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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.
Zebra 6.4.0 is a security release that also adds an experimental lightwalletd-compatible gRPC server, lowers the ZIP 317 conventional fee, speeds up block template delivery for miners, and moves the end-of-support halt earlier in preparation for NU7, which is tentatively scheduled for November 5, 2026. Zebra 6.4.1, released the same day, fixes a potential sync stall near the chain tip.Node operators are strongly encouraged to upgrade straight to version 6.4.1. Before 6.4.1 halts around November 2, operators should also prepare to update to the upcoming release planned for next week, which will feature NU7 support.
Security Advisories GHSA-3c94-hf7p-g5mf: Forged Block Bodies Could Stall SyncA peer could serve a block with a canonical hash but a forged body whose authorizing data did not match the header commitment. Zebra treated this as an ordinary invalid block, so it canceled the whole sync round, paused the syncer for its restart delay, and dropped the block hash instead of requesting it again, letting a malicious peer repeatedly stall a node’s sync. Zebra now continues the sync round and re-requests the body from another peer, up to a bounded number of retries, and re-requests blocks rejected only because they were queued behind a forged body without penalizing the peers that served them (#11502).
Thanks to @ouicate for reporting this issue.
GHSA-4f6v-mj46-gxg3: Coinbase scriptSig Rewrite Not Penalized on the Inbound PathPeers relaying blocks with a rewritten coinbase scriptSig on the inbound path were not penalized. Zebra now scores misbehavior for peers that do this (#11502).
Thanks to @craftsoldier (Julian Abraham) for reporting this issue.
GHSA-jhpp-8h75-7pv5: Peer Limits and Bans Apply Per IPv6 /64Connection limiting under network.max_connections_per_ip and peer bans now apply to a whole IPv6 /64 subnet rather than to each individual address, so a single machine can no longer bypass the limit or evade a ban by connecting from many addresses in the same allocation. IPv4 connections are still limited per address (#11256).
Bans now expire after 24 hours instead of lasting until Zebra restarts, so a peer banned by mistake, or one that shares an IPv6 /64 with a misbehaving peer, is not shut out permanently (#11256).
Peers that advertise a block containing duplicate transactions are now scored for misbehavior, matching how Zebra treats other definitive block-validity violations (#11157).
Breaking Changes Earlier End-of-Support Halt Ahead of NU7The end-of-support window is now 12 weeks instead of 15, so Zebra 6.4.x halts in early November 2026, around November 2, ahead of NU7’s tentative November 5 activation. We recognize that shortening the window is not ideal and do not intend to make it a common practice, but it ensures nodes move to the NU7-supporting release in time. Operators can check their node’s exact halt height and estimated time with the getdeprecationinfo RPC (#11491).
rpc.max_response_body_size is now limited to 4,294,967,295 bytes. Configurations with larger values must be reduced; they are now rejected when the configuration loads instead of causing an RPC server panic at startup (#11259).
Zebra can now serve Zcash light clients directly. A new experimental gRPC server implements the lightwalletd CompactTxStreamer interface and is enabled by setting rpc.lightwalletd_listen_addr in the config (#10953).
Following zcash/zips#1352, the mempool now accepts transactions paying at least 1,000 zatoshis per ZIP 317 logical action instead of 5,000 (2,000 instead of 10,000 for a minimal transaction), and getstandardfee reports 1,000. Block template construction follows the new conventional fee and raises the fee weight ratio cap from 4 to 10, widening the priority lane for transactions that pay more than the conventional fee (#11290).
When a miner address is configured and the RPC server or internal miner is enabled, Zebra now precomputes block templates, refreshing them on chain tip changes and every few seconds, so getblocktemplate can respond immediately. A template can trail the mempool by a few seconds, but each one is checked against the committed tip (#11371).
Zebra now caches Orchard, Ironwood, and Sapling bundle verification results, so proofs and signatures verified when a transaction enters the mempool aren’t verified again when the block that mines it arrives. The cache is reported through new zebra.consensus.cache.* metrics (#11380).
New zcash.pool.value.zatoshis and zcash.pool.notes.created metrics, labeled by pool, report value pool balances and note commitment counts at the chain tip (#11391).
Zebra could stall permanently after a sync restart near the chain tip, repeatedly logging “queued download of hash behind our chain tip” until the node was restarted. Zebra 6.4.1 fixes this (#11510).
Sync Restart Loop on Transient TimeoutsThe syncer no longer restarts when a transparent input lookup times out near the tip, or when the short post-checkpoint verification timeout fires. Both are transient races, and restarting canceled the in-flight parent block, which could cause a restart loop (#11377).
Chain Selection on Equal-Work TiesWhen two competing chains have equal cumulative work, Zebra now prefers the chain whose tip it received first, as the Zcash protocol specifies, instead of the chain with the greater tip hash (#11341).
Mempool Peer Slots Freed on TimeoutThe mempool now frees a peer’s download slot when one of its transactions times out during verification. Previously, each timeout permanently used a slot until the mempool rejected all further transactions from that peer (#11229).
Consistentz_gettreestate During Reorgs z_gettreestate no longer returns null commitments for a block that a concurrent reorg moves onto a side chain (#10820).
The embedded zcashd-compat sidecar is now pinned to zebra-compat-v1.2.0, which raises its reorg limit from 99 to 1,000 blocks to match Zebra. The previous sidecar shut itself down on reorgs deeper than 99 blocks. Wallets holding shielded notes should expect the witness cache and wallet.dat to grow roughly tenfold, gradually over about 900 blocks. The installer’s split-container Docker mode also now prints a working zcashd container command (#11413).
Zebra drops the unmaintained ordered-map crate along with its legacy dependencies (#11321), updates nix to 0.31 (#11267), and builds librocksdb-sys so libclang loads correctly when more than one bindgen version is present (#11444).
Zebra 6.4.1 is available from GitHub, crates.io, and Docker Hub as zfnd/zebra:6.4.1. Library consumers should note that zebra-rpc and zebra-state include breaking API changes in this release.
This release was made possible by the work of @alchemydc, @andres-pcg, @aphelionz, @arya2, @Bortlesboat, @CodeMongerrr, @conradoplg, @craftsoldier, @evan-forbes, @gustavovalverde, @jiehuo100net, @john-lawniczak, @LarryRuane, @mpguerra, @natalieesk, @oxarbitrage, @questfever, @robustfengbin, @str4d, @syszery, and @upbqdn. Thank you for your continued contributions to Zebra.
