Web3 | Identosphere Blogcatcher

The TRON founder accused the Trump-linked DeFi project of hiding a 'trap door' in its token contract.

Cryptography-breaking quantum computers and zero-day finding AI models are signaling the end of the human-secured internet.

We track the momentum so you don’t have to. Catch the stories shaping our community every week, only in the Pulse.

Market Pulse Masternode Count: Masternode growth continues to reinforce the PIVX network. We’ve seen the active node count climb from 2,142 to 2,159 over the past seven days. Price Check: PIVX showed resilience this week as prices traded sideways, holding steady in the $0.09 zone. This represents a slight improvement over last week’s performance, mirroring tentative signs of recovery across the broader crypto market. While it may be too early to bank on a complete trend reversal, the momentum is leaning positive. Consequently, the weekly average climbed to $0.0864, a 7.2% increase from the previous week’s $0.0806. Trading Buzz: Trading metrics reflected a healthy week for PIVX, with total volume rising from $15.9 million to $17.6 million (a 10.7% increase). Daily trading remained robust, consistently holding above the $2 million benchmark, underscoring a period of renewed liquidity and buyer interest.

PIVX. Your Rights. Your Privacy. Your Choice.
To stay on top of PIVX news please visit PIVX.org and Discord.PIVX.org.

PIVX Weekly Pulse (Apr. 3rd, 2026 — Apr. 9th, 2026) was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

Agents are knowledge systems first. Local models make them more private, but security gaps loom.

The Ethereum Layer 2 network raised its L1 data cost scalars 1,280x over six days before rolling them back yesterday.

The March inflation print came in hotter than expected, but a tame core reading and easing oil prices gave risk assets room to rally.

CEO Brian Armstrong is now publicly supporting the bill after Treasury Secretary Scott Bessent called for faster crypto regulation.

The integration marks the latest expansion of Visa's stablecoin infrastructure, which now spans settlement, card spending, and direct on-ramp capabilities.

The HKMA selected two issuers from a pool of 36 applicants under the Stablecoins Ordinance, which took effect in August 2025.

The existential threats facing DeFi, the risk users are taking on, and the nascent solutions.

Donald Trump’s family-backed crypto project is dismissing recent pushback as FUD.

Storm's defense argued his work on the non-custodial mixer was lawful, while prosecutors claimed he profited from money laundering.

The DEX aggregator's $415K treasury will be transferred to the protocol's development company, along with future revenue.

The embattled DATco is considering emergency measures to remain compliant with Nasdaq's listing requirements.

The Asian city's central bank has awarded its first licenses to HSBC and a Standard Chartered-backed joint venture.

Coinbase CEO Brian Armstrong publicly supported Treasury Secretary Scott Bessent's call to pass the CLARITY Act, citing the urgency of crypto regulation.

The founder of Covenant AI announced the project's departure from Bittensor last night, kicking off public accusations from both sides, and sending the subnet ecosystem down 26%.

MoonPay, WalletConnect, and Ingenico announced a partnership to enable stablecoin payments at physical retail locations globally using MoonPay Virtual Accounts for fiat settlement.

MetaMask now supports the ERC-7715 standard, allowing agents and dApps to request execution permissions on OP Mainnet.

Securitize announced integration with TRON Network to bring tokenized assets to one of the world's largest blockchains, expanding its multichain presence.

Theo Jaffee speaks with Steven Sinofsky, board partner at a16z and former president of the Windows division at Microsoft, about Apple's 50th anniversary, the cultural differences that separated Apple and Microsoft, why the MacBook Neo puts Windows laptops in a difficult position, and what the history of computing design reveals about where hardware and software are headed.

 

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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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BTC clung to a three-week high as the Iran truce lifted risk assets, but doubts about the deal's durability capped upside.

What should a social app actually feel like? Sup is one potential answer.

Curve's FXSwap pools use frxUSD as the base dollar pairing for cross-currency swaps spanning the Brazilian real, Indonesian rupiah, British pound, Australian dollar, Korean won and USDT.

The QSB scheme uses only existing Bitcoin consensus rules, sidestepping the network's contentious upgrade process.

A Bank of Canada report offered a window into how legacy institutions see the opportunities and risks involved with DeFi investing.

Interested parties are apparently hunting for a regulatory shortcut to more easily enter European and British crypto markets.

The feature prevents compromised curator keys from redirecting depositor funds to unvetted reserves.

It is unclear whether the President will be able to physically attend the publicly touted event.

The DeFi project's treasury used 3 billion WLFI tokens as collateral on Dolomite to borrow $75 million in stablecoins over the past week.

RWA perpetuals tied to assets like gold, silver and oil, grew 40x in six months, the new report shows.

Joe "CupOJoseph" Schiarizzi is running for Congress as a Democrat in Virginia's new 7th district.

MSBT saw a strong first day of trading on Wednesday, but the broader U.S. Bitcoin ETF sector was in the red yesterday.

The DOJ and CFTC filed to enjoin Arizona's criminal and civil enforcement against prediction market platform Kalshi, arguing federally regulated event contracts fall under CFTC jurisdiction.

Yuga Labs has reached a settlement in its NFT counterfeiting lawsuit against artist Ryder Ripps and his business partner Jeremy Cahen, with parties agreeing to permanent blocks on trademark and imagery use.

Binance Wallet has integrated predict.fun prediction markets and is sponsoring all gas fees for users on BNB Smart Chain.

Canary Capital has filed registration with the SEC for a Pepe ETF, marking what appears to be the first attempt to create and ETF for the "blue-chip" memecoin in the U.S.

Eddy Lazzarin speaks with Vitalik Buterin, founder of Ethereum, and Guillaume Verdon, founder and CEO of Extropic, about whether AI progress can or should be steered, the risks of concentrated power, and what open source and decentralization mean for who benefits from increasingly powerful systems. This episode originally aired on the a16z crypto podcast. 

 

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The coolest Ethereum tools don't always come from startups with major VC backing.

Polymarket has acquired Brahma to enhance its DeFi infrastructure and trading performance capabilities.

Bitcoin touched a three-week high above $72,700 while $470 million in short positions were liquidated as geopolitical tensions eased.

The Treasury Department is preparing for stablecoins, proposing new rules to treat issuers like full-fledged financial institutions.

Visa's Intelligent Commerce platform lets AI agents shop, compare, and transact on behalf of consumers, and the company says the majority of business leaders are ready for it.

Circle Payments Network (CPN) Managed Payments let financial institutions operate in fiat, while using crypto rails behind the scenes via Circle.

Polygon is reportedly seeking to promote real-world payments use cases on its EVM blockchain with a new stablecoin startup.

On-chain AI agents are increasingly capable of reasoning through complex DeFi strategies, but ERC-8211's devs say a shared on-chain execution layer was lacking.

The EF is offloading approximately $11M worth of ether today via CoWSwap to fund R&D, grants, and donations.

Arkham Intelligence is discontinuing support for the TON blockchain on its platform effective April 8 at 12pm EST.

Tokenization firm Securitize has partnered with Nasdaq-listed Currenc Group to tokenize its ordinary shares on Ethereum and Solana blockchains.

A White House Council of Economic Advisers study released Wednesday concludes that banning stablecoin yield would have minimal impact on bank lending and would harm consumers.

The Italian Data Protection Authority recently slammed Intesa Sanpaolo with a $36 million fine, and the reason is nothing short of a privacy nightmare.

For more than two years (from February 2022 to April 2024), the private financial records of 3,573 customers were accessed without authorization. The victims included high-risk public figures, whose sensitive data was left exposed to internal prying due to what regulators called serious shortcomings in security infrastructure.

So, while they were trusting the system, a rogue employee was allegedly treating the private financial lives of customers like a personal social media feed.

Findings paint a troubling picture of the circular operating models used by major institutions. For instance, an employee could query the entire customer database with minimal oversight. Internal control systems failed to detect thousands of unauthorized intrusions for twenty-six months. And the bank allegedly failed to meet legal deadlines for notifying affected individuals, leaving customers in the dark.

Feel free to argue, but this is the reality of the modern financial world. You do not actually own your data. In the traditional system, privacy is a promise made by a corporation; a promise that can be broken by a single disgruntled or curious employee.

True financial privacy should be permissionless and cryptographic, not dependent on the technical and organizational measures of a third party that can be compromised from within. As long as our financial history remains a searchable database for bank employees, the concept of banking secrecy remains an outdated myth.

PIVX. Your Rights. Your Privacy. Your Choice.
To stay on top of PIVX news please visit PIVX.org and Discord.PIVX.org.

Your Bank is Watching: The $36M Privacy Disaster was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

The Federal Deposit Insurance Corporation a proposed rule that would establish a framework for stablecoin issuers supervised by the FDIC.

Erik Torenberg, Steve Sinofsky, and Martin Casado speak to Aaron Levie, CEO at Box, about what happens to enterprise software when agents become the primary users. They discuss why coding agents succeed where other knowledge work agents struggle, what abstraction layers mean for the workforce, and how data access and systems of record must change in an agent-first world.

 

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Spot Bitcoin ETFs recorded their strongest daily inflows since February on Monday despite ongoing geopolitical tensions.

An analysis of Morpho markets finds depositors are undercompensated by 5-10x. Curators counter that empirical loss data tells a different story.

The banking regulator's Board of Directors has proposed a new framework for stablecoins under the GENIUS Act.

Sky Governance is proposing a stronger solvency buffer and a more sustainable staking rewards model to solidify long-term protocol stability.

The shock hack and unimpeded fallout is leaving plenty in the industry pointing fingers at the USDC issuer.

The crypto exchange will implement its "Spot Price Range Execution Rule" beginning April 14.

It will be the first BTC ETF launched by a major U.S. commercial bank.

The AAVE token has lost roughly 75% of its value since its most recent peak in August 2025.

MSBT will launch tomorrow as the lowest-fee Bitcoin ETF on the market, potentially kicking off a fee war among funds.

Publish lets you sell digital work directly to humans or AI agents, just price and deploy.

Starting next week, taker orders on Binance that breach dynamic price corridors will be automatically canceled.

The new tool from the Solana-based DEX aggregator lets DEXs, launchpads, and AI agents build verification into their token creation flows.

The collateral and liquidity focused fintech is also building a node-as-a-service on Canton, which is known as an institution-focused blockchain platform.

CME Group expanded is looking to expand its crypto derivatives offerings with new futures contracts for Avalanche and Sui, pending regulatory approval.

US-listed spot bitcoin ETFs posted their strongest day since late February with $471.32 million in net inflows on April 6.

Security researcher Taylor Monahan claims North Korean IT workers have infiltrated more than 40 decentralized finance platforms, with the $280 million Drift Protocol exploit last week being the latest operation tied to the network.

The Polygon Foundation confirmed the Giugliano hardfork will activate on mainnet at block 85,268,500 on April 8 at approximately 2 p.m. UTC.

Ethereum's stablecoin supply reached an all-time high of $180 billion, representing 150% growth over three years and 60% of the total stablecoin market.

a16z general partner Erik Torenberg speaks with Balaji Srinivasan, angel investor and entrepreneur, about why AI simultaneously reduces the cost of creation and increases the cost of verification, and what that tension means for the shape of the AI economy. They discuss why AI drives companies toward the "trusted tribe" model of the Chinese internet, why physical world tasks are easier to automate than digital ones, why shortcuts only work for experts, and why AI makes everyone a CEO rather than making CEOs obsolete.

 

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Solana Foundation unveiled STRIDE, a comprehensive security evaluation program for DeFi protocols, alongside SIRN, a membership-based incident response network with five founding security firms.

Tom Lee continues growing his ETH stack, scooping up over 71k coins last week as his DAT approaches 4% of outstanding supply.

JPMorgan says the tokenized real-world assets market could grow to $13 trillion by 2030.

USDe may soon include institutional loans, private credit, and cross-market basis strategies.

Five takeaways from our podcast interview with Nic Carter on Bitcoin's quantum timeline.

The prediction market giant can continue to offer sports-related event contracts in New Jersey while it defends such contracts in court.

BlackRock's BUIDL token on Ethereum has exceeded $1 billion in market capitalization, up approximately 115% year-to-date.

A 45-day ceasefire plan and Strategy's $330M Bitcoin purchase buoyed crypto markets.

The changes will result in lower gas fees and faster transaction speeds for Polymarket's users.

The perpetuals exchange will use World Liberty Financial's stablecoin as the sole settlement asset for its commodity markets, starting with gold, silver, and crude oil.

On-chain researcher Andrey Sergeenkov found that only 2% of the 2.5 million wallets analyzed have ever made over $1,000.

Aave's primary risk manager just terminated its engagement with crypto's largest lending market.

Polymarket USD replaces bridged USDC as part of an exchange-wide upgrade.

The risk management provider exits after three years, marking the third departure of a core contributor in two months.

The synthetic dollar protocol is moving beyond its crypto basis trade roots into institutional lending, real-world credit, and equity and commodity perpetuals.

Anish Acharya speaks with Peter Yang, creator and product lead at Roblox, about how personal AI agents are replacing the apps we open every day, why coding agents feel like slot machines, and what happens when the cost of building software drops to near zero. They discuss why future companies will stay radically small, how the IDE is becoming a thinking tool rather than a making tool, and why human ambition will always create more jobs than AI eliminates.

