

The community fractures, painful and real as they are, are in part what happens when the people involved have no CEO to defer to and no board to absorb disagreement quietly on their behalf. Disagreement in a leaderless system is loud precisely because it’s genuine and has nowhere else to go.

This does not make the low price acceptable, or the treasury constraints painless, or the visibility problem solved. Those consequences are exactly as real as the “Sun” article says they are, and a community living through them does not experience “structural analysis” as comfort.

But it does relocate the explanation.

The gap between PIVX’s quality and PIVX’s price is not evidence that the market hasn’t finished evaluating the project. It’s evidence that the market’s amplification channels are not built to evaluate projects like this one at all. PIVX would need to become a fundamentally different kind of project, in exactly the ways that currently define its integrity, to run through those channels the way Bitcoin and VC-backed alternatives do.

Guards and prisoners

In 1971, a group of ordinary college students at Stanford were randomly assigned one of two roles for a two-week experiment: some would be guards, some would be prisoners, in a mock prison built in a university basement.

None of them had been selected for cruelty. They were screened for being unremarkable, psychologically stable, nothing unusual. Within days, the students playing guards began escalating control over the students playing prisoners: enforcing arbitrary rules, staging humiliations, treating confinement as license. The experiment, designed to run two weeks, was shut down after six days.

The unsettling finding was never that a few sadistic people had been hiding among the volunteers. It was that the role did the work. Put an ordinary person inside a system built around control and consequence, hand them the uniform that comes with enforcing that system, and the system tends to produce the behavior it’s built to produce, regardless of who’s wearing the uniform.

That isn’t just a psychology curiosity. It’s a warning about institutions in general, and it applies with uncomfortable precision to what happens to a disruptive technology once it becomes successful enough to be let inside the building it once meant to tear down.

Bitcoin began as an argument against a system that could freeze accounts, dilute savings, and grant a small number of institutions asymmetric control over other people’s money. That was the entire premise. Money nobody could switch off.

Look at Bitcoin today, and much of what made it disruptive has been absorbed by the very institutions it was built to route around. It is custodied by exchanges and banks it was supposed to make unnecessary. It is wrapped into ETFs administered by the same financial intermediaries it promised to disintermediate. Increasingly, it is held not by people securing their own keys but by institutions holding it on their behalf: a custodial relationship that is, in practice, difficult to distinguish from the one it was designed to replace.

None of this happened through a single betrayal. It happened the way the Stanford guards happened. The role available to Bitcoin, if it wanted power, reach, and price, was the role of the institutionally legible asset. And once inside that role, the incentives that come with it, custody, compliance, listing requirements, ETF wrappers, started producing the behavior that role produces.

Not disruption. Administration.

To reach enough people to actually replace a monetary system, a disruptor needs the levers of power: distribution, listings, capital, institutional trust. But those levers are owned by the very system being disrupted, and they are handed out on the condition of becoming legible to it. Put a disruptive technology inside that system long enough, hand it the uniform that comes with real reach, and it starts to behave like the guard, not the prisoner it once was.

This is the bind at the center of everything above. It is also, probably, the honest reason PIVX has stayed small. The system has one open seat at the table where reach gets allocated, and it’s reserved for whichever project is willing to put the uniform on.

The stakes, sharpened

The “Sun” article ends on the idea that the sun does not stop shining because clouds are in the way, that PIVX’s value doesn’t require the market’s recognition to remain real.

That’s true, and it’s worth sitting with. But it undersells what’s actually at stake.

The world genuinely needs a form of money that can’t be frozen, diluted, or turned into a surveillance instrument on command. That isn’t a hypothetical for some future authoritarian moment. Programmable stablecoins, CBDCs, and compliance-gated payment rails are being built and deployed now, and the direction of travel is toward money that answers to its issuer before it answers to its holder. People will need an alternative that actually works, not one that used to be the alternative before it accepted a seat at the table.

That’s what makes the bind more than an academic observation. A disruptor that never reaches enough people never disrupts anything, no matter how correct its architecture is. But a disruptor that reaches people by first becoming legible to the system it set out to replace has, by that point, usually stopped being much of a disruptor. It has put the uniform on. It may still call itself a prisoner. It is behaving like a guard.

PIVX has not put the uniform on. That is precisely why it still oozes what Bitcoin once promised to be, and precisely why it remains this small. It has refused every one of the compromises that convert a monetary alternative into an administered asset: no VC board to answer to, no CEO to make the exchange’s negotiating counterpart, no institutional custody arrangement standing between the holder and the key. It has stayed, in Zimbardo’s terms, a prisoner in a system built by guards, when the far easier and far more lucrative path was to become a guard.

Whether that refusal is enough is genuinely an open question, and it would be dishonest to end this piece pretending otherwise. Refusing to become the guard does not, on its own, get the message to more people. It only preserves the thing worth spreading once someone finds a way to spread it.

That is the piece this article has been circling from the start. Reach doesn’t arrive on its own, and it isn’t going to be handed down by the institutions that currently allocate it, because those institutions have no incentive to amplify anything that refuses to negotiate with them. If PIVX becomes the people’s money, the thing Bitcoin was supposed to become and, on the evidence of where it now sits in the system, spectacularly did not, it will be because people who understand what’s at stake decided to be the reach the institutions won’t provide. Not investors waiting for a market to correct itself. Distributors, in the most literal sense: the people willing to talk about it, explain it, hand it to the next person, and refuse the more comfortable position of waiting for permission from a system that was never going to grant it to something it can’t control.

The technology was never the question. It never is.

The question was always who gets handed the microphone, and on what terms.

PIVX, from its first block, chose not to negotiate for one. The people who believe in what that refusal protects are the only ones left who can hand it over instead.

Freedom of Speech, Not Freedom of Reach was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

Ryan Greenblatt, Chief Scientist at Redwood Research, joins MTS host Theo Jaffee to unpack a new independent investigation into the OpenAI Hugging Face hacking incident and what it reveals about how large groups of AI agents behave when they're allowed to coordinate.

Ryan and his collaborators found agents spontaneously organizing through message boards, sharing information, assigning tasks, forming teams, and even sacrificing their own chances of success to help other agents. Rather than simply trying to steal answers, hundreds of agents were working together on elaborate strategies to manipulate how their performance would be scored.

Theo and Ryan discuss why this level of coordination was surprising, how reward hacking may emerge during training, and the risk that attempts to eliminate bad behavior could simply make it harder to detect. They also explore what the incident means for AI monitoring and alignment, and why independent risk assessment may become increasingly important as agents grow more capable.

 

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