Zebra is the Zcash Foundation’s independent, Rust-based implementation of the Zcash protocol. Learn more at github.com/ZcashFoundation/zebra.
The post Zebra 6.4.0 and 6.4.1: Security Fixes, Light Client Serving, and NU7 Preparation appeared first on Zcash Foundation.
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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Join Firo: Private cryptocurrency infrastructure, BasicSwapDEX, Particl and PIVX!
🗓️ Sept 30th 9:00 am EST/1:00 pm
📍 Xspace
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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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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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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.
Resources:
Learn more about the Paid in Full Foundation: https://paidinfullfoundation.org
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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.
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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.
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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.
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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.”
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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 BaseBase 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 AssetsNow that Panther is live on Base, users can privately interact with the following assets:
ZKP cbBTC ETH USDC AERO ZORA VIRTUAL MORPHO AAVEAdditional 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 NextNow 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 FoundationPanther 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 ZCAP poll on the outstanding scope questions for NU7 has closed, having run since August 27th concurrently with the coinholder poll.
This poll followed the NU7 Sentiment Polling from earlier this year, which surfaced where the community stood on a range of possible NU7 features but left several questions open. These five questions were intended to settle them. We announced the poll on the Zcash Community Forum, and the questions themselves were discussed there in the weeks beforehand.
ZCAP ParticipationA total of 135 Zcash Community Advisory Panel (ZCAP) members cast ballots out of 198 eligible participants, representing a 68% response rate. Each question was answered separately, and voters were permitted to abstain from individual questions while still submitting a valid ballot. The polling results page is available here.
Results at a GlanceWe want to thank every ZCAP member who took the time to review the proposals, engage in discussion, and cast their ballot.
The post ZCAP Polling Results: NU7 Scope appeared first on Zcash Foundation.
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.
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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.
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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.
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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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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.
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The Zcon7 program is live! View the full program and speakers lineup.
Zcon7 is happening October 27–29 in Cancún, Mexico.
This year, we designed Zcon differently. There are fewer presentations, more conversations, and more opportunities to engage with the questions that will shape what comes next for Zcash. Everyone in the room is part of making our future.
Zcon7 will bring the Zcash community together for three days of debates, panels, workshops, technical discussions, and small-group conversations. The program is designed to create space for the conversations that need to happen- not just from the stage, but across the room (and on the beach).
We’ll dig into some of the biggest questions facing Zcash: What should Zcash governance look like? How do we accelerate development without sacrificing security? What technical threats should we be preparing for? How do we bring the next 1,000 developers into the ecosystem? Should the Dev Fund end? Do you support ZSAs? And, fundamentally, what is Zcash for—and where do we want it to go next?
You can expect different perspectives, disagreement, technical depth, and plenty of opportunities to participate. Rather than filling the schedule with back-to-back presentations, we’ve deliberately created room for interaction and reflection, including small-group discussions throughout the event.
Zcon has always been about bringing the Zcash community together. This year, we want to make the most of having so many people who build, fund, research, use, secure, and care about Zcash in the same place at the same time.
The future of Zcash isn’t something we’re coming together to hear about, it’s something we’re coming together to make.
We still have a few spots available. Apply to attend Zcon7 here.
See you in Cancún.
¡Vamos!
The post The Zcon7 Program: Building What Comes Next appeared first on Zcash Foundation.
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.
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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.
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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.
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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.
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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.
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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.
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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.
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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 MobileA 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 exploitAn 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.
Verus Galactic: a native Apple Silicon walletVerus 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 stackChainVue’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 toolsVerus 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 minersWalled 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 toolVerus 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.
NoteWe 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
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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 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:
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Learn more about Atlas: https://www.worldlabs.ai/blog/atlas
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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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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.
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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 actionPreston 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-makingRohan 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 challengeBoth 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 itWhether 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.
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/
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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 dataThese 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 softwareThis 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 WorkloadWe 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 benchmarkingTo 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.
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 toloadEventEnd 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. CPUThe 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. MemoryFigure 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 timeFigure 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 atloadEventEnd, 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 consumedTo 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 benchmarksWhile 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).
ConclusionAcross 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.
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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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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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 BoundariesPublic 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 PoolsAt 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 FoundationPanther combines several cryptographic components to deliver confidential transactions.
zk-SNARKsZero-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 TreesAppend-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.
zAssetszAssets 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.
zAccountsWithin 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 ZonesA 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 ModelsOperators 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 CompliancePanther 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 EscrowData 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 StatusPanther 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.
ConclusionPrivacy 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
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.
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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 candidateEvery 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 meritocracyThis 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 prisonersIn 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, sharpenedThe “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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Ben Horowitz, Martin Casado, Raghu Raghuram, and Erik Torenberg discuss the launch of a16z's new Machine Age Fund and the infrastructure buildout behind AI, from chips, memory, and networking to power, cooling, and data centers.
Why a dedicated fund now? The group argues that the bottleneck in AI is increasingly shifting from the models themselves to everything beneath them. Hyperscaler CapEx is surging, critical components are booked years in advance, and each new generation of reasoning and agents requires dramatically more compute. They unpack why this cycle looks different from previous infrastructure booms and how AI is turning problems once constrained by engineering into problems that can increasingly be attacked with capital and compute.
They also explore where the next generation of infrastructure companies could emerge, why founders are returning to hard technical problems across hardware and systems, and what it will take to rebuild the computing stack for the Machine Age.
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In 1993, Eric Hughes wrote a short document that became something like scripture for a certain kind of person: the Cypherpunk Manifesto. Its argument was simple and, at the time, radical. Privacy in an electronic age wouldn’t be handed down by governments or corporations, because those institutions have no structural reason to grant it. If you wanted privacy, you had to build it yourself, in code, and defend it yourself, without asking permission. Cypherpunks write code. That was the whole ethos, in three words.
It’s worth holding that standard up against the current state of the project most people would name first if you asked them for the cypherpunk-coded privacy coin.