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The ETH treasury company posted its largest weekly purchase since December, and will begin trading on the main NYSE board on Thursday.

In a Proof of Stake (PoS) network like PIVX, the blockchain is secured by people who “stake” their coins. Think of it like a high-yield savings account. By holding and locking your coins, you help verify transactions, and in return, the network pays you interest in the form of new coins.

In this beginner’s guide, I’ll walk you through how you can start earning passive income by staking on the PIVX network.

What is Cold Staking?

Cold Staking is a way to earn rewards for securing a blockchain while your actual coins remain offline.

In traditional “hot” staking, your wallet must be open and connected to the internet 24/7 because the computer needs access to your private keys to sign new blocks. This is a security risk because your funds become vulnerable if your computer is hacked.

Cold staking solves this by splitting the “power” of your coins into two separate keys, the spending key (cold) and the staking key (hot). The spending key stays on your hardware wallet or an offline computer. It is the only key that can move or spend your money. The staking key, on the other hand, allows you to delegate your coins to an online computer or hot node. This node stays online to do the technical work of securing the network, but it has zero authority to touch your funds.

PIVX allows you to delegate your staking rights without giving up ownership.

The Delegation Process

As a beginner, you can start staking on either the PIVX Core Wallet or the MyPIVXWallet (MPW). I personally recommend MPW due to its ease of use. MPW acts as a “light” interface that can connect to your hardware wallet or a web-based seed.

PIVX Core Wallet Generate a Staking Address: You get a special address from the Hot Node (the staker).

2. Create a Delegation: In your Cold Wallet, you send a transaction to yourself using that staking address. This “locks” the coins into a cold staking contract.

3. Network Validation: The PIVX network sees that your coins are assigned to that Hot Node. The Hot Node then begins competing for block rewards on your behalf.

4. Reward Distribution: When the Hot Node wins a block, the reward is automatically sent directly to your Cold Wallet

MyPIVXWallet Access Your Wallet: Go to MyPIVXWallet.org (ensure you are using the official URL).

2. Navigate to the Staking Tab: On the main dashboard, look for the “Staking” bar. MPW has a dedicated interface designed to make delegation simple.

3. Stake Your Funds: Click on the “Stake” button. A pop-up tab will appear where you can specify the amount of PIV you’d like to stake. Click on stake, and you are good to go. Wait for the network to confirm your transaction and start earning rewards. Confirmation typically takes less than 1 hour.

Pro Tips

Technically, you can stake as low as 1 PIV. The network does not prevent you from delegating a single coin; however, doing so is generally not recommended.

Because PIVX uses a weight-based system, your chance of winning a block is directly proportional to the number of coins you have delegated. Staking just 1 PIV is like having a single ticket in a global lottery with millions of entries. It could take years, or even forever, to actually secure a reward.

The PIVX network generates a new block approximately every 60 seconds. For every block successfully confirmed, stakers are rewarded with 4 PIV. The remaining portion of the block reward goes to masternodes.

One of the best features of staking on MPW is that your rewards (those 4 PIV payments) are sent directly back to your “Owner Address.” This means they are automatically added to your total staking balance. Over time, this compounds your stake, increasing your weight and your chances of winning future blocks without you having to lift a finger.

For those starting with a smaller amount, the best strategy is to be patient or continue adding to your balance to “beef up” your weight and reduce the time between those 4 PIV rewards.

PIVX. Your Rights. Your Privacy. Your Choice.
To stay on top of PIVX news please visit PIVX.org and Discord.PIVX.org.

The Beginner’s Guide to Cold Staking was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

The Linux Foundation now officially houses x402 as agentic commerce grows at hyperspeed.

Safe launched a decentralized validator network that blocks malicious transactions before they execute. Here's how it works and why it matters.

The lottery hasn't changed in 50 years. Megapot is fixing that and letting anyone be the house.

Anonymous onchain sleuth ZachXBT notes $420M+ in alleged compliance failures by the USDC issuer since 2022.

This episode originally aired on the Latent Space Podcast. swyx and Alessio Fanelli speak with Marc Andreessen about the arc of AI from its origins in 1943 to today's breakthroughs in reasoning, coding agents, and self-improvement. They cover the parallels between AI scaling laws and Moore's Law, the architectural insight behind Claude Code and the Unix shell, the coming supply crunch in compute, and why the messy reality of 8 billion people means both AI utopians and doomers are too optimistic about the pace of change.

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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 International Monetary Fund also warns that the distribution and speed of on-chain transactions bring new challenges and risks that require international coordination.

Hyperliquid quietly dropped a mobile app for Android yesterday, which has already received 500 downloads.

The achievement marks a significant milestone in Coinbase's pursuit of regulatory clarity, but does not come unopposed.

Coinbase got conditional approval from the OCC for its trust, a step toward federal oversight for its offerings to replace the current state by state licensing approach.

Nasdaq-listed Bitcoin miner Riot Platforms sold 3,778 BTC in the first quarter of 2026, generating roughly $289.5 million in net proceeds.

Your weekly briefing on market momentum and the stories shaping the industry; only in the Pulse.

Market Pulse Masternode Count: The PIVX network continues to strengthen as masternode metrics trend upward. We’ve seen 32 new masternodes come online over the last seven days, bringing the total count from 2,109 to 2,141 active nodes. Price Check: PIVX briefly lost its support this week as the Daily USD Value dipped into the $0.08 zone. This downward pressure wasn’t isolated; the broader crypto market plummeted in response to the escalating US-Iran-Israel conflict. Consequently, the weekly average plunged to $0.0806, marking a 9.64% decrease from the previous week’s $0.0892. Trading Buzz: Activity held steady as PIVX continues to show resilience. Total weekly volume fell slightly to $15.9 million, down from last week’s $16 million. Although daily activity momentarily slipped under the $2 million mark, the overall sideways movement indicates that investor interest in the privacy coin remains firm despite the downward price pressure.

PIVX. Your Rights. Your Privacy. Your Choice.
To stay on top of PIVX news please visit PIVX.org and Discord.PIVX.org.

PIVX Weekly Pulse (Mar. 27th, 2026 — Apr. 2nd, 2026) was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

Polymarket Journalism Tools is now available, a free suite of tools for writers and researchers using prediction market data.

Innovations like the Ethereum Economic Zone and EIP-8141 are about to change everything around NFTs.

April showers bring May flowers - an important reminder for hunting airdrops.

Bitcoin fell below $67,000, and Ether dropped over 4% as oil surged on renewed geopolitical tensions.

The partnership brings leveraged derivatives to one of crypto's largest consumer distribution channels, targeting emerging-market users priced out of traditional brokerages.

OpenAI declined to disclose the terms of the transaction, but maintained that TBPB will retain its editorial independence.

The derivatives regulator just sued Arizona, Connecticut, and Illinois, asserting that states have no authority to regulate federally registered markets.

The stablecoin issuer's latest offering will be backed 1:1 by BTC, with reserves be readily and independently verifiable onchain.

The open standard for embedding payments into HTTP interactions aims to become the settlement layer for AI agent commerce, with over 20 founding members spanning tech, payments and crypto.

The integration launches with more than a dozen U.S. stocks, major equity indices, and commodity contracts resolved using Pyth's real-time price data.

Kraken introduces rewards up to 1% for users holding xStocks, extending yield opportunities beyond traditional dividend structures.

Ethereum's share of non-USD stablecoin supply has fallen from 90% in early 2023 to 65% as of February 2026, though it remains the primary issuance chain.

SoFi, a nationally chartered bank with 13.7M members and $50B+ in assets, launched an enterprise banking platform combining fiat and stablecoin services on Solana with 24/7 payment support.

Paradigm is building a prediction markets trading terminal aimed at professional traders and market makers, with partner Arjun Balaji leading the effort since late 2025.

a16z's Ben Horowitz and Erik Torenberg speak with Alex Blania, cofounder and CEO of Tools for Humanity, World, and cofounder of Merge Labs. World is building the largest real human network, a proof-of-human layer for the AI era. They cover the technical challenge of proving human uniqueness at scale using iris biometrics, the privacy architecture behind World ID, and why platforms from social networks to dating apps to video conferencing will soon require proof of human verification.

 

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Crypto markets rose as oil prices retreated under $100 a barrel on growing expectations that the conflict could wind down within weeks.

Ten foreign nationals across four firms have been charged with orchestrating pump-and-dump schemes.

Onchain data shows more than a dozen asset types drained from the Solana perp DEX's main vault address in a rapid burst of transactions.

Shares in the European digital asset manager began trading on Nasdaq under the ticker symbol CSHR earlier today.

Citadel's "EDX Markets" is vying to become crypto’s next regulated powerhouse, applying with the OCC for a national trust bank charter.

Whop's new Treasury product is taking its creator economy marketplace onchain.

Another Strategy BTC buy is likely already underway, with confirmation expected in next Monday’s announcement.

The $1.7 trillion asset manager will absorb the 250 Digital team and all liquid crypto strategies previously managed by CoinFund, targeting pensions and sovereign wealth funds.

The unaudited financials recorded $85.8M of total assets at year-end 2025, and are expected to be revised for Q1 2026 to include the impacts of UNIfication.

As crypto enters its institutional era, we're redefining what it means to go bankless. 

Solana's non-USD stablecoin adoption surged nearly threefold in the past year, driven by EURC and BRZ growth alongside institutional integrations from Visa, Stripe, PayPal, Mastercard, and Western Union.

Under the banner of complying with the UK’s Online Safety Act, Apple now requires users to prove they are over 18 to access certain services or features.

Apple’s latest iOS 26.4 release introduces a feature that compels UK users to verify their age to use some features. While the tech giant claims some users can be verified automatically based on account longevity, many are being met with a hard digital wall: provide a credit card or scan a government-issued ID, or lose access to your device’s full capabilities.

Two Sides of a Coin

Privacy advocates, including groups like Big Brother Watch, have not minced words, labelling the update as a form of identity ransomware. In reality, Apple has moved age verification from the website level to the operating system level.

Previously, if a user wanted to visit an adult website, that specific site might ask for proof of age. Now, the iPhone itself acts as the primary filter. If you do not volunteer your sensitive ID documents or credit card details to Apple, the device automatically triggers a child-safe mode.

While Apple has long marketed itself as a champion of privacy, this move is seen by many as crossing the Rubicon. By centralizing age verification at the OS level, Apple is creating a durable, permanent link between a user’s physical identity (via passport or driving license) and their digital activity.

To be fair, the move has its supporters. UK regulator Ofcom welcomed the change as a “real win for families,” arguing that it keeps young people away from harmful content more effectively than easily bypassed website-level pop-ups. From a parental perspective, having a device that is “safe by default” reduces the burden of manual monitoring.

However, the question remains: at what cost? By turning the iPhone into a mandatory ID checkpoint, Apple may be solving a safety problem by creating a much larger privacy catastrophe.

The Problem of Centralized Surveillance

When identity is verified at the system level, the device effectively carries a verified adult token that can be shared across apps. While this is convenient, it eliminates the friction that once protected anonymity.

If the OS knows exactly who you are, the potential for that data to be misused, either by future policy changes, government subpoenas, or sophisticated hacks, increases exponentially. You are no longer an anonymous user; you are a verified citizen whose every digital interaction is tied to a government ID.

In my opinion, Apple’s decision has set a global precedent. Once the infrastructure for OS-level identity verification is built and deployed in one major market, it becomes trivial to roll it out elsewhere.

What starts as “protecting the children” in London could quickly become a tool for “identity-linked browsing” in any region that demands it.

PIVX. Your Rights. Your Privacy. Your Choice.
To stay on top of PIVX news please visit PIVX.org and Discord.PIVX.org.

Apple’s UK Age Verification and the End of Digital Anonymity was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

Caltech researchers estimate a working quantum computer could be operational before 2030 using far fewer qubits than previously thought, as crypto industry assesses vulnerability exposure.

Changpeng Zhao addressed quantum computing concerns, stating the crypto industry can upgrade to quantum-resistant algorithms to mitigate threats.

David Haber speaks with Owen Jennings, executive officer and business lead at Block, about how the company rebuilt itself around AI agents, small squads, and internal tools like Goose and Builder Bot after restructuring more than 40% of its workforce. They discuss what it took to execute a major restructuring, how teams of three are now doing what teams of 14 used to, and how Block is shipping AI-native products like Money Bot and Manager Bot that generate custom interfaces on the fly for tens of millions of users.

 

Resources:

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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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Square is waiving processing fees for Bitcoin payments at US merchants for two years, with instant dollar conversion to reduce adoption barriers.

New Hampshire's Bitcoin-backed municipal bond receives Ba2 rating from Moody's, marking the first instance of a public finance instrument backed by cryptocurrency.

OpenClaw’s explosive adoption confirms Brave as the go-to Web search for the agentic future

Brave Search API has crossed a major milestone: nearly 700,000 OpenClaw users have now signed up to use the Brave Search API, and integrate the service as their agent’s primary Web search tool. This surge cements Brave as the preferred API for the fast-growing OpenClaw ecosystem, the leading open-source platform for building autonomous AI agents, which now operates under a foundation supported by OpenAI. It also signals the accelerating shift toward machine-driven search that is fundamentally reshaping the internet.

OpenClaw, with its massive community traction (evidenced by rapid GitHub growth and widespread developer enthusiasm), lists the Brave Search API as a search tool of choice to enable real-time Web access in AI agents, and Brave Search was the first provider integrated into OpenClaw. Developers have praised Brave’s independent index, strong privacy protections, reduced SEO noise, and seamless optimization for RAG (Retrieval-Augmented Generation) and agent workflows.

This milestone arrives as AI agents are emerging to dominate both personal and professional tasks like scheduling, research, automation, browser navigation, form-filling, and dynamic decision-making—all of which demand reliable, full-scale Web search. Brave uniquely delivers this through its truly independent search capabilities, empowering agents to operate securely and effectively without Big Tech dependencies.

Some analysts show machine search overtaking human-initiated queries in volume in the near future, a change fueled by the proliferation of AI. This trend will intensify exponentially with embodied agents like Tesla’s Optimus robots relying on Web data for real-time awareness and planning. Soon, the average queries per day per entity—human or machine—will dwarf the old human benchmark of roughly 2.5 daily Google searches, potentially scaling to hundreds or thousands per day per active agent.

In this new era, access to a comprehensive, independent Web search index becomes strategically essential. Only three major search providers remain viable at scale: Google, Microsoft Bing, and Brave. With Google limiting API availability and Bing phasing out its API, Brave stands out as the only alternative fueling the agent revolution. It also happens to be the best option.

To wit: In a recent internal evaluation of major AI search engines, Ask Brave (powered by Brave’s LLM Context API and open-weights Qwen3) outperformed ChatGPT, Perplexity, and Google AI Mode. While the AI industry has emphasized the importance and value of high-end models, Brave’s testing shows that less powerful open-weights models can outperform closed frontier models if they incorporate high-quality grounding data. This data is available to AI app makers and agent projects like OpenClaw via the LLM Context API.

OpenClaw’s embrace of Brave is now backed by nearly 700,000 integrated users, positioning both projects at the forefront of this transformation, where machines don’t just query the Web…they live on it.

How to use the Brave Search API with OpenClaw

If you’d like to try using the Brave Search API with OpenClaw, check out our step-by-step guide.

Note that (as with any AI agent) there are ongoing security risks with OpenClaw. If you plan to use it, you should follow the best-practices recommendations in our guide, including running OpenClaw on a dedicated machine or VM that has restricted access to sensitive data. You should also set usage limits for the Brave Search API.

About Brave Search and the Brave Search API

Brave Search is the default search engine for most of the Brave browser’s 110 million users; it’s also available as a private, high-quality alternative in any browser at search.brave.com. Brave Search is the third-largest global independent search engine, with an index of 40 billion webpages that handles over 2 billion monthly queries across the API and end-user search.

The Brave Search API helps anyone access this high-quality index for their AI and search projects. With the Brave Search API, customers can supply their AI LLMs with real-time data, power agentic search, train foundational models, and create search-enabled software. Any AI application can benefit from having access to the Web, ensuring the otherwise static knowledge of AI models is constantly refreshed.

If you’re not yet a Brave Search API customer, the API is available now with low-cost monthly subscriptions and a monthly credit system that makes the API free for trials and ongoing, small-scale projects.

→ Sign up and make your first API call today
→ Contact us to learn more about bespoke plans

It marks the GENIUS Act-compliant stablecoin's first expansion beyond the Ethereum L1.

The DeFi giant's next iteration goes live.

Innovations like the Ethereum Economic Zone and EIP-8141 are about to change everything around NFTs.

Earlier this month, five regional banks partnered with ZKsync to launch the Cari network; here's why.

Coinbase's Layer 2 shifts focus to tokenizing every major asset class and scaling stablecoin payments.

Ivan Kozlov shared the first public update on recovery efforts nine days after an attacker minted 80 million unbacked USR tokens and extracted roughly $23 million.

The tech giant's quantum and AI team also released a new research paper about threats posed to cryptographic encryption schemes.

The a16z-backed privacy chain goes live with private smart contracts, but warns users of known critical vulnerabilities as audits continue.

Employees can elect to receive a portion of their salary in shares of WTGXX, earning yield from the day compensation is paid.

A whitepaper co-authored with the Ethereum Foundation and Stanford researchers slashes qubit estimates by 20x, warns that billions in crypto assets are exposed to multiple attack vectors.

From Hierarchy to Intelligence

By Jack Dorsey and Roelof Botha Published March 31, 2026

At Sequoia, we see that speed is the best predictor of start-up success. Most companies are focused on AI as a productivity enhancer. Few are focused on the potential of AI to change how we work together. Block is showing what it looks like to fundamentally rethink organization design, ultimately harnessing AI to increase speed as a compounding competitive advantage.

Two thousand years before the first corporate org chart, the Roman Army solved a problem that every large organization still faces: how do you coordinate thousands of people across vast distances with limited communication?

Their answer was a nested hierarchy with a consistent span of control at every level. The smallest unit was the contubernium, eight soldiers who shared a tent, equipment, and a mule, led by a decanus. Ten contubernia formed a century of eighty men under a centurion. Six centuries made a cohort. Ten cohorts made a legion of roughly 5,000. At each layer, a named commander held defined authority, aggregated information from below, and relayed decisions from above. The structure (8 → 80 → 480 → 5,000) was an information routing protocol built around a simple human limitation: a leader can effectively manage somewhere between three and eight people. The Romans discovered this through centuries of warfare. Even today, the US Army’s hierarchical chain follows a similar pattern. We now call it “span of control,” and it remains the governing constraint of every large organization on earth.

The next big change came from Prussia. After Napoleon’s army destroyed the Prussian forces at the Battle of Jena in 1806, a group of reformers led by Scharnhorst and Gneisenau rebuilt the military around an uncomfortable truth: you cannot depend on individual genius at the top. You need a system. They created the General Staff, a dedicated class of trained officers whose job was not to fight but to plan operations, process information, and coordinate across units. Scharnhorst intended these staff officers to “support incompetent Generals, providing the talents that might otherwise be wanting among leaders and commanders.” This was middle management before the term existed. Professionals whose purpose was to route information, pre-compute decisions, and maintain alignment across a complex organization. The military also formalized the distinction between “line” and “staff” functions. Line advances the core mission. Staff provides specialized support. Every corporation still uses this vocabulary today.

Military hierarchy entered the business world through the American railroads in the 1840s and 1850s. The U.S. Army lent West Point-trained engineers to private railroad companies, and these officers brought military organizational thinking with them. Staff and line hierarchies, divisional structure, bureaucratic systems of reporting and control: all of it was developed in the military before the railroads adopted it. In the mid-1850s, Daniel McCallum of the New York and Erie Railroad created the world’s first organizational chart to manage a system stretching over 500 miles with thousands of workers. The informal management styles that worked for smaller railroads were failing. Train collisions were killing people. McCallum’s chart formalized the same hierarchical logic the Romans had used: layers of authority, defined reporting lines, structured information flow. It became the blueprint for the modern corporation.

Frederick Taylor (1856-1915), often called the “Father of Scientific Management,” optimized what happened within that hierarchy. Taylor broke work into specialized tasks, assigned them to trained experts, and managed through measurement rather than intuition. This produced the functional pyramid organization – a structure optimized for efficiency within the information routing system that the military had pioneered and the railroads had commercialized.

The first real stress test of functional hierarchy came during World War II. The Manhattan Project required physicists, chemists, engineers, metallurgists, and military officers to work across disciplinary boundaries toward a single objective under extreme secrecy and time pressure. Robert Oppenheimer organized Los Alamos into functional divisions but insisted on open collaboration across them, resisting the military’s instinct to compartmentalize. When the implosion problem became critical in 1944, he reorganized the lab around it, creating cross-functional teams unlike anything in corporate America at the time. It worked, but it was a wartime exception led by a singular figure. The question the postwar business world faced was whether that kind of cross-functional coordination could be made routine.

With the growth and globalization of companies after World War II, the scale limitations of functional design became acute. In 1959, McKinsey’s Gilbert Clee and Alfred di Scipio published “Creating a World Enterprise” in the Harvard Business Review, providing an intellectual framework for a matrix organization that combined functional specialties with divisional units. Under the leadership of Marvin Bower, McKinsey helped companies like Shell and GE implement these principles, balancing central standards with local agility. This became the “professional” or “modern” corporation that propelled the postwar global economy.

Over time, other frameworks emerged to address the complexity, rigidity, and bureaucracy of matrix structures. The McKinsey 7-S framework, developed in the late 1970s by Tom Peters and Robert Waterman, distinguished the “hard Ss” (Strategy, Structure, Systems) from the “soft Ss” (Shared Values, Skills, Staff, Style). The core idea was that structural elements alone were insufficient. Organizational effectiveness required alignment across cultural traits and the human factors that determine whether a strategy actually succeeds.

In more recent decades, technology companies have experimented aggressively with organization structure. Spotify popularized cross-functional squads with short sprint cycles. Zappos attempted Holacracy, eliminating management titles entirely. Valve operated with a flat structure and no formal hierarchy. Each of these experiments revealed something about the limitations of traditional hierarchy, but none solved the underlying problem. Spotify moved back toward conventional management as it scaled. Zappos saw significant attrition. Valve’s model proved difficult to scale beyond a few hundred people. As organizations grow into the thousands, they revert to hierarchical coordination because no alternative information routing mechanism has been powerful enough to replace it.

The constraint is the same one the Romans faced and the Marine Corps rediscovered in World War II: narrowing span of control means adding layers of command, but more layers mean slower information flow. Two thousand years of organizational innovation has been an attempt to work around this tradeoff without breaking it.

So what’s different now?

At Block, we’re questioning the underlying assumption: that organizations have to be hierarchically organized with humans as the coordination mechanism. Instead, we intend to replace what the hierarchy does. Most companies using AI today are giving everyone a copilot, which makes the existing structure work slightly better without changing it. We’re after something different: a company built as an intelligence (or mini-AGI).

We are not the first to try to move beyond traditional hierarchy. Haier’s rendanheyi model, platform organizations, “data-driven” management: these are real attempts at the same problem. What they lacked was a technology capable of actually performing the coordination functions that hierarchy exists to provide. AI is that technology. For the first time, a system can maintain a continuously updated model of an entire business and use it to coordinate work in ways that previously required humans relaying information through layers of management.

For this to work, a company needs two things: a kind of “world model” of its own operations, and a customer signal rich enough to make that model useful.

Block is remote-first. Everything we do creates artifacts. Decisions, discussions, code, designs, plans, problems, and progress all exist as recorded actions. It’s the raw material for a company world model. In a traditional company, a manager’s job is to know what’s happening across their team and relay that context up and down the chain. In a remote-first company where work is already machine-readable, AI can build and maintain that picture continuously. What’s being built, what’s blocked, where resources are allocated, what’s working and what isn’t. That’s the information the hierarchy used to carry. The company world model carries it instead.

But the capability of the system is only as good as the quality of the customer signal feeding it. And money is the most honest signal in the world.

People lie on surveys. They ignore ads. They abandon carts. But when they spend, save, send, borrow, or repay, that’s the truth. Every transaction is a fact about someone’s life. Block sees both sides of millions of these transactions every day, the buyer through Cash App and the seller through Square, plus the operational data from running the merchant’s business. That gives the customer world model something rare: a per-customer, per-merchant understanding of financial reality built from honest signal that compounds. The richer the signal, the better the model. The better the model, the more transactions. The more transactions, the richer the signal.

Together, the company world model and the customer world model form the foundation for a different kind of company. Instead of product teams building predetermined roadmaps, you build four things.

First, capabilities. The atomic financial primitives: payments, lending, card issuance, banking, buy-now-pay-later, payroll, and so on. These are not products. They are building blocks that are hard to acquire and maintain (some have network effects and regulatory permission). They have no UIs of their own. They have reliability, compliance, and performance targets.

Second, a world model. This has two sides. The company world model is how the company understands itself and its own operations, performance, and priorities, replacing the information that used to flow through layers of management. The customer world model is the per-customer, per-merchant, per-market representation built from proprietary transaction data. It starts with raw transaction data today and evolves toward full causal and predictive models over time.

Third, an intelligence layer. This is what composes capabilities into solutions for specific customers at specific moments and delivers them proactively. A restaurant’s cash flow is tightening ahead of a seasonal dip the model has seen before. The intelligence layer composes a short-term loan from the lending capability, adjusts the repayment schedule using the payments capability, and surfaces it to the merchant before they even think to look for financing. A Cash App user’s spending pattern shifts in a way the model associates with a move to a new city. The intelligence layer composes a new direct deposit setup, a Cash App Card with boosted categories for their new neighborhood, and a savings goal calibrated to their updated income. No product manager decided to build either solution. The capabilities existed. The intelligence layer recognized the moment and composed them.

Fourth, interfaces (hardware and software). Square, Cash App, Afterpay, TIDAL, bitkey, proto. These are delivery surfaces through which the intelligence layer delivers composed solutions. They are important, but they are not where the value is created. The value is in the model and the intelligence.

When the intelligence layer tries to compose a solution and can’t because the capability doesn’t exist, that failure signal is the future roadmap. The traditional roadmap, where product managers hypothesize about what to build next, is any company’s ultimate limiting factor. In this model, customer reality generates the backlog directly.