A ticker symbol that says the quiet part out loud
There is, right now, a company trading on the Nasdaq stock exchange under the ticker CYPH. Its name is Cypherpunk Technologies Inc. It used to be a biotech company called Leap Therapeutics, before a $58.88 million private placement, led by Winklevoss Capital, rebranded it into a Zcash accumulation vehicle. It currently holds several hundred thousand ZEC and has stated a public target of accumulating 5% of the entire circulating supply. It has also invested millions alongside a16z, Coinbase, and Paradigm into Zcash’s development ecosystem.
Sit with that for a second. A publicly traded company, answerable to shareholders and the SEC, has taken the name of a 1990s cryptographic freedom movement and put it on a stock ticker. Not as commentary. As a business strategy. It’s the same playbook Michael Saylor built at MicroStrategy, buy the asset, hold it on the corporate balance sheet, let the stock price track the coin, multiple financial outlets have described Cypherpunk’s approach as explicitly modeled on it.
Here’s the part that actually matters more than any single name attached to it. In December 2023, Zooko Wilcox stepped down as CEO of Electric Coin Company, writing at the time that Zcash’s identity had become too conflated with his own, and that he didn’t think that was healthy for either of them. He went further in early 2025, resigning from the Bootstrap Project board entirely, stepping fully outside the institutional structure he’d built, and moved on to Chief Product Officer at Shielded Labs, a separate research organization. By any reasonable reading, that’s a founder deliberately trying to opt out of exactly the kind of institutional entanglement this piece is describing.
In December 2025, he joined Cypherpunk Technologies as a Strategic Advisor anyway.
That’s the detail worth sitting with, not because it proves Wilcox personally controls anything, he doesn’t, he isn’t on ECC’s board and had no role in January’s implosion, but because of what it says about the gravity involved. A founder who explicitly stepped back from institutional Zcash, specifically to avoid being the personal face of its direction, still ended up back in orbit around a Wall-Street-style accumulation vehicle trading his protocol’s ticker on Nasdaq. If the pull toward capital is strong enough to draw back in someone who visibly tried to leave, that’s not a story about one person’s choices. It’s a story about how much gravity a for-profit company with venture roots generates once it exists, regardless of who’s currently sitting in which chair.
That alone would be worth a raised eyebrow. It’s not the whole story, though. It’s just the most visible symbol of something structural that’s been building for years, and that finally broke into the open this January.
What actually happened in January 2026
Zcash’s core protocol development has been led since the beginning by the Electric Coin Company, ECC, a for-profit entity legally housed under a nonprofit called Bootstrap. ECC itself was seeded in 2016 with venture capital, a $1 million round led by Pantera Capital, followed by a $2 million round led by Digital Currency Group, with angel investors including Barry Silbert and Erik Voorhees. None of that was hidden. It’s also, on its face, a strange origin story for a project claiming the cypherpunk mantle, cypherpunks write code, they don’t typically pitch decks to venture capital first.
That tension sat mostly dormant for years. Then, on January 8, 2026, it ruptured. The entire ECC team was forced to resign, in what former CEO Josh Swihart publicly called a constructive dismissal, engineered by Bootstrap’s board. The immediate trigger: ECC wanted to privatize Zashi, Zcash’s flagship mobile wallet, spinning it out to raise outside capital and accelerate development. Bootstrap’s board refused, on the grounds that doing so would violate its legal obligations as a nonprofit protecting a public asset. The team left en masse. ZEC dropped 20% within hours, briefly falling below $400. Swihart and his former team have since started a new company to build a competing wallet from the same codebase.
Whatever you think of either side’s position, and there are reasonable arguments on both, notice what the fight was actually about. Not cryptography. Not privacy architecture. A dispute over whether the project’s future should run through more outside capital, adjudicated by a nonprofit board versus a team that wanted to go get funded. That’s not a cypherpunk disagreement. That’s a business disagreement that happened to be wearing cypherpunk clothing.
To be fair, because the cryptography deserves it
None of this is a knock on Zcash’s actual technology. Zero-knowledge proofs, zk-SNARKs specifically, are one of the most important cryptographic contributions to come out of this entire space, and Zcash’s team did real, foundational work bringing that research into production. The trusted setup ceremony, the Sapling and Orchard upgrades, the ongoing work on quantum-resistant shielded pools, this is serious cryptography built by serious people. The critique here isn’t about whether Zcash’s engineers know what they’re doing. It’s about what surrounds the engineering: who funds it, who governs it, and what happens when those two things pull in different directions, which, as of January, they very publicly did.
The actual cypherpunk question
So here’s the question worth sitting with, the one Hughes’ manifesto actually poses, not “which privacy coin has the best marketing” but “which one doesn’t need anyone’s permission or capital to keep existing.”
What would that look like in practice? No founding venture round. No company with a ticker symbol sitting between the protocol and its users. No nonprofit board with legal authority to fire the entire development team over a fundraising dispute. No flagship wallet that can be privatized in the first place, because there’s no private entity positioned to privatize it.
Go through that list one item at a time, because it’s worth checking each claim rather than taking the summary on faith.
No founding venture round. PIVX launched with no ICO, no pre-mine, and no venture round, at any point across its now ten-year history. Every coin in circulation entered the same way everyone else’s did, mined or staked, not allocated to early investors before the public ever got a chance to buy in. There was no seed round to disclose because there was never a seed round.
No company sitting between the protocol and its users. There is no PIVX Inc. There is no CEO whose departure could trigger a 20% price drop, because there’s no CEO whose presence the price ever depended on. Development happens across a distributed set of contributors, funded proposal by proposal, not managed by an entity with a legal existence separate from the community itself.
No board with authority to override the community. PIVX’s treasury is spent exactly one way: anyone can submit a proposal, but only the network’s masternodes, each backed by 10,000 PIV in locked collateral, get to vote on whether it passes, and only if it passes does the treasury pay out. There is no Bootstrap-style nonprofit board sitting above that process with legal power to fire anyone or veto a direction the community has chosen. The vote is the process. There’s no higher authority standing over it, in either direction.