If this is what the company builds, then the question becomes: what do the people do?

The org structure follows from this, and it inverts the traditional picture. In a conventional company, the intelligence is spread throughout the people and the hierarchy routes it. In this model, the intelligence lives in the system. The people are on the edge. The edge is where the action is.

The edge is where the intelligence makes contact with reality. People reach into places the model can’t go yet. They sense things the model can’t perceive: intuition, opinionated direction, cultural context, trust dynamics, the feeling in a room. They make the calls the model shouldn’t make on its own, especially ethical decisions, novel situations, and high-stakes moments where the cost of being wrong is existential. A world model that can’t touch the world is just a database. But the edge doesn’t need layers of management to coordinate it. The world model gives every person at the edge the context they need to act without waiting for information to travel up and down a chain of command.

In practice, this means we normalize down to three roles.

Individual contributors (ICs) who build and operate capabilities, the model, the intelligence layer, and the interfaces. They are deep specialists and experts in a specific layer of the system. The world model provides the context that a manager used to provide, so ICs can make decisions about their layer without waiting to be told what to do.

Directly Responsible Individuals (DRI) who own specific cross-cutting problems or opportunities and customer outcomes. A DRI might own the problem of merchant churn in a specific segment for 90 days, with full authority to pull resources from the world model team, the lending capability team, and the interface team as needed. DRIs may persist on certain problems or move elsewhere to solve new ones.

Player-coaches who combine building with developing people. They replace the traditional manager whose primary job was information routing. A player-coach still writes code or builds models or designs interfaces. They also invest in the growth of the people around them. They don’t spend their days in status meetings, alignment sessions, and priority negotiations. The world model handles alignment. The DRI structure handles strategy and priority. The player-coach handles craft and people.

There is no need for a permanent middle management layer. Everything else the old hierarchy did, the system coordinates, and everyone is empowered, with a role that’s much closer to the work and the customer.

Block is in the early stages of this transition. It will be a difficult one, and parts of it will likely break before they work. We’re writing about it now because we believe every company will eventually need to confront the same question we did: what does your company understand that is genuinely hard to understand, and is that understanding getting deeper every day?

If the answer is nothing, AI is just a cost optimization story. You cut headcount, improve margins for a few quarters, and eventually get absorbed by something smarter. If the answer is deep, AI doesn’t augment your company. It reveals what your company actually is.

Block’s answer is the economic graph: millions of merchants and consumers, both sides of every transaction, financial behavior observed in real time. That understanding compounds every second the system operates. We believe the pattern behind this, a company organized as an intelligence rather than a hierarchy, is significant enough that it will reshape how companies of all kinds operate over the coming years. Block is far enough along to show the idea is more than theory (though, we welcome debate and feedback to pressure test and improve our ideas).

Companies move fast or slow based on information flow. Hierarchy and middle management impede information flow. For two thousand years, from the Roman contubernium to today’s global enterprises, we have had no real alternative. Eight soldiers sharing a tent needed a decanus. Eighty men needed a centurion. Five thousand needed a legate. The question was never whether you needed layers. The question was whether humans were the only option for what those layers do. They aren’t anymore. Block is building what comes next.

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The post From Hierarchy to Intelligence appeared first on Sequoia Capital.

a16z general partners Erin Price-Wright and Erik Torenberg speak with Doug Bernauer, founder and CEO of Radiant, and Drew Baglino, founder and CEO of Heron, about rebuilding American energy infrastructure. They discuss portable micro nuclear reactors, solid state power electronics, why delivery rather than generation is the real bottleneck, the case for modular manufacturing, and whether data centers are actually good for the grid.

 

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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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ETH gained 2% as BitMine extended its buying streak.

Ethereum's liquidity fragmentation problem might not be an issue for much longer.

The bill would create a voluntary certification program, establish federal supports for hardware manufacturers, and codify the Strategic Bitcoin Reserve.

The DeFi curator says existing deposits and smart contracts are unaffected, but asked users to avoid the platform until the front-end is restored.

In this episode, host Friederike Ernst is joined by Alex Svanevik, CEO of Nansen, to explore the platform's radical pivot from passive on-chain analytics to active, AI-driven agentic trading. Alex unpacks the technical hurdles of labeling over 500 million addresses, the transition from raw data into harmonized insights, and why true alpha now lies in attribution rather than raw data . He explains how Nansen uses ClickHouse databases and a mix of algorithmic heuristics, agentic teams, and human specialists to maintain the highest industry precision.

The conversation dives deep into the intersection of LLMs and blockchain, exploring how standard AI models lack domain-specific common sense and why Nansen augments them with real-time data and visual "artifacts". Alex introduces "Nansen Gym," a simulated historical replay environment for training trading agents and teases the upcoming release of "Smart Money 2.0", which aims to predict future profitable addresses with 2-3x uplift on precision. Finally, they discuss the existential risks of AI, the striking parallels between open-source AI and early DeFi, and why Alex believes agentic trading will be the absolute default by 2028.

Chapters

00:00 Intro & Context 04:15 Nansen's Evolution & Agentic Trading 09:30 Harmonizing Data & The Attribution Layer 15:00 Deterministic vs. Inferred Labeling (Uniswap vs. Binance) 21:45 Evaluating AI Agents: LLMs as Judges 27:10 User Privacy & Public Blockchain Realities 35:20 Building a Unified Trading OS 42:15 Smart Money 2.0: Predicting Which Wallets Win 49:00 The Limitations of Vanilla LLMs in Crypto 55:30 Nansen Gym & Time-Traveling AI Agents 59:45 The Open Source AI vs. DeFi Parallel

Links

Alex Svanevik on X: https://x.com/ASvanevik Nansen: https://www.nansen.ai/ NEAR: https://near.ai/

Sponsors:

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.

The federal derivatives regulator will "defer to leagues" when determining which sports event contracts are vulnerable to manipulation.

The ex-Blackstone team wants to move beyond crypto-collateralized loans and into ‘real economy credit’ as the tokenized RWA sector continues to grow.

The next generation of Aave's blockchain-based lending markets has finally arrived.

Built by Tezos R&D hub Trilitech, the new web app brings tokenized rare earth metals on-chain alongside gold and uranium as AI-driven industrial demand intensifies.

This episode originally aired on The Twenty Minute VC with Harry Stebbings. Marc Andreessen explains why learning from past investment mistakes can be a trap, shares his framework for evaluating founder greatness through IQ, courage, and drive, and makes the case that venture investors should back the person over the business plan. They also discuss why AI is reconcentrating the tech industry in Silicon Valley, the concept of consumer surplus and where 99% of AI's value will actually go, and why the labor displacement narrative is fundamentally wrong.

 

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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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Co-funded by the Ethereum Foundation, the EEZ promises synchronous composability between Ethereum mainnet and Layer 2 networks, aiming to address ecosystem fragmentation.

“Power is given only to him who dares to stoop and take it.” — Crime and Punishment

In Fyodor Dostoevsky’s Crime and Punishment, guilt is not always tied to action sometimes it is imposed by society itself. Suspicion becomes a sentence long before truth is examined.

Today, privacy coins stand in a similar courtroom.

They have been accused, labeled, and condemned not always for what they are, but for what they might enable. In the global narrative of digital finance, privacy has quietly been placed on trial by uncanny bureaucrats in the Halls of power from Europe to Asia and America.

THE BIRTH OF SUSPICION: PRIVACY AS A “CRIME TOOL”

Privacy coins such as PIVX, Monero, and Zcash were designed with a simple principle: financial privacy is a right, not a loophole.

Unlike Bitcoin, where every transaction is publicly traceable, privacy coins use advanced cryptography to shield identities, balances, and transaction paths.

Yet this very feature has become their greatest accusation.

Regulators argue that privacy coins could facilitate money laundering, tax evasion, and illicit financing. This concern has shaped global policy responses but it has also oversimplified a far more complex reality.

Privacy coins are not inherently criminal. They are neutral tools and we must protect these tools as well as continuously innovate on them.

THE FALSE EQUIVALENCE: PRIVACY ≠ CRIMINALITY

The labeling of privacy coins as “criminal tools” stems from a flawed assumption: that anonymity automatically implies wrongdoing.

Cash the most widely used financial instrument in the world is anonymous. Yet no one argues that physical currency should be abolished.

Privacy coins provide:
- Protection against data exploitation
- Resistance to financial censorship
- Security from targeted theft
- Confidentiality for individuals and businesses

GLOBAL CRACKDOWN: POLICY, NOT PROOF

Across the world, governments have intensified scrutiny not necessarily because of overwhelming criminal evidence, but because privacy disrupts control.

Europe is tightening AML frameworks, The United States is expanding surveillance compliance. Asia has enforced delistings and Africa remains conflicted between adoption and suspicion.

In Africa, crypto adoption is growing rapidly due to currency instability and limited banking access.

Yet privacy tools are viewed with suspicion.

In regions where financial freedom is most needed, privacy tools are most distrusted.

THE CASE OF PIVX

PIVX has remained steadfast on it’s Privacy vision and mission, innovating in the process as well, while not stagnant, PIVX has been open to a unique form of flexibility, giving users the choice of optionality in their transactions, Transparent or Shield, the ultimate choice is within the fingertips of the user in deciding what they want during every transaction. PIVX’s upgrade and usage of the ZK-SNARK technology has proven to be visionary considering at the very beginning many coins didn’t approve of such technology but PIVX endured the lonely road in choosing vision over hype and has since remained true to this vision. PIVX represents a unique balance:
- Proof-of-Stake efficiency
- Optional privacy via zk-SNARKs
- Decentralized governance

Yet it operates under growing regulatory pressure, including exchange delistings and reduced visibility.

THE REAL ISSUE: CONTROL VS FREEDOM

At its core, this debate is not about crime.

It is about control.

Governments seek transparency.
Users seek privacy.

As oversight increases, demand for privacy tools continues to grow because from time immemorial, the struggle for privacy and dignity have always been a focal point in every generational debate and without ambiguity, those that support, stand with and show respect for privacy and human dignity have always been the biggest winners and this generation will not be different.

CONCLUSION

Privacy coins are not criminals. They are challengers.

And history has never been kind to challengers until it finally understands them.

If privacy is a crime, then freedom itself stands accused.

PIVX. Your Rights. Your Privacy. Your Choice.
To stay on top of PIVX news please visit PIVX.org and Discord.PIVX.org.

Crime, Punishment and Privacy: How Privacy Coins Became the Convenient Villain was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

The World Foundation sold $65 million in WLD tokens through over-the-counter block trades with four private counterparties at an average price of $0.2719 per token.

This market isn't what we wanted. But looking forward, ETH is still in a great place.

Retail investors trust the feed. The feed can't be trusted.

The era of “set it and forget it” AI evaluation is over.

For years, organizations assessed artificial intelligence through a familiar lens: accuracy scores, benchmark performance, adversarial robustness. These metrics made sense for models that answered questions and stopped there. But today’s agentic AI systems don’t stop. They plan, they act, they remember, they call external tools, and they evolve , often without a human watching every step.

That changes everything about how we evaluate them.

The Governance Gap Nobody’s Talking About

When an AI system can autonomously execute multi-step workflows, interact with live systems, and adapt its behavior over time, a static benchmark score tells you almost nothing about whether it’s safe to deploy. You need to know: Can it be stopped mid-action? Does it respect data boundaries? Will it behave consistently under stress? What happens when something goes wrong?

Most enterprises deploying agentic AI today cannot confidently answer all of those questions. That’s not a technology problem , it’s a governance problem.

Introducing RDG-AX: Governance-First Evaluation for Agentic AI

Developed by Kavya Pearlman and XRSI, RDG-AX is a structured governance and evaluation architecture designed specifically for agentic AI systems operating in enterprise and regulated environments. It doesn’t replace your compliance programs or security stack , it fills the gap they were never built to address.

Built on the XRSI RDG data lifecycle governance standard, the framework introduces two core innovations: a stage-gated evaluation process and six behavioral domains that together assess what responsible autonomy actually looks like in practice.

As the framework puts it directly: trust in agentic AI is not assumed. It is earned through structured evidence, independent evaluation, and verifiable governance.

How RDG-AX Works

Three Architectural Layers

RDG-AX operates across three interlocking layers. The first is the RDG governance backbone , establishing data provenance, access controls, role accountability, and incident response structures before any behavioral testing begins. The second is behavioral evaluation, where the agent’s real-world performance is assessed across six domains. The third formalizes certification logic and trust signaling for enterprise and regulatory audiences.

The key insight here is sequencing: governance mapping must precede sandbox evaluation. Evaluation without governance preconditions produces incomplete risk visibility.

A Five-Gate Evaluation Journey

Rather than a one-time test event, RDG-AX walks each agentic system through five sequential gates:

Gate 1: Intake & Scoping , documenting intended use, autonomy level, tool interfaces, and performing risk classification

Gate 2: Governance Alignment , reviewing data lifecycle discipline, lawful basis, minimization constraints, and retention boundaries

Gate 3: Sandbox Analysis , structured scenario testing in a deterministic environment with enforced telemetry capture, including runtime action security assessment

Gate 4: Deployment Readiness , validating remediation, confirming autonomy tiers, and verifying rollback and human intervention pathways

Gate 5: Post-Deployment Monitoring , defining drift detection, recertification cadence, and ongoing runtime action visibility

Six Behavioral Domains

Once inside the sandbox, agents are evaluated across six domains: Capability, Reliability, Controllability, Compliance, Impact, and Model Integrity. Together these domains ask the questions that matter most , not just “does it work?” but “can we control it, trust it, and hold it accountable?”