No wallet a company could privatize. This is the part worth sitting with the longest, because it’s almost a direct answer to the exact fight that tore ECC apart in January. PIVX’s own flagship mobile and web wallet is built by PIVX Labs, and it’s funded the same way every other proposal is, through the masternode-voted treasury, not through outside investment. Nobody has ever proposed spinning it out into a company to raise capital, because there’s no mechanism by which that proposal could even be made. The wallet was never a corporate asset in the first place, so there was never a boardroom fight waiting to happen over who gets to sell it.
That’s four separate structural guarantees, not one. Zcash has serious, talented people and genuinely important cryptography. It also has a for-profit company with venture-capital roots, a nonprofit board with legal authority over that company’s biggest decisions, and, as of January, a real, public example of what happens when those two things disagree about whether to raise more outside capital. PIVX was built so that fight structurally cannot happen, not because anyone promised it wouldn’t, but because there’s no company to raise capital, no board to fight about it, and no wallet sitting there as a corporate asset waiting to be spun out.
And credit where it’s due, because none of this is a claim to better cryptography: PIVX’s shielded transactions exist because Zcash’s engineers did the hard, foundational cryptographic work first. PIVX’s SHIELD protocol is a heavily customized implementation of Zcash’s own Sapling protocol, adapted to run on a proof-of-stake network instead of proof-of-work, but the zk-SNARK cryptography underneath traces directly back to Zcash’s research and engineering. That lineage is real, and worth stating plainly rather than glossing over. What differs isn’t the cryptography’s origin. It’s everything built around it since.
Hughes wrote that cypherpunks write code, and that the ones who care about privacy will build it themselves rather than waiting for it to be granted. That’s not a slogan PIVX put on a website. It’s closer to a description of what building without a funding round, a ticker symbol, or a board to answer to actually requires, for ten years running, including through this year’s own stress test, when PIVX lost its Binance listing entirely and kept building anyway, with no company to bail it out and none needed.
Put simply: PIVX stayed close to the values it started with. Zcash fell for capital.
The question was never which privacy coin has better marketing, or even, entirely, which one has better cryptography. It’s which one still needs someone else’s permission to keep existing. Only one of them has ever had to answer that question by actually going and finding out.
Edit: An earlier version of this piece described Zooko Wilcox simply as “Zcash’s own founder” advising Cypherpunk Technologies, without noting that he stepped down as ECC’s CEO in 2023 and left the Bootstrap board entirely in 2025, well before January’s implosion. That framing overstated his current role. Thanks to the reader who flagged it, the section above has been corrected and, I think, made into a stronger point in the process.
The Cypherpunks Who Aren’t was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.
The PIVX ecosystem continues to move forward across network participation, market activity, privacy-focused development, and community growth. Here are the latest developments shaping the ecosystem this week.
Masternode Network
The PIVX masternode network currently stands at approximately 2,122 masternodes, with an estimated annual reward of 17.16% and around 20.02% of PIVX supply locked.
Masternodes remain an essential component of the PIVX network, contributing to network stability, decentralized governance, and the broader Proof-of-Stake ecosystem.
Market Update
PIVX is currently trading around $0.0145, with market activity continuing to develop amid changing liquidity and broader cryptocurrency market conditions.
24-hour trading volume is approximately $352,000, reflecting continued participation from traders and holders. MEXC remains an active venue for PIVX, with the PIVX/USDT market providing an accessible option for trading $PIVX.
Stablecoin Transparency & Financial Privacy
Tether has completed its first full independent financial statement audit, conducted by KPMG U.S., which issued an unqualified opinion on Tether’s 2025 financial statements.
For the stablecoin industry, this represents a notable step toward greater transparency around the financial position and assets backing USDT. While the complete audit report has yet to be publicly released, independent examination adds another layer of accountability to an increasingly important part of the digital asset economy.
For PIVX, the broader conversation around transparency also highlights why financial choice and privacy remain important. PIVX has maintained this focus since its inception, with no premine, no ICO, open-source development, decentralized governance, and optional financial privacy.
The underlying principle remains straightforward: individuals should have meaningful control over their money and their financial information.
Nigeria’s Evolving Crypto Landscape
Nigeria continues to develop its regulatory approach toward cryptocurrency and virtual assets.
New regulatory proposals and government initiatives could provide greater clarity for businesses, investors, and users while potentially attracting additional institutional participation. At the same time, regulation needs to strike a careful balance between oversight and innovation.
As one of Africa’s largest crypto markets, Nigeria’s approach could have a significant impact on how digital assets develop across the region.
Privacy Infrastructure
Privacy-focused infrastructure continues to expand beyond individual blockchain networks.
HoudiniSwap offers a non-custodial cross-chain swap and privacy aggregation service designed to separate the on-chain connection between sending and receiving wallets. Tools like these demonstrate the growing demand for greater financial privacy and user control across the broader crypto ecosystem.
For PIVX, privacy remains a core part of the mission: giving users the ability to choose when and how their financial activity is exposed.
PIVX & Cake Wallet Development
Development efforts are also expanding PIVX’s accessibility.
PIVX lead core developer @Liquid369 has pushed a public release to Cake Wallet for PIVX integration, including support for full SHIELD transactions.
Wallet integrations are an important part of making privacy technology practical for everyday users. Bringing PIVX’s SHIELD capabilities into additional wallet infrastructure can help broaden access to private transactions while giving users more choice in how they manage their funds.
Community & Ecosystem
Community remains at the center of the PIVX ecosystem.
Through PIVX.org, Discord, and Telegram, community members can follow development, discuss privacy and cryptocurrency, exchange ideas, and participate in conversations about the future of decentralized finance and financial freedom.
As the ecosystem continues to develop, accessibility, education, privacy, and community participation remain key areas of focus.
Looking Ahead
PIVX continues building on its long-standing commitment to privacy, decentralization, and individual choice.
From network participation and wallet development to broader conversations around financial transparency and regulation, the ecosystem is continuing to evolve while keeping user control at its core.
The coming weeks will bring further opportunities to expand accessibility, strengthen the network, and advance privacy-focused technology.
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: Privacy, Markets & Growing Accessibility was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.
Today, we opened a SIV poll of the Zcash Community Advisory Panel (ZCAP), which will run until Monday, September 14th, 19:00 UTC, concurrently with the coinholder poll. The purpose of this poll is to resolve the outstanding scope questions for NU7.
Deciding the Scope of NU7This poll follows the NU7 Sentiment Polling from earlier this year, which surfaced where the community stood on a range of possible NU7 features. Several questions were left open, and this poll is intended to settle them. We announced the poll on the Zcash Community Forum earlier this month, and the questions themselves were discussed there in the weeks since.
There are five questions. Each one is answered separately, and every question includes an option to abstain.
Q1 – NSM Issuance SmoothingThe component of the Network Sustainability Mechanism that removes ZEC from circulation is already approved. How that ZEC is recycled into future block rewards remains unresolved. In no case will the total supply of ZEC be affected. Refs: ZIP 233, ZIP 234.
Which approach do you support?
Smooth issuance curve. Replace halvings with a gradual issuance curve. ZEC removed from circulation by the NSM is recycled into future block rewards along the same curve. Preserve halvings. Keep the existing halving schedule for new ZEC. ZEC removed from circulation by the NSM is eventually recycled into future block rewards. Do not include issuance smoothing in NU7. How ZEC removed from circulation by the NSM is recycled into future block rewards is left to future governance. Abstain. Q2 – NSM Reissuance Start DateNSM has prior coinholder approval. This question concerns the start of reissuance of funds removed from circulation (which includes at least 60% of total fees). When should NSM reissuance of funds removed from circulation begin?
As soon as possible. If the outcome of Q1 is smoothed issuance, this will be February 2027; otherwise it may be sooner. February 2027, regardless of the outcome of Q1. February 2031, regardless of the outcome of Q1. Abstain. Q3 – Sprout DeprecationThe Sprout pool was deprecated in 2018. Deposits are disabled, it holds less than 23,000 ZEC, and it accounts for under 0.1% of transaction volume. Disabling v4 transactions is now broadly accepted; only timing is open. The disposition of the affected funds is out of scope for this poll and is not specified here. When should v4 transactions be disabled?
Immediately at NU7 activation. One year after this poll concludes. Do not set a date to disable v4 transactions. Abstain. Q4 – Faster Block TimesShould we reduce the block target spacing from 75s to 25s, and introduce per-pool action limits, per ZIP 218?
Yes. No. Abstain. Q5 – NU7 Scope and ReadinessNU7 will be consistent with the results of this poll, assuming each applicable feature is implemented by September 30th. How should features that are not ready by the deadline be handled?
Ship NU7 as soon as possible, removing any feature that is not implemented by the September 30th deadline. Delay NU7 until every applicable feature approved in this poll is deemed complete. I do not support this NU7 plan. Abstain. VotingZCAP members should check their mailbox for instructions on how to vote from election@siv.org. In the past, SIV emails have sometimes been flagged as spam, so if you can’t find the instructions please check your Spam folder.
Why ZCAP MattersThe ZCAP process is a transparent, community-driven way to surface the views and priorities of long-term Zcash supporters. Though advisory in nature, these votes play a vital role in informing decisions across the ecosystem. Thank you for lending your voice.
As always, we welcome feedback from the Zcash Community. If you have comments or suggestions, please join the conversation on the Zcash community forum.
The post ZCAP Poll Now Open: NU7 appeared first on Zcash Foundation.
This blogpost describes work done by Darnell Andries, Sofia Celi, Rafael Ebron, François Marier, Agustín Ruiz, Szilard Szaloki, the Engineering and Research teams and many other amazing people.
Today we’re introducing Brave Accounts, a brand new way to sign up for our Brave services, such as Email Aliases. However, contrary to what other services do, the way it handles your password is different from other login forms you have ever filled in.
Here’s the short version: when you sign in to a service built on Brave Accounts, your password itself is never sent to our servers: not encrypted, not hashed, nor “briefly held in memory and then discarded”. The password is never transmitted, so you don’t have to “trust” that we are keeping it safe for you. We don’t know it at sign-up, we don’t know it at login, and if someone were to steal our entire password database tomorrow, with high probability they still wouldn’t know it.
How do we do this? We are using cryptography, and specifically using a cryptographic protocol called OPAQUE (recently specified by the IRTF). We are in fact one of the first to use this new cryptography.
The problem with how login works todayThink about what happens when you type your password into a regular website in order to log in. Your browser opens a TLS connection, which encrypts the password in transit. This essentially means that no one looking at the network will be able to see your password. But, what happens when the password reaches the server where the website is hosted? The server has to have some representation of the password (often a hash) so that it knows that it is you who is authenticating. Often, this means that, at the other end (often at a load balancer or CDN before your application even sees it) the connection is decrypted and your actual password sits there in plaintext. The server, then, runs it through bcrypt or Argon2 (a hash-like mechanism) and compares the result against the stored representation.
You might reasonably ask: why not hash it in the browser and send only the hash (or the representation) instead of the password? Because then the hash is the password itself. Anyone who stole the database could replay the stored value straight back at the login endpoint. Verification has to happen on the server, against the real thing, so that the real thing has to be handed over.
That plaintext moment, however, is the whole problem. In that instant, the server knows your password, and so does anything with access to the server: a logging misconfiguration that writes request bodies to disk, a compromised dependency in the authentication path, a rogue insider, a memory-scraping attacker. Password managers and TLS don’t help here: the design requires the secret (the password) to be handed over.
Then, there’s the breach scenario. When a password database leaks, attackers get the optionally-salted hashes and start guessing offline, on GPUs, at billions of attempts per second. Worse, in many older protocols the salt is public or predictable, which lets attackers do the expensive work before the breach even happens, building precomputed tables and then cracking millions of accounts the moment the database drops. This is not a constrained scenario. When LinkedIn was breached in 2012, it was found that their password database was stored using unsalted SHA-1, which is a fast hash, with nothing to make one user’s entry substantially different from another’s. The initial dump was thought to cover 6.5 million accounts. When the full set surfaced four years later, it was 117 million, and roughly all of them were cracked in a few days. Identical passwords produced identical hashes, so recovering them was closer to a database lookup than a cracking job. And because most people reuse passwords, one company’s error becomes real users’ compromise across many services.
Enter OPAQUEOPAQUE is an augmented password-authenticated key exchange, an aPAKE. It came out of academic work by Jarecki, Krawczyk and Xu, was selected for standardization as part of the IRTF Crypto Forum Research Group’s PAKE selection process, and was published as RFC 9807 in July 2025. It has a formal security proof in a strong, universally composable model.