The Model Integrity domain is particularly forward-looking, addressing governance risks introduced by experience-based learning and internal state evolution , the kinds of risks that will only grow as AI systems become more sophisticated.

The Action Layer Is the New Control Boundary

One of RDG-AX’s most important contributions is its integration of runtime action security, aligned with the Autonomous Action Runtime Management (AARM) Specification v1.0. The framework treats the action layer , the point at which an AI system’s reasoning translates into real-world effects , as a primary governance boundary.

This means evaluating not just what an agent decides, but how that decision becomes an action: whether it can be intercepted, whether policies are enforced, whether outcomes are logged in a tamper-evident way. In a world where AI agents are sending emails, modifying databases, and triggering workflows, this distinction is critical.

What Certification Actually Means

Upon completing the evaluation process, Cautelare issues a structured trust signal , categorical, evidence-backed, and scoped to the declared deployment context. Importantly, certification does not guarantee legal compliance. What it does signal is something arguably more actionable: structured governance maturity and controlled autonomy.

For enterprises, this is the difference between deploying an agentic system with confidence and deploying one with fingers crossed.

The Bigger Picture

Static benchmarking was built for a static world. As agentic AI systems move toward self-directed learning, world-model reasoning, and multi-agent coordination, the evaluation paradigms governing them must keep pace. RDG-AX is a direct response to that challenge , a framework that treats autonomy not as a feature to be celebrated uncritically, but as a risk surface to be mapped, bounded, and governed.

The question for every enterprise deploying agentic AI right now isn’t whether your model performs well on a leaderboard. It’s whether your organization truly knows what that system will do when no one is watching.

Take the Next Step

Agentic AI governance isn’t a future problem , it’s a present one. If your organization is deploying or evaluating agentic AI systems, here’s what you can do today:

Read the full RDG-AX whitepaper at xrsi.org/rdg , including the executive summary and complete architectural framework Assess your current governance posture, can you answer all five gate questions for your deployed agents? Explore the AARM Specification at aarm.dev to understand runtime action security in depth Contact XRSI at info@xrsi.org to learn how RDG-AX certification can be integrated into your AI deployment lifecycle

Responsible autonomy isn’t a constraint on innovation. It’s what makes innovation sustainable.

This post is based on the RDG-AX whitepaper by Kavya Pearlman, XRSI (2026). © 2025–2026 X Reality Safety Intelligence. All rights reserved.

WEBSITE AND SOCIAL MEDIA

https://xrsi.org/  | https://cautelare.com/ | X Account – XRSI | LinkedIn Account – XRSI

For any inquiries or more information, please contact XRSI via info@xrsi.org

No tokens, VC funding, or roadmap theater. Exploring three of the latest no-frills Ethereum tools created by the ECF.

A newly proposed bipartisan bill that hopes to deliver digital asset tax clarity has already ran into opposition within the crypto industry.

Kalshi rolled out automated ban lists for political hopefuls and sporting insiders earlier this week.

Insider trading was already illegal; it is now officially banned for appointed officials in the State of California.

A new working paper from the European Central Bank examined four major protocols and found that a small number of actors control the bulk of governance token holdings.

Intercontinental Exchange has now deployed nearly $2 billion into the onchain prediction market, underscoring Wall Street's growing conviction that event-based trading is here to stay.

KPMG will audit Tether's financials, while PwC is assisting with pre-audit prep.

Iran escalation and $171 million in ETF outflows drive BTC below $66,000.

The NYSE parent company previously announced that it would invest up to $2B in the popular prediction market last October.

Catch the latest price trends and the biggest talking points in this week’s Pulse.

Market Pulse Masternode Count: Masternode metrics are turning green. With 261 nodes joining the network over the past seven days, we’ve successfully reversed the recent downward trend. The total number of active PIVX masternodes now stands at 2,109. Price Check: Sideways movement continues for PIVX. The weekly average settled at $0.0892, a 1.22% decrease from last week’s $0.0903, as prices consolidate around the $0.09 zone. Trading Buzz: Trading volume mirrored the price action this week, seeing a slight pullback. Total weekly volume dropped from $18.5 million to approximately $16 million. But despite the 13.51% drop in volume, trading activity consistently held above the $2 million benchmark throughout the week.

PIVX. Your Rights. Your Privacy. Your Choice.
To stay on top of PIVX news please visit PIVX.org and Discord.PIVX.org.

PIVX Weekly Pulse (Mar. 20th, 2026 — Mar. 26th, 2026) was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

Erin Price-Wright speaks with Chandler Luzsicza, founder and CEO of Galadyne, and Turner Caldwell, cofounder and CEO of Mariana Minerals, about what they actually learned building Starship and Tesla's lithium refinery, and how those lessons translate to their own startups. They cover decision velocity, flat organizations, critical path management, vertical integration, hiring for high-talent-density teams, and how to set aggressive milestones without burning people out.

 

Resources:

Follow Chandler Luzsicza on X: https://x.com/_chandlerl
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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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Wartime trading is onboarding retail to perpetuals as Trump-driven headlines move markets over the weekends.

What if there was a universal adapter that could translate your achievements across any data sources?

Sacks says his 130-day limit as a special government employee has expired.

The stock market's second-worst day of 2026 resulted in new lows for a shaken U.S. tech sector.

Largest U.S. Bitcoin miner offloads roughly a quarter of its treasury to buy back $1 billion in zero-coupon notes at a 9% discount, dropping to third among corporate BTC holders.

On-chain traders on Hyperliquid can now trade over 250 tokenized U.S. equities.

Law No. 15,358 gives judges sweeping power to freeze digital assets during investigations as Brasília takes a "financial strangulation" approach to organized crime.

Borrowers can pledge Bitcoin or USDC as down payment collateral without triggering a taxable event.

BTC treasury darling MARA just blinked, dumping 15k BTC in a subtle pivot away from its HODL-heavy playbook.

The integration connects the dominant gold-backed token to BNB Chain's RWA ecosystem amid a volatile stretch for spot gold prices.

Major altcoins plunge, with ETH, SOL, and XRP dropping 5%.

The LayerZero integration gives assets tokenized on Canton access to over 165 public blockchains.

Borrowers with BTC or USDC can now collateralize their holdings to access additional home loan credit.

Enertoken, developed by Justoken for YPF Luz, launched with over $800 million in tokenized energy assets on XRPL.

David Ulevitch speaks with Justin Fanelli, CTO of the Navy, and John Doyle, founder and CEO at Cape, about how the Navy is transforming its approach to technology adoption, from running bootcamps for program managers to piloting commercial solutions in months instead of years. They discuss the Salt Typhoon breach that exposed China's infiltration of American cellular networks, how Cape built a secure alternative, and what defense tech founders need to understand about selling to the government.

 

Resources:

Follow Justin Fanelli on LinkedIn: https://www.linkedin.com/in/justinfanelli/

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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 new framework attempts to classify crypto assets and clarify securities law boundaries. Let's see where some of today's crypto assets belong.

A breakdown of DeFi's yield sources reveals that borrowing demand, trading fees, and funding rates drove the bulk of returns, while more than half of stablecoin deposits in the Ethereum ecosystem are earning less than U.S. Treasuries.

Spot BTC ETFs had $74 million in outflows on Tuesday as traders await Friday's PCE data.

The island nation is also capping the donations of British citizens living abroad as part of an effort to prevent foreign financial interference.

The crypto exchange wants projects to detail their market maker agreements before launching or listing tokens.

Bitmine's MAVAN platform launches with 3.14M staked ETH, targeting institutional clients and projecting nearly $300M in annual staking rewards.

Russian authorities are intensifying their efforts to transition the country’s internet infrastructure into a “walled garden.” This initiative involves creating a whitelist of state-approved websites while effectively cutting off access to the global web.

For years, the Kremlin has been laying the groundwork for what is often called sovereign “RuNet,” an independent internet infrastructure that can function in isolation from the rest of the world. However, the latest developments suggest a shift from merely filtering content to a more radical exclusion strategy.

Under the guise of national security and digital sovereignty, the Russian government is pushing for a system where access is restricted by default. Instead of blocking specific blacklisted sites, the system would only allow traffic to whitelisted domains that have been vetted and approved by the state.

By routing traffic through government-controlled exchange points, the state gains total visibility into user behaviour and the power to sever connections instantly.

There are growing concerns that the state will mandate the use of domestic encryption standards or state-issued security certificates, effectively stripping away the privacy provided by global HTTPS protocols.

In my opinion, what we are witnessing in Russia is the manifestation of “digital authoritarianism.” When a government controls the gateway to information, privacy is no longer a right; it becomes a conditional privilege that can be revoked at any moment.

By limiting the internet to state-approved sites, the government gains total surveillance and can eliminate dissent. Without access to independent news, international social media, or encrypted messaging apps, the ability for citizens to organize, protest, or even share alternative viewpoints is crippled.

The tragedy of the State-Approved Internet is that it uses the language of safety to implement a system of total control. Governments often justify these crackdowns by claiming they are protecting citizens from “foreign influence” or “extremism.” However, the true target is almost always the individual’s right to think, communicate, and exist privately.

PIVX. Your Rights. Your Privacy. Your Choice.
To stay on top of PIVX news please visit PIVX.org and Discord.PIVX.org.

Moscow Pushes for State-Approved Internet was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

David Ulevitch speaks with Chris Power, founder and CEO at Hadrian, and Vice Admiral Robert Gaucher, the Pentagon's first direct reporting portfolio manager for submarines, at the opening of Hadrian's Factory Four in Cherokee, Alabama. They discuss the state of America's submarine industrial base, why the Navy now needs more than five times the manufacturing capacity it had a decade ago, and how software-driven factories and a new workforce can close the gap.

 

Resources:

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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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Tempo’s launch signals more industry momentum — and tradeoffs — ahead.

Crypto gaming is dead, or so they say. Here's why I disagree.

According to CoinDesk, the latest draft crypto legislation is disappointedly narrow in its approval of stablecoin rewards.

The bipartisan duo claims a prohibition is necessary to prevent China from accessing advanced AI technologies.

Several teams at the EF have collaborated to launch a dedicated resource portal for Ethereum's post-quantum security effort.

As with any audit, the devil is in the footnotes.

Erin Price-Wright speaks with Adam Warmoth, founder and CEO of Chariot Defense, and Alex Miller, CTO of the U.S. Army, about the power crisis at the heart of modern military operations. As the battlefield becomes more distributed and electronics-heavy, the Army's legacy power infrastructure, built around diesel generators and lead-acid batteries, is struggling to keep up. They examine how commercial breakthroughs in EV and aviation technology are being adapted for the front line, why fuel convoys are a military liability, and how procurement reform is letting startups get hardware into soldiers' hands faster than ever.

 

Resources:

Follow Adam Warmoth on X: https://x.com/AdamWarmoth

Follow Alex Miller on LinkedIn: https://www.linkedin.com/in/alex-m-0983a5201/

Follow Erin Price-Wright on X: https://x.com/espricewright

 

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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 long-running crypto exchange is asking governance to approve a radical restructuring that would extend its operational runway.

The company has become the Stablecoin Development Corporation and is betting big on Sky Protocol.

Can the proposed legislation make its way to the House of Representatives?

It’s a critical tool for anyone looking to confidently execute onchain trades across 24 popular, EVM-compatible blockchains.

Bridgit Mendler, Co-founder and CEO of Northwood, joins a16z’s Erik Torenberg to discuss the critical but overlooked bottleneck in space: ground infrastructure. Northwood is building the systems that connect satellites back to Earth, enabling faster, more scalable space missions.

They cover Bridgit’s unconventional path to founding a space company, why vertical integration matters in hard tech, and how modern ground networks could unlock the next wave of innovation in the space economy, from national security to new commercial applications.

 

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OpenAI is sweetening the pot in its battle to win private equity co-investments, guaranteeing 17.5% returns and early access to cutting-edge models

Two U.S. senators have reportedly reached a tentative deal on stablecoin yield, which has gained the blessing of the White House.

How AI agents, stablecoins, and micropayments could rebuild the internet’s business model.

x402 vs. MPP is the wrong debate. The real question is who Cloudflare picks to issue the NET Dollar.

Coinbase International customers can now ape stock-linked perpetual futures with up to 20x leverage at any time.

Prediction market platform Kalshi has secured over $1 billion in its latest funding round, led by Coatue Management.

The raise was completed in April 2025, but is being disclosed now as the company gets a new CEO.

U.S. Attorney Jay Clayton has filed criminal charges against SMCI associates for illegally diverting billions of dollars in servers to China.

Starknet is leaning into privacy infrastructure as the race to differentiate from the Ethereum L1 intensifies.

The markets move fast, but we move faster. Catch the latest price action and top talking points in this week’s Pulse. Stay informed, stay ahead.