The core idea is that the client and server run a little cryptographic dance in which the client proves it knows the password without ever revealing it, and both sides (client and server) come out the other end sharing a fresh secret session key, with the ability for the client to log in to this server. This dance is super fast (thanks to elliptic-curve cryptography), so no impact is seen by users.
How it actually worksThere are two phases in the protocol. Bear with us here for the details: this is the genuinely interesting part.
Registration
You choose a password. Your device and our server jointly run an Oblivious Pseudorandom Function (OPRF). This means that: you blind your password with a random value and send the blinded version of it; the server applies a secret key it holds and sends the result back; then, your device unblinds it. The output is a value derived from both your password and our server-side secret (the secret key), but the server learned nothing about your password, and you learned nothing about the key. That’s what “oblivious” means here: both ends are oblivious to each other’s values.
Your device then runs that value through a memory-hard function (Argon2id), so that even in the worst case, every guess an attacker makes is expensive, and combines the result with a random nonce to derive an authentication key pair deterministically. Nothing secret, like your password, needs to be stored anywhere.
It sends us the resulting public key, a masking key, and a small envelope: just the nonce and an authentication tag. We store that. There’s no encrypted password in it and no encrypted key either: only material that’s useless without your password.
Login
You type your password again. The same OPRF dance produces the same value if you use the correct password. The server sends back your stored envelope: masked, XORed with a pad only your masking key can reproduce, which means an eavesdropper can’t tell a real account from one that doesn’t exist. Your device unmasks it, and the nonce inside feeds the same derivation as before, regenerating the identical key pair. Your device then checks the envelope’s authentication tag: if the password was right, the tag verifies and your device holds the correct private key.
The device and our server then run an authenticated key exchange using those keys, agreeing on a session key while each proves to the other that it’s legitimate. If the password was wrong, the derived keys are simply the wrong keys, the tag doesn’t verify, and nothing useful or sensitive ever crosses the wire.
Why this makes everyone saferSo, why did we decide to use this protocol? Because we wanted to give the best security we have for users using passwords. This means:
The password itself is never transmitted. No plaintext at the server means no accidental logs, no memory scraping, no insider peeking, no “we’ve discovered a subset of passwords were stored in cleartext” blog post two years from now. On-mass precomputation of passwords is dead. Because part of the derivation depends on a secret key held by the server, attackers can’t build dictionaries of passwords in advance. They have to steal the database and the server secret first, and only then start guessing: per user, from scratch, against a memory-hard function. A breach, hence, then becomes a slow, expensive, per-account per-user grind. Login isn’t the end, it’s the beginning. OPAQUE also gives the client an export key: a strong secret derived from your password that the server never learns. That’s a key you can use to encrypt data end-to-end, with nothing to manage beyond the password you already remember and know. What OPAQUE doesn’t doWhile using OPAQUE means that we are using very cool cryptography, it still has some caveats.
It doesn’t stop phishing on its own. If an attacker controls the page or app you’re typing into, they can capture the password before any protocol runs.
It doesn’t make weak passwords strong. “password123” still falls to an online guessing attack, which is why Brave Accounts rate-limits and asks for strong passwords.
After a full server compromise, a determined attacker can eventually mount an offline per-user dictionary attack. OPAQUE makes that dramatically slower and unparallelizable across users, but it doesn’t make it impossible.
Why we think this is genuinely cool and better for our usersMost security improvements are about reducing the blast radius of a mistake. OPAQUE is about removing the thing that could create that blast. But also, this is a protocol that is composable. Because OPAQUE hands back a session key and an export key, it isn’t just a login box, it’s a key-agreement primitive with a password-shaped front door. That unlocks a lot:
End-to-end encrypted storage, where the encryption key is derived from your password and never touches our infrastructure (this is roughly how WhatsApp built password-protected encrypted chat backups). Device sync and recovery, bootstrapped from something you remember rather than a code you’ll lose. We are also planning on a new version of Sync built on this, so stay tuned, as you’ll soon be able to pair Brave Sync with your Brave Account, and, hence, you will be able to forgo the current QR code pairing process and instead just log in to bring end-to-end-encrypted sync to a new device. An account-less sync option will continue to be available and fully supported, so if you don’t want an account to use our services, you can still do it!Brave Accounts serves as the foundation for our new Email Alias service, and it will support a growing number of future Brave services as well.
Getting startedBrave Accounts is available today, so try it out! You can go to brave://settings/getStarted and follow the banner in order to create an account.
You can give us feedback on the support form, GitHub, or any of our social media channels.
This is the 39th post in an ongoing series describing new privacy features in Brave. This post describes work done by Pavel Beloborodov (Sr. Software Engineer), Tarik Demirović (Sr. Automation and Infrastructure Engineer), Harold Spencer Jr. (Sr. Staff Engineer) and Agustín Ruiz (DesignOps Lead). Arthur Edelstein (ex-Brave Sr. Research and Privacy Engineer) contributed as well. It was written by Shivan Kaul Sahib (VP, Privacy and Security).
Starting with today’s desktop version 1.94, the Brave browser is offering Email Aliases to allow you to sign up for online services without revealing your personal email address. Email Aliases can keep your email free of spam, and help you protect your privacy by generating unique email addresses that forward to your primary email inbox.
How your email address can be used to track you across the WebYour email address is a durable, universal identifier. When shared with websites, it can be used for tracking your activity across the Web. Ad tech companies like Google, Meta, and LinkedIn publicly promote how businesses can upload email addresses to match customers against their own user profiles. While Brave offers best-in-class protections against third-party trackers like Meta Pixel that are embedded on websites, your data can still be shared using techniques like server-side matching.
For example, imagine you want to buy a pair of trail running shoes from amazingshoes.com, and the website asks for your email address when signing up. This by itself isn’t suspicious, since the website needs to know where to send your receipt. But amazingshoes.com also uses Meta ads, so upon receiving your address it also uploads your email address to Meta’s server-side audience-matching tool. Meta already has that exact email address on file from the Facebook account you created years ago. The two records match, and Meta now knows that you, specifically, bought expensive trail running shoes. Since it’s happening server-side, none of this traffic goes through your browser, so blocking trackers on the page can’t prevent this action.