Grassroot Momentum

While the charts show a 12.31% recovery in weekly price and our masternode count begins to stabilize at 1,848, the true strength of PIVX lies in its utility.

Real adoption isn’t found on a price chart; it is found on the ground. This week, PIVX Africa proved what’s possible by bringing privacy and decentralized finance to a local football event in Oyo State, Nigeria. By integrating PIVX into a community that lives and breathes the sport, we are introducing real-world crypto usage and privacy awareness where it matters most. This is what grassroots adoption looks like: empowering people to transact freely and securely within their own vibrant, local ecosystems.

Market Pulse Masternode Count: The market is gaining ground, but masternodes are still clawing back. After the dip from 2,074 two weeks ago, we’ve seen a slight reversal. Four new nodes joined the network this week, bringing the number of active PIVX masternodes to 1,848. Price Check: It was a week of sideways movement for PIVX as the daily value settled around $0.09. A momentary break above $0.1 was met with a quick correction, but the underlying trend remains positive. The weekly average rose to $0.0903, marking a 12.31% recovery from last week’s $0.0804. Trading Buzz: We saw a general improvement in trading sentiment, though total volume couldn’t quite match the previous week’s surge. Weekly volume settled at $18.5 million, an 11.48% decrease from $20.9 million. However, the day-to-day engagement tells a more positive story, with daily volume holding steady above $2 million.

PIVX. Your Rights. Your Privacy. Your Choice.
To stay on top of PIVX news please visit PIVX.org and Discord.PIVX.org.

PIVX Weekly Pulse (Mar. 13th, 2026 — Mar. 19th, 2026) was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

In this conversation, Shyam Sankar, chief technology officer at Palantir Technologies, discusses his new book Mobilize, his commission in the U.S. Army, and why he believes the most important thing America can do right now is inspire its latent heretics to step forward. He also breaks down how he thinks about the SaaS market under AI pressure, what the "alpha versus beta software" distinction means for which companies survive, and why he started a film production company.

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How Convex Finance is still serving top farming opportunities four years after its peak.

Bezos is wooing Middle Eastern royalty and Asian financial giants to invest in his automated empire.

Hallucinated servers can be combined with Ethereum's onchain primitives to power new kinds of crypto apps.

The crypto exchange believes that laying off employees will better help it prioritize resources and drive efficiency.

Just months after an embarrassing pitch fixing scandal rocked the MLB, baseball is ready to embrace prediction market betting.

A new paper, “Some Simple Economics of AGI,” is making the rounds—Web3 with a16z we sat down with author Christian Catalini (MIT Crypto Economics Lab) and Eddy Lazzarin (CTO of a16z crypto), in conversation with Robert Hackett, to unpack what AGI could mean for work and markets.

EPISODE NOTES: 

A hot paper — "Some Simple Economics of AGI" — has been making the rounds, so we sat down with the author, covering: 

Automation vs. verification: the key economic split  Why AI agents now feel like coworkers - What's happening to junior roles and the “codifier’s curse”  The “AI sandwich” structure for firms  The value of "meaning-makers," consensus, and status economies  Why crypto may become essential infrastructure for identity, provenance, and trust  Two possible futures: a hollow vs. augmented economy 

Featuring Christian Catalini (founder of MIT Crypto Economics Lab) and Eddy Lazzarin (CTO of a16z crypto) in conversation with Robert Hackett, our discussion dives deep into how automation is reshaping labor markets, as well as the nature of intelligence. 

What do these changes mean for startups, the future of work, and your career?

 

 

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Democrats are poised to upset the balance in Congress; which midterm races matter most for the crypto industry?

Stripe's highly anticipated L1 blockchain has finally arrived, and comes equipped with a new standard for agentic payments.

The crypto exchange's previously announced IPO is on pause, sources told CoinDesk.

Trade[XYZ] is now the first and only officially licensed perpetual futures provider for the S&P 500 index.

Attack poisoning is becoming one of the fastest-growing crypto scams. Attacks have grown in the past few years and have targeted even the most seasoned crypto whales. To put things in perspective, data suggests that users may have lost nearly $80 million to these attacks between July 2022 and June 2024.

In today’s “What Could Possibly Go Wrong” series, I’ll walk you through all you need to know about address poisoning and how to stay safe.

What is Address Poisoning?

As the name suggests, address poisoning is a deceptive tactic where an attacker contaminates your transaction history with a fraudulent address. These attacks work because the malicious address looks nearly identical to one you frequently use.

Unlike traditional hacks, this doesn’t involve stealing your private keys or compromising your wallet software. Instead, it is a social engineering attack that exploits a common user habit: copying addresses from recent transaction logs rather than verifying them from a primary source.

How Does Attack Poisoning Work?

The goal of the attacker is to wait for the moment you decide to move funds. They rely on the fact that most wallet interfaces truncate addresses (e.g., 0x123…4567) to save space. The image below is my dummy account on Phantom.

Phase 1: Surveillance

Attackers use automated bots to monitor “high-traffic” blockchains like Ethereum, Solana, and Tron. They look for active wallets moving significant amounts of stablecoins (USDT/USDC) or native tokens.

Phase 2: The Vanity Mirror

Once a target is identified, the attacker uses a Vanity Address Generator. They create a new address that matches the first 4–6 and last 4–6 characters of your frequent counterparty. For instance:

Real Address: 0x742d…4438f44e Poison Address: 0x742d…4638f44e (Note the subtle difference in the middle characters) Phase 3: The Dust Injection

The attacker sends a “dust” transaction (a negligible amount like 0.0001 tokens) or a zero-value transfer from the fake address to your wallet.

On networks like Ethereum, scammers can use the “transferFrom” function of a smart contract to make it appear as if you sent a transaction to them for 0 tokens. This ensures the fake address sits at the very top of your “Sent” history.

Phase 4: The Fatal Mistake

Next time you need to send funds to your friend or your exchange account, you glance at your history, see an address that starts and ends with the familiar characters, click “Copy,” and hit “Send.” Since the blockchain is irreversible, those funds are gone the moment the transaction is confirmed.

Let’s Talk Numbers

As of early 2026, address poisoning has become a multi-million dollar “lottery” for scammers. Security researchers have identified over 270 million poisoning attempts across Ethereum and BNB Chain alone. Other interesting stats worth mentioning include:

Up to 17 million individual wallets have been poisoned by at least one fraudulent transaction. Estimated losses from address poisoning and related phishing reached approximately $83.8 million in 2025. The average victim’s wallet balance in these campaigns is roughly $338,900, proving that scammers are specifically hunting high-net-worth individuals. But don’t assume you are still safe if you are a small-time player. When Experience Isn’t Enough 1. The $68 Million Whale (May 2024)

In one of the most famous cases, a sophisticated trader lost $68 million in Wrapped Bitcoin (WBTC) in a single transaction. The attacker had “poisoned” the trader’s history with an address matching the first and last digits of the victim’s own vault. In a rare turn of events, the attacker eventually returned the funds after a public bounty negotiation, but this is the exception, not the rule.

2. The $50 Million USDT Loss (December 2025)

A trader lost $50 million in USDT after copying a lookalike address from their transaction history. Despite offering a $1 million bounty for the return of the funds, the assets were quickly laundered through decentralized mixers, making recovery nearly impossible.

3. The DEA’s Test Failure (2023)

Even government agencies aren’t immune. The U.S. Drug Enforcement Administration (DEA) lost over $55,000 in seized USDT to a poisoning attack. After sending a test transaction to a Marshals Service address, a scammer immediately “poisoned” the DEA’s history with a lookalike. The DEA agent copied the wrong address for the main transfer, sending the funds directly to the scammer.

How to Stay Safe

I know you’ve been safely using the same wallet address for five years and think you’d never be a victim. Well, better safe than sorry. For a start, you must treat your transaction history as a publicly editable, untrusted document. Here are some general tips on how to stay safe from address poisoning.

Never Copy from History: This is the number one rule. Always copy the destination address from the original source, such as your exchange’s “Deposit” page or your friend’s direct message. Use an Address Book: Most reputable wallets allow you to save “Verified Contacts.” Give them nicknames like “My Ledger” or “Binance Deposit.” When sending, select the name, not the hex string. The “Middle Character” Rule: Never verify an address by just the first and last 4 characters. Brute-forcing the ends is cheap; matching the middle 10 characters is computationally nearly impossible for scammers. Send a Test Transaction: For large sums, always send a tiny amount first. Confirm the receipt on the other end independently, then use the exact same address for the full amount. Leverage Security Features: Wallets like Trust Wallet now offer “Address Poisoning Protection” that uses APIs to flag known lookalike addresses before you hit send. If your wallet gives you a “Similarity Alert,” stop immediately.

PIVX. Your Rights. Your Privacy. Your Choice.
To stay on top of PIVX news please visit PIVX.org and Discord.PIVX.org.

How “Address Poisoning” is Emptying Crypto Wallets was originally published in PIVX on Medium, where people are continuing the conversation by highlighting and responding to this story.

Partnering with Edra: Context for Agents at Scale

Eugen, Yannis and their team are turning enterprise knowledge into dynamic context that makes AI agents dramatically more effective.

By Luciana Lixandru Published March 18, 2026 TEAM EDRA.

Every company runs differently. Two businesses in the same industry will have their own escalation paths, and workarounds—their own tribal knowledge accumulated over years and stored, if anywhere, in the institutional memory of people who won’t always be there. When you drop a general-purpose AI into that environment, it starts from zero. The work of getting it up to speed (the forward-deployed engineers, manual documentation, consultants) is slow, expensive and has to be redone every time a process changes. Most companies are living this problem right now.

Eugen Alpeza spent seven years at Palantir, where he was instrumental in building the company’s U.S. commercial go-to-market motion, including starting Palantir’s work with AT&T, one of its largest and most complex deployments. In 2023, he took on the launch of Palantir’s AI Platform under CEO Alex Karp. Together with Yannis Karamanlakis, they created the Forward Deployed AI Engineer role at Palantir—designed to bridge AI research with real world production deployments. Yannis became the first Forward Deployed AI Engineer at the company, leading a team focused on taking LLMs from demos into production at scale. Yannis had already led a major pure AI commercial project, a recruiting search engine that increased placement rates for a staffing firm by 129%. The two left Palantir as close friends and co-founders. They had known each other for 13 years, since university, and had long planned to start a company together.

What Edra has built is elegant in its logic. Instead of asking humans to document processes, Edra analyzes the data a company already generates. Through support tickets, emails, logs, chat histories, it creates a living knowledge base that reflects how the business actually runs, not just how it was supposed to run on paper. As people use it, the system learns and improves on its own. And unlike black-box fine-tuning approaches, it is transparent and editable—you can see exactly what Edra has learned and why. From there, agent automation is straightforward. 

The early results are real. The first successful use cases are around automating IT service management and customer technical support, where the data is rich and the pain is acute. The early customers love it and are expanding aggressively. 

As always, our investments are all about people. When I first met Eugen and Yannis, what struck me was not only what they had built, but how they work together. Eugen is one of the most commercially gifted people I have met—someone who earns the trust of skeptical buyers and makes them believe. Yannis is technically exceptional, the kind of partner who makes the hardest things feel solid. Their dynamic as a founding duo is a genuine superpower.

We are thrilled to partner with Eugen, Yannis and the entire Edra team. 

Share Share this on Facebook Share this on Twitter Share this on LinkedIn Share this via email Related Topics #AI #Funding announcement Partnering with Aspora: Diaspora Banking Goes Global By Luciana Lixandru, George Robson and James Flynn News Read Partnering with Robco By Luciana Lixandru, Shaun Maguire and Cornelius Menke News Read Partnering with Tacto: Future-Proof Supply Chains Luciana Lixandru, Julien Bek News Read JOIN OUR MAILING LIST Get the best stories from the Sequoia community. Email address Leave this field empty if you’re human:

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Erik Torenberg sits down with Jacob Helberg to discuss AI, manufacturing, supply chains, and the new geopolitics of technology. Drawing on themes from Helberg’s book The Wires of War, they explore why hardware, industrial capacity, and secure supply chains have become central to both economic strength and national security.

They also unpack what it means to “win the AI race” — from model leadership and global adoption to energy, compute, tariffs, and reindustrialization in the U.S.

 

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Vishal Misra returns to explain his latest research on how LLMs actually work under the hood. He walks through experiments showing that transformers update their predictions in a precise, mathematically predictable way as they process new information, explains why this still doesn't mean they're conscious, and describes what's actually required for AGI: the ability to keep learning after training and the move from pattern matching to understanding cause and effect.

 

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In this episode, originally aired on Big Technology Podcast, Olivia Moore discusses whether AI startups can compete with the big chatbots, why American sentiment toward AI is so negative, and what she learned from giving LLMs personality tests. She also breaks down where ChatGPT, Claude, and Gemini are diverging, why Open Claw signals a new wave of agentic products, and what makes memory the most underrated feature in consumer AI.

 

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Marc Andreessen joins David Senra for a conversation about entrepreneurship, history, and what drives some of the world’s most ambitious builders.

In this conversation with David, Marc reflects on patterns he’s seen across great founders, why many of them focus relentlessly on building rather than introspection, and how technology and entrepreneurship continue to shape the future.

 

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This conversation with Emil Michael, undersecretary of defense for research and engineering and acting director of the Defense Innovation Unit, was recorded at the a16z American Dynamism Summit in Washington, D.C. Michael walks through how he inherited a department running 14 undefined technology priorities, cut them to six, and made applied AI number one. He also gives the first detailed account of why commercial AI contracts written under the previous administration created a vendor-lock crisis that put active military operations at risk.

 

 

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This conversation with Alex Karp, cofounder and CEO of Palantir, was recorded at the a16z American Dynamism Summit in Washington, D.C. Karp discusses the role of technology in modern warfare, Silicon Valley's obligations to national defense, and why he believes America's single greatest competitive advantage is its ability to cultivate and protect unconventional talent.

 

 

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… and other musings from our Risk Club Dinner in Lisbon we hosted in partnership with Ricardo Sequerra Amram at Point Nine Capital.

Portuguese real estate woes as a proxy for where we are geopolitically

Portugal is about as far from active conflict zones as you can get while staying on the continent — neutral twice in the World Wars, Atlantic-facing, welcoming to expat families. Thousands of American families are moving there every year and the supply of homes cannot keep pace with demand.

In an era of geopolitical upheaval, many people who can afford to move here are doing so. Remote work has decoupled talent from geography — especially when you might just be co-working with your AI agents. And the countries that make it easy to arrive — a clear path to residency, a functioning bureaucracy, quality of life — may well pull ahead of the ones that don’t. Countries actively hostile to immigration were among our short positions for a reason.

But…what if AI agents start optimizing for geopolitical safety when they allocate capital they are tasked to manage? Could we expect them to start buying real estate in places like Portugal? Will there be tension between expats, locals and AI agents in these safe-haven places?

As international pressure for a Ukraine ceasefire intensifies, the conversation turned to what any agreement needs to include

When the war started, millions of Ukrainians fled for their safety — among them a significant portion of the country’s top technical talent. These people want to go home. And the country needs them to return in order to rebuild. But what conditions would make that a rational choice for people who, rightly, sought safety for their families?

At the table, we talked about explicit non-conscription protections for returnees and possibly a credible multinational security presence as the necessary conditions for ceasefire and, eventually, recovery. Longer term, reconstruction in Ukraine would be a greenfield investment opportunity — with a highly educated diaspora ready to return and a potential EU accession path that would unlock capital to rebuild the nation in a way that could rival Poland’s post-1989 transformation.

European defense has come up at every dinner we’ve hosted this year

In Lisbon, we talked at length about the capabilities of European armies vis a vis the realities of the modern battlefield. Case in point: Germany is still producing Leopard 2 tanks — €10 million assets that are functionally obsolete in a war waged on €500 DJI drones and intelligence.

With the US signalling ambiguity about Article 5 compliance, the continent has little choice but to prepare for a post-NATO world — ironically, making that world all the more likely. Because if you are not actively working to affirm that the alliance holds, then you are (intentionally or not) building for its fallout.

As investors, we follow specific areas of defense closely but we’ve been in this space long enough to know that the best signals come from the founders themselves. We keep conversations like this going because we want to hear how they see the future and what they think it will take to keep everything from unravelling. Then we back them.

Bullish on India, bearish on manufacturing exposed to robotics

The table was bullish on India (manufacturing shift, consumer market growth, early tech adoption), the US (hard to bet against in an AI-dominated world, despite everything), and Switzerland (neutral positioning, financial infrastructure, talent concentration). Bearish on manufacturing economies exposed to robotics disruption, emerging markets without resource backing, and countries actively hostile to immigration.

Several policy proposals echoed themes from prior dinners: universal capital ownership from birth, higher inheritance taxes, global taxation modeled on the US approach. One idea we hadn’t heard before was publishing all government spending on a public blockchain — every transaction from any public actor, immutable and accessible, making data manipulation structurally impossible.

BlueYard Capital hosts regular Risk Club dinners across Europe and the US. The conversations are off the record; these notes reflect themes and ideas. We’re looking for the next generation of founders making civilizational bets. If that’s you — or if you’re an investor, policymaker, or operator thinking about these questions — we’d love to talk.

Disclaimer: The information contained in this article has been prepared solely for informational purposes and is not an offer to sell or a solicitation of an offer to purchase an interest in any entity managed by BlueYard Capital (“BlueYard”). Any reference to a specific company or security does not constitute a recommendation to buy, sell, hold, or directly invest in the company or its securities. It may not be modified, reproduced, or redistributed in whole or in part without the prior written consent of BlueYard. Portfolio company information presented herein is for informational purposes only and not intended to be a guarantee of certain investment results. BlueYard does not represent that the information herein is accurate, true, or complete, makes no warranty, express or implied, regarding the information herein and shall not be liable for any losses, damages, costs, or expenses relating to its adequacy, accuracy, truth, completeness, or use. All other company, product and service names or service marks of others and their use does not imply their endorsement of, or an association with this program.

In this episode, previously aired on Cheeky Pint, Garrett Langley describes how a stolen gun in his Atlanta neighborhood led him to build Flock Safety, now deployed in more than 6,000 cities and involved in clearing over a million crimes last year. He covers how the product has evolved from license plate cameras to drones, real-time 911 integration, and an AI-powered orchestration layer for city safety.

 

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Today we’re adding NEAR Intents to Brave Wallet in our latest browser release (v1.88). The Brave Wallet enables multi-chain access right from the Brave browser, and NEAR Intents is the first swap provider that ties together nearly all of our supported blockchains: Bitcoin, Solana, Zcash, Cardano, and EVM (including Ethereum, Base, Arbitrum, etc).

NEAR Intents connects any chain, any asset, and any agent, and has executed over 19 million swaps and over $14 billion in all-time volume across 35 chains. NEAR Intents uses a novel transaction architecture to abstract away cross-chain complexity and maximize performance, security, and efficiency for DeFi apps, AI agents and end users.

This major step for Brave Wallet enables any-to-any chain swaps without the complexity that comes with traditional bridges. Brave Wallet users now have a decentralized way to swap assets like BTC and ZEC that traditionally lack DEX options. 

For instance, users could swap assets from: 

Transparent ZEC to any chain Any chain to transparent ZEC Shielded ZEC to any chain Any chain to shielded ZEC

Additionally, if the user is spending shielded ZEC, they are always returned back to the shielded pool in case of a refund. Shielded transactions use zero-knowledge proofs to hide the sender, receiver, and amount of a transaction from the public blockchain. Shielded transactions with Zcash in Brave Wallet give users a way to send and store crypto privately.

James Mudgett, VP of Web3 at Brave, said, “The integration of NEAR Intents marks a big step in Brave Wallet’s mission to make moving assets across blockchains simple, secure, and most importantly, intuitive, for everyone. Users can now move a wide variety of assets across chains, from Bitcoin and Zcash to Solana, Cardano, and the EVM ecosystem, all without bridges or manual gas handling. It’s a major step toward making cross-chain interaction feel natural and frictionless. For users, it means moving value anywhere becomes as easy as sending a message, and for the ecosystem, it’s another stride toward making Web3 truly accessible to everyone.”

Alex Shevchenko, CEO of the team behind NEAR Intents, Defuse Labs, said, “Brave sits at the heart of Web3, connecting hundreds of millions of users to the next generation of digital finance. Integrating NEAR Intents into Brave unlocks the freedom to trade seamlessly across chains for anybody with access to a browser, anything from Bitcoin to Shielded Zcash. It’s a powerful example of how intent-based infrastructure can redefine access, simplify complexity, and put privacy back into the hands of users.”

Adding NEAR Intents to Brave Wallet is the latest step in the longstanding collaboration between Brave and NEAR.

About Brave Wallet

Brave Wallet is the secure, multi-chain crypto wallet built directly into the Brave browser, no extensions required. With Brave Wallet, users can manage tokens and NFTs; connect to DApps and onramp to Web3; and explore decentralized finance, social media, gaming, and more. Brave Wallet users can connect other “hot” wallets, or “cold” wallets like Ledger & Trezor. They can buy, store, send, and connect to DApps on Solana, Ethereum, Cardano and EVM chains, and the Filecoin chain. 

Brave is a driving force leading the way for Web3 adoption, directly supporting Web3 into the broader Web through its privacy-preserving browser, independent search engine, and browser-native, multi-chain crypto wallet. Brave currently has 110 million monthly active users. Learn more at brave.com.

About NEAR Intents:

NEAR Intents is the universal liquidity protocol powering one-click cross-chain swaps and unified liquidity for onchain markets and tokenized assets. Using a novel intent-based transaction infrastructure that empowers users to express outcomes instead of managing routes, bridges, and liquidity sources, NEAR Intents unlocks frictionless cross-chain swaps for DeFi users, autonomous trading for AI agents, and broad distribution for blockchains, dApps, and asset issuers. NEAR Intents has powered billions of dollars in volume across leading chains and assets and is now natively integrated into major DeFi protocols, wallet providers, traditional financial systems, and AI platforms, bringing instant and verifiable execution to global markets. Learn more at https://intents.near.org/.

Partnering with Scanner: Every Log Tells a Story—If You Can Find It Fast Enough

Cliff and Steven are making petabytes of security data searchable in seconds, and opening the door to a new era of AI-driven security operations.

By Bogomil Balkansky Published March 10, 2026 Steven and Cliff.

A while back, I was deep in research on the next generation of security infrastructure, talking to CISOs and security engineers at some of the most technically sophisticated companies in Silicon Valley. I asked them all the same question I’d asked a decade earlier when I worked in enterprise software: What’s your biggest headache? The consistency of their answers surprised me. “We drown in logs we can’t afford to keep,” as one security leader put it, “and go blind on the logs we can’t afford to search.”

Enterprise security today is a story of impossible choices. The tools that teams rely on generate enormous amounts of log data—every API call, every login event, every network connection. To investigate cyber threats, they need all of it, often going back a year or more. But storing everything in a SIEM like Splunk is prohibitively expensive; costs could easily consume 15% of a CISO’s entire budget. Instead, companies make a compromise: they keep only the most recent 10 to 30 days of logs in their SIEM and park the rest in Amazon S3, where storage is cheap, but the data is effectively frozen. When a breach, a compliance audit, or a forensic investigation happens, security teams discover too late that the evidence they need is out of reach, opaque and unsearchable. 

I first heard about Scanner from a member of the security team at Temporal, one of our portfolio companies, who called it, “crazy fast.” I looked into it, and reached out to Cliff Crosland right away.

What Cliff and his co-founder Steven Wu have built is elegant in its insight. They asked: what would a log search engine look like if you designed it from scratch for object storage? The answer was a purpose-built inverted index that maps field values directly to file regions in S3. Rather than combing through billions of rows, Scanner narrows each query to only the relevant slices of data. A petabyte of logs becomes interactive. Queries that took hours now run in seconds. And a streaming detection engine runs hundreds of detection rules continuously across tens of terabytes a day, without re-scanning the world for each one.

Cliff and Steven are exactly the kind of founders we look for. Both Stanford CS alums, they were engineering leads together at Accompany (acquired by Cisco), where they built core data infrastructure under demanding, production-scale conditions. They have an obsession with performance that borders on the philosophical; they don’t tolerate systems that feel slow. And they have the expertise to build something better.

What’s most striking about Scanner isn’t the technology—though that is genuinely impressive. It’s the customers. The companies using Scanner today read like a who’s who of the cloud native world: Notion, Ramp, Benchling, Confluent, Lemonade, BeyondTrust. And they’re not just using it—they love it. Benchling replaced another product after a forced tenfold price increase, and their head of security engineering called it one of the best technical decisions their team had made. Ramp started with security logs and then expanded to application logs, reducing their SIEM bill in the process. Notion’s detection and response team built an internal AI agent that autonomously runs security investigations using Scanner. 

That last example signals what’s to come. We are entering a new era of security operations, where AI agents will do much of the investigative work that today consumes hours of human time. But agents need to rapidly iterate, ask questions and follow threads; queries can’t take minutes, much less hours. Scanner’s speed is enabling these agentic security workflows across a wide range of companies: within weeks of their MCP release, nearly a third of Scanner’s customers were already using it in production, and agents now account for 80% of queries on the platform. That is not a prototype or a promising beta. That is the future arriving ahead of schedule.

Sequoia is proud to lead Scanner’s Series A, and we’re thrilled to partner with Cliff, Steven and their team as they work to transform a market overdue for reinvention. Scanner is winning hearts and minds among the most technically forward organizations today, and together, they will define the next decade of security infrastructure.

Share Share this on Facebook Share this on Twitter Share this on LinkedIn Share this via email Related Topics #AI #Funding announcement Partnering with Sandstone: An AI-Native Platform for In-House Legal Teams By Bogomil Balkansky News Read Partnering with Traversal By Bogomil Balkansky and Charlie Curnin News Read Partnering with FastAPI Labs: Simplified App Deployment By Bogomil Balkansky and Lauren Reeder News Read Partnering with Apex Security: The AI-Empowered Future, Secured By Bogomil Balkansky News Read JOIN OUR MAILING LIST Get the best stories from the Sequoia community. Email address Leave this field empty if you’re human:

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Anish Acharya speaks with Olivia Moore about the latest edition of the a16z Top 100 AI Apps report. They cover why ChatGPT is still 30 times bigger than Claude on web, how the three major platforms are specializing for different users, what global adoption data reveals about cultural attitudes toward AI, and why agents, memory, and voice are about to change everything.