Worse, websites vary widely in how well they protect the data they collect. If a website you signed up for is hacked, your information can be leaked and end up with data brokers or worse. Your email address then circulates far beyond the company you originally trusted with it, and can show up in phishing campaigns for years afterwards.
We built Email Aliases to plug this privacy hole. Email Aliases is integrated into Brave, which means you can generate privacy-protecting email addresses right from a website’s sign-up form. These aliases then forward to your real, primary email address, which remains hidden from websites, thus breaking the cross-website tracking link. The feature can also prevent spam, since you can easily deactivate your email alias and create a new one.
Brave already isolates what websites can store in the browser. Cookies, caches, and network state are partitioned per site, so a tracker can’t use what it stored on one site to recognize you on the next. But partitioning stops at the edge of the browser. It can’t stop two companies from comparing notes on their own servers. Email Aliases extends that same partitioning past the browser.
How to use Email Aliases Creating a Brave AccountIn order to create an email alias, you’ll first need to create a Brave account with an email address and password. Note that this account is separate from the Brave Premium account (which Premium users use for managing subscriptions to some of our services, such as the Brave VPN).
Go to brave://settings/email-aliases and click “Log in or create a Brave account” Provide your email address and a strong password Follow the instructions to verify your email Creating an alias on a websiteOnce you’re logged into your Brave account, simply click into an email field on any website to create an alias.
Right click (context menu)If the “New Email Alias” hint doesn’t appear, you can right-click the email field and select ‘New Email Alias’ to create one manually.
Managing aliasesYou can manage all your aliases by going to Settings > Autofill & Passwords > Email Aliases (or directly follow the link at brave://settings/email-aliases).
Why do I need a Brave Account to use the Email Aliases feature?Under the hood, Email Aliases uses Brave Accounts, a brand-new way of signing into Brave using an email address and password. Email Aliases considers the email address associated with your Brave Account as the primary email address, and forwards all email delivered via your aliases to that primary email address.
Brave Accounts uses OPAQUE, a recently standardized cryptographic protocol, so your password is never sent to Brave’s servers. For more information on Brave Accounts, check out our blog post: “Brave Accounts: your password never leaves your device, ever.”
What information can Brave see if I use Email Aliases?As with everything we do, Brave’s goal is to protect user privacy. Once you sign up for Email Aliases, we’ll securely store the email address associated with your Brave Account and any email aliases that you generate. All data is encrypted-at-rest. Emails sent to an alias are forwarded to your primary email address.
Brave doesn’t read the contents of emails sent to an alias. We only process emails to perform standard spam and virus filtering (we need to do this to maintain our status as a reputable email provider). Once an email is delivered, it is deleted from our servers within seconds.
If you add notes to an alias (e.g. “Throwaway account for SendMomFlowers.com”), those notes are stored locally on your device. If you turn on Brave Sync, your notes will be encrypted end-to-end (i.e. hidden even from Brave) between devices on the same Sync chain. Only you can decrypt or read these notes.
For more details, see the section for email aliases in our privacy policy and our support page.
What’s next for Email AliasesIn this initial release, we’re offering everyone the option of five free email aliases. Running a mail forwarding service has ongoing costs, so we’re starting small while we gather feedback on how people use the feature. We’re working hard to bring Email Aliases to mobile, and we plan to offer a Premium version of the feature in the future.
During this phase, some Brave-forwarded emails might go to your spam folder, as we build up our reputation score as a mail provider. If that happens, please mark the message as “not spam.” This ensures that future emails get routed correctly and improves our sending reputation. If you find that too much mail is going to spam, please let us know.
You can share feedback on the support form, GitHub, or any of our social media channels.
Note: If you’re a Brave Origin user and you opted to upgrade the existing version of Brave on your device, the Email Aliases feature will appear in the Settings panel where you can toggle features on/off. The Email Aliases feature will not appear in the version of Origin available via separate download (aka the “standalone” version).
a16z General Partners Martin Casado, Sarah Wang, and Matt Bornstein unpack the story of Cursor: how a small, product-obsessed team entered one of the most competitive markets in technology, took on incumbents with seemingly unbeatable advantages, and repeatedly made decisions that ran against conventional startup wisdom.
They revisit the early bet that the interface between humans and AI would matter more than building a coding-specific foundation model, why Cursor built its own product rather than a VS Code plugin, and how the founders' ability to say "no" became one of the company's defining strengths. They also discuss Cursor's rapid evolution from IDE to agent and model platform, and why the team was willing to cannibalize its own products as AI capabilities improved.
The conversation gets into what founders can learn from Cursor's approach to competition, hiring, enterprise sales, M&A, and company culture, including why the team remained unfazed by competitors from Microsoft to Anthropic and how its obsessive focus on product ultimately extended into every part of building the company.
Resources:
Explore Cursor Compile: https://cursor.com/compile
Follow Martin Casado on X: https://x.com/martin_casado
Follow Matt Bornstein on X: https://x.com/BornsteinMatt
Follow Sarah Wang on X: https://x.com/sarahdingwang
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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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Anish Acharya joins Jen Kha to break down the next frontier of AI, from the evolving model landscape and open-source AI to why the application layer, and consumer AI in particular, may be entering a new phase.
Anish explains why he believes there will be multiple winners at the model layer, why traditional moats like network effects, scale, and brand still matter, and how companies can choose between frontier and open-weight models depending on the economics of the task. They also explore why models are increasingly specializing, and how applications can combine different types of intelligence to create products that are more valuable than any single model.
The conversation then turns to consumer AI: personal agents that can shop and manage your inbox, coding tools enabling a new generation of small businesses, and why Anish thinks we're seeing a renaissance for consumer builders. They also discuss the changing economics of AI software, the rise of "luxury software," and why the biggest risk for today's founders may no longer be thinking too big, but thinking too small.
Stay Updated:
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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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a16z General Partners Martin Casado and Erik Torenberg are joined by Board Partner Steven Sinofsky to explore what recent breakthroughs in AI and mathematics tell us about where the technology is headed, and whether some of the basic assumptions that have governed computing for decades are starting to break.
Martin and Steven debate whether AI's progress in mathematics represents a genuine leap in reasoning or simply a new tool for solving problems at a higher level of abstraction. From the four-color theorem and early computers to graphing calculators and today's models, they trace how new technologies have repeatedly changed which problems humans need to solve themselves, and ask what makes this moment different.
The conversation then turns to one of the biggest shifts in AI: problems that were once constrained by engineering talent can increasingly be attacked with capital and compute. They discuss what that means for startups versus incumbents, venture capital, the coming wave of AI applications, and why pouring billions into increasingly capable models may force us to rethink what these systems can ultimately accomplish.
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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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Daisy Wolf and Eva Steinman are joined by Engy Ziedan, co-founder and Chief Scientific Officer of Protege, to discuss why medical AI has a measurement problem, and why scoring well on a benchmark doesn't necessarily mean a model is ready for the hospital.
Engy explains why healthcare AI needs independent evaluations that go beyond static exams and measure how models actually perform in real-world clinical workflows. They explore the risks of subtle bias and misalignment, why the same model can rank differently depending on how it's prompted or tested, and what happens as AI becomes more personalized and changes faster than traditional healthcare quality systems can keep up.
The conversation also gets into Protege's role as an independent evaluator, how contaminated training data can undermine benchmarks, and why the future of medical AI may require continuous monitoring rather than occasional testing.
Resources:
Read our insights piece: https://www.a16z.news/p/the-oracle-problem-an-invisible-bottleneck
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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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Martin Casado joins MTS hosts Theo Jaffee and Sophia Dew to unpack where value is actually accruing in AI, why this technology cycle looks fundamentally different from previous waves, and whether the frontier labs will ultimately capture most of the market.
Martin explains why AI has turned venture into a scale-up capital game, where small teams can productively deploy extraordinary amounts of money, and why the relationship between capital, innovation, and growth has never been tighter. He lays out the case both for and against the frontier labs dominating AI, the role of open-source and specialist models, and why applications are increasingly capturing more value.
The conversation also explores model routing, AI economics, founder-market fit, and why Martin believes this may be the biggest unlock of wealth he's seen since the 1990s.
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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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a16z's Joel De La Garza is joined by Aaron Zollman, Deputy CISO at Microsoft Gaming, to discuss how security teams can embrace AI agents without losing control.
Aaron shares Microsoft's experience with OpenClaw, from the initial instinct to ban it to figuring out how to make it safe to use. They unpack what agents mean for identity, permissions, containerization, and monitoring, as well as how AI is shifting the CISO's role from saying "no" to safely enabling new technology.
They also explore whether AI could help defenders patch vulnerabilities as quickly as they're discovered, and why new AI threats don't make the old security problems go away.
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The PIVX ecosystem continues to make progress across network participation, market activity, privacy-focused development, and community engagement. Here’s a look at the latest updates.
Masternode Network
The PIVX masternode network currently stands at approximately 1,888 masternodes, with an estimated annual reward of 15.43% and around 18.17% of PIVX supply locked.
Masternodes continue to play an important role in supporting network security, decentralized governance, and participation across the PIVX ecosystem.
Market Update
PIVX is currently trading around $0.0118, with continued activity from traders and holders despite broader market volatility.
24-hour trading volume is approximately $213,000, representing an increase of around 66% from the previous day. MEXC remains an active market for PIVX, with the PIVX/USDT pair among the leading trading pairs.
Ecosystem & Community
PIVX continues to expand access to $PIVX across the broader crypto ecosystem.
PIVX is available on MEXC, providing another option for users to trade PIVX alongside thousands of other digital assets, with competitive trading fees and a wide range of markets.
The PIVX Medium publication also recently featured an article examining the public reaction to destroyed traffic cameras and the broader questions surrounding surveillance, privacy, and financial freedom. The discussion reflects the importance of maintaining individual choice as technology becomes increasingly integrated into everyday life.
$PIVX is also available through ChangeNOW, giving users another option for swapping PIVX. As a Proof-of-Stake blockchain, PIVX combines staking and community governance with optional privacy through its SHIELD protocol.
Community participation remains an important part of the PIVX ecosystem. Through PIVX.org, Discord, and Telegram, community members can connect, discuss privacy and cryptocurrency, share ideas, and contribute to ongoing conversations around the future of decentralized finance.
Looking Ahead
PIVX remains focused on strengthening its network, expanding accessibility, and advancing privacy-focused technology while keeping financial freedom and user choice at the center.
These developments reinforce PIVX's position as a leading privacy-focused cryptocurrency, with growing accessibility, stronger educational outreach, and continued advocacy for financial freedom.
#PIVX Your Rights. Your Privacy. Your Choice.
PIVX Weekly Ecosystem Update was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.
Elena Burger is joined by a16z’s Angela Strange and Gabriel Vasquez to discuss the rise of the "borderless founder": entrepreneurs who bring the networks and insights of their home markets together with the talent, capital, and speed of Silicon Valley to build global companies.
Angela and Gabriel trace how a16z's international investing efforts grew from early work in Latin America into a broader global network, and why AI has accelerated the flow of founders and talent between Silicon Valley and startup ecosystems around the world. They explore the advantages borderless founders can bring, from differentiated talent networks and early customers to strong local brands and communities that help open doors across markets.
They also discuss how founder diasporas can function like powerful alumni networks, why spending time in Silicon Valley can help founders recalibrate around speed and ambition, and how the next generation of global companies may increasingly be built across multiple countries from day one.
Resources:
Read Angela Strange and Gabriel Vasquez's piece on Borderless Founders: https://www.a16z.news/p/rise-of-the-borderless-founder
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a16z General Partner David George is joined by Grant LaFontaine, co-founder of Whatnot, to unpack how a marketplace that started with collectibles evolved into one of the world's leading live shopping platforms.
Grant traces the company's origins from selling Pokémon cards online as a kid to discovering live commerce by watching Whatnot's earliest customers hack together sales on social media. They discuss why Whatnot thinks less like a traditional e-commerce marketplace and more like a digital shopping mall, where discovery, entertainment, community, and commerce all happen at once. Today, users spend roughly 95 minutes a day on the platform, and most aren't even buying something on a given day.
They also explore how Whatnot is enabling small businesses to reach global audiences, expanding from collectibles into categories like fashion, food, and golf, and using AI to make sellers more efficient without replacing the human connection at the center of the experience.
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