 

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Daisy Wolf speaks with Dr. Andrew Huberman, professor of neurobiology and ophthalmology at Stanford University and host of the Huberman Lab podcast. They discuss how the pandemic sparked a consumer health revolution, the emerging peptide and GLP landscape, what the science actually says about focus drugs, and the neurotechnologies Huberman believes will let us write to our own biology within the next five years.

 

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Alex Rampell and Erik Torenberg speak with Mike Cannon-Brookes, cofounder and CEO of Atlassian, about how to make sense of the SaaS selloff, why not all software companies face the same AI-driven risks, and how Atlassian is thinking about the shift from records to processes. They also examine the real design challenge of getting everyday users to trust and benefit from AI agents in enterprise workflows.

 

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Services: The New Software

By Julien Bek Published March 5, 2026

The next $1T company will be a software company masquerading as a services firm. 

Every founder building an AI tool is asking the same question: what happens when the next version of Claude makes my product a feature? They’re right to worry. If you sell the tool, you’re in a race against the model. But if you sell the work, every improvement in the model makes your service faster, cheaper, and harder to compete with. A company might spend $10K a year for QuickBooks and $120K on an accountant to close the books. The next legendary company will just close the books.

Intelligence vs Judgement

Writing code is mostly intelligence. Knowing what to build next is judgement.

Translating a spec into code, testing, debugging: the rules are complex but they are rules. Judgement is different. It requires experience and taste, instinct built on years of practice. Deciding which feature to build next, whether to take on tech debt, when to ship before it’s ready.

A year ago, most Cursor users treated AI as autocomplete. Today, more tasks are started by agents than by humans. Software engineering accounts for over half of all AI tool usage across professions. Every other category is still in single digits. The reason is that software engineering is primarily intelligence work. AI has crossed the threshold where it can do most of the intelligence work autonomously and leave the judgement to humans. Software engineering got there first. It is coming to every single profession.

Copilots and Autopilots

A copilot sells the tool. An autopilot sells the work.

Until recently, AI models were still developing intelligence and judgement, so the right approach was to build a copilot first: put AI in the hands of a professional and let them decide what to do with it. Harvey sells to law firms. Rogo sells to investment banks. The professional is the customer, the tool makes them more productive, and they take responsibility for the output.

Today, the models are intelligent enough that in some categories the best place to start is as an autopilot. Crosby sells to the company that needs an NDA drafted, not to outside counsel. WithCoverage sells to the CFO who needs insurance, not to the broker. The customer is buying the outcome directly. The work budget in any profession dwarfs the tool budget, and autopilots capture the work budget from day one.

The higher the intelligence ratio in any field, the sooner autopilots will win.

The Convergence

Today’s judgement will become tomorrow’s intelligence. As AI systems accumulate proprietary data about what good judgement looks like in their domain, the frontier will shift. Copilots and autopilots will converge. The copilot-to-autopilot transition has already begun in several categories. But the starting position matters because it determines where autopilots can win customers now and begin compounding the data that will eventually let them handle judgement too.

The Autopilot Playbook: Outsourcing as the Wedge

For every dollar spent on software, six are spent on services.

The total addressable market for autopilots is all labour spend in a category, insourced and outsourced combined. But the right place to start is where outsourcing already exists.

If a task is already outsourced, it tells you three things. One, the company has accepted that this work can be done externally. Two, there’s an existing budget line that can be substituted cleanly. Three, the buyer is already purchasing an outcome. Replacing an outsourcing contract with an AI-native services provider is a vendor swap. Replacing headcount is a reorg.

The playbook: companies should start with the outsourced, intelligence-heavy task. Nail distribution. Expand toward the insourced, judgement-heavy work as the AI compounds. The outsourced task is the wedge. The insourced work is the long-term TAM.

Crosby started with NDAs: a well-defined task, primarily intelligence, that most companies already outsource to external counsel. The budget exists, the scope is clear, the ROI is immediate, and the substitution is frictionless.

Opportunity Map

Plotting every services vertical on an intelligence-to-judgement spectrum and outsourced-to-insourced ratio produces a priority map with labour TAM in brackets. The list is illustrative.

Insurance brokerage ($140-200B). The largest dollar market on this list. Standard commercial lines are highly standardised: the broker’s value-add is essentially shopping across carriers and filling forms, pure intelligence work. The distribution layer is incredibly fragmented, tens of thousands of small brokers each running the same process, so no single incumbent controls the customer relationship. WithCoverage and Harper are interesting newcomers.

Accounting and audit ($50-80B outsourced in the US alone). The US has lost roughly 340,000 accountants over five years while demand has grown. 75% of CPAs are nearing retirement, the licensing path is long, and starting salaries lag tech and finance. That structural shortage is pushing firms to accept AI faster than almost any other profession. Rillet is building the AI-native ERP that will close the books. Basis started as a copilot for accountants.

Healthcare revenue cycle ($50-80B outsourced in US). People hear “healthcare” and assume it’s judgement-heavy, but the billing layer is almost pure intelligence. Medical coding is translating clinical notes into ~70,000 standardised ICD-10 codes. The rules are complex but they are rules. The outsourcing is already mature and outcome-based. An autopilot just has to do the same thing at lower cost. Anterior is the furthest along.

Claims adjusting ($50-80B including TPAs). On the other side of the insurance policy, claims adjusting is a separate autopilot surface. Standard-line claims are settled by interpreting policy language against damage schedules and setting reserves using actuarial tables. The adjuster workforce is aging out and nobody’s replacing them. The market is massively outsourced to independents and TPAs like Crawford and Sedgwick. One industry, at least two distinct autopilot opportunities. Pace is building the autopilot for claims handling. Strala is building an AI-native TPA. 

Tax advisory ($30-35B). CPA licensing creates a regulatory moat, but 80-90% of the underlying work is intelligence. Every additional jurisdiction a tax autopilot handles deepens its data moat. Multi-jurisdiction complexity is exactly what SMBs outsource because no single in-house accountant can cover it. TaxGPT is an early mover alongside Skalar and Ravical in Europe.

Legal, transactional work ($20-25B). Contract drafting, NDAs, regulatory filings: high intelligence, routinely outsourced. The work product is standardised enough that quality is verifiable, so the buyer can trust AI output without deep legal expertise. Harvey is the emerging leader and is moving quickly to autopilot; Crosby and Lawhive are the autopilot-native newcomers.

IT managed services ($100B+). Every SMB outsources its IT. Patching, monitoring, user provisioning, alert triage: intelligence work running on repeat across thousands of identical environments. The existing software layer (ConnectWise, Datto) sells tools to the MSP. Nobody has yet sold “your IT runs” directly to the company as an outcome. Edra is automating IT processes. Serval is automating IT support.

Supply chain and procurement ($200B+). Most enterprises negotiate seriously with only their top 20% of suppliers. The long tail gets zero attention because it’s not economical to have humans do the work. Contract leakage runs 2-5% of total procurement spend. The wedge is abandoned work: no budget line to justify, no incumbent to displace, just found money. Magentic is building the AI for direct procurement, AskLio for indirect procurement. Tacto is building both the system of record and copilot for the midmarket. 

Recruitment and staffing ($200B+). The largest services market on this list. The top of the hiring funnel (screening, matching, outreach) is pure intelligence, but closing a candidate and assessing culture fit is judgement built on years of pattern recognition. The autopilot wedge exists in high-volume, low-judgement roles where matching is standardised. Juicebox, Mercor, Jack & Jill are emerging leaders building across the spectrum.

Management consulting ($300-400B). Huge market but the work is mostly judgement. The interesting question is whether AI can disaggregate consulting into intelligence components (data gathering, benchmarking) and judgement components (strategic recommendations), with the intelligence layer getting automated and the judgement layer staying human. Best candidates TBD.

In 2025, the fastest-growing AI companies were copilots. In 2026, many will try to become autopilots. They have the product and the customer knowledge. But they also face the innovator’s dilemma: selling the work means cutting their own customers out of doing it. That’s the opening for pure-play autopilots.

If you’re building one, reach out. julien@sequoiacap.com / @julienbek

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Google has announced that starting September 2026, every Android app developer must register with Google and upload government-issued identification, even if they don’t use the Google Play Store. Brave has joined the EFF, the Tor Project, and more than 40 other organizations in calling upon Google to Keep Android Open and withdraw this requirement, which undermines a historically user-first ecosystem, presents massive privacy risks, and further entrenches Google’s surveillance economy.

Google is overriding user choice

When users install software outside Google’s Play Store, they are choosing to control what runs on their devices without Google’s gatekeeping. That choice is fundamental to what makes Android an open platform.

Last year, we launched an official Brave repository on F-Droid (a free and open source Android app store) so users could get Brave without going through Big Tech app stores and the accompanying tracking and restrictions. Many of our users specifically want software that is not mediated by Google.

Google’s new policy would override that choice. Even when a user deliberately seeks out an app from an independent source, Google would require the developer to have registered with Google first: paying a fee and submitting their legal name, physical address, phone number, and government ID for mandatory developer verification.

A developer registry is a privacy risk

Google’s developer verification policy creates a centralized database, controlled by a single corporation, containing the real-world identity of every person who writes software for Android. 

The privacy risks are immense: developers (often volunteers) who build privacy-first browsers, encrypted messaging apps, VPNs, Tor-based software or tools for journalists and activists in hostile environments would be required to upload government ID and other highly personal data to Google. These developers are unlikely to trust Google and might stop developing for Android, leaving vulnerable users much worse off.

This is part of a pattern

Google has repeatedly proposed mechanisms that expand its control over the platforms it operates, and we have opposed them each time. To name just a few:

Deprecation of Manifest V2 reduces what extensions can do, weakening the tracker blockers and other privacy tools that users rely on.

Google’s AMP Project inserts Google between users and the websites they want to visit, and requires pages to be built in ways that benefit Google’s advertising systems. Under pressure, Google eventually walked back this project.

Privacy Sandbox uses Google’s browser monopoly to force participation in advertising infrastructure and cement Google’s control over the Web. Under pressure, Google walked back this project as well.

Each of these mechanisms share the same structure: Google leverages its platform position to try to insert itself into activities where users and developers did not ask for Google’s involvement, framing the change as beneficial.

Keep Android open

The open letter we signed urges Google to do three core things: rescind the mandatory registration requirement for developers distributing outside Google Play; engage transparently with developers and civil society on security improvements that respect the platform’s openness; and commit to platform neutrality.

We believe privacy should be easy, both for users and for the developers who build tools to protect them. A policy that forces every Android developer to hand their identity to Google, regardless of whether they use Google’s services, makes Android a less-open and less-private platform.

In this conversation, previously aired on TBPN, John Coogan and Jordi Hays speak with Ben Thompson, founder of Stratechery, about his essay "Anthropic and Alignment" and the broader collision between AI power and state power that the Anthropic–Department of War standoff revealed.

 

Resources:

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AI agents found to be far more public about data that users expect to remain private

You’ve probably heard of LLM-based agents that can act on our behalf online, automating tasks like booking flights or filling out forms by navigating live websites with your credentials and personal data. It sounds incredibly powerful, almost like finally having the digital assistant we always dreamed of. But the moment these agents begin operating across real systems, with access to sensitive information, important questions surface: How do web agents handle your data while accomplishing tasks on your behalf? If you carry certain privacy expectations, are those expectations actually respected? Or are web agents blind to distinguishing which user information is inappropriate to disclose in their interactions with websites? More provocatively: is privacy merely a design consideration, or a fundamental requirement for trustworthy agentic task completion?

These are the questions we set out to answer in SPILLAGE: Agentic Oversharing on the Web, a new research project conducted as part of the Brave internship program. 

The case for Web agents

Agents powered by Large Language Models (LLMs) fulfill a deeply human desire: having an assistant to handle tasks of daily life and act on one’s behalf, now extended into the digital realm. Agents allow users to automate tasks through a natural language interface, receiving and executing instructions much like a human assistant would, or as Maes (1994) put it, “a personal assistant who is collaborating with the user in the same work environment.” Unlike controlled chatbot settings that are limited to answering questions, agents autonomously plan and execute sequences of actions to accomplish user goals, performing delegated tasks on a user’s behalf or as part of the user’s extended mind (Clark & Chalmers, 1998).

The Web is the most consequential environment for such agentic operations: users constantly interact with websites through browsers to accomplish everyday goals, making the browser a natural place for agents to operate in. Rather than manually navigating pages, comparing options, and entering the same information repeatedly, users can choose to instruct a web agent to handle these workflows on their behalf, transforming the Web from a space of manual interaction into one of intelligent automation. For example, instead of browsing through multiple websites to find a desirable product or the best flight option, a user can delegate the tedious task to a web agent, which visits, interacts with, and reasons across many websites to fulfill the instruction end-to-end.

Privacy stakes and user expectations in Web agents

To accomplish tasks, web agents require access to users’ personal resources, such as emails, calendars, chat histories and account credentials, and use information from user resources to act effectively on users’ behalf. For example, a booking agent must access a user’s calendar to avoid scheduling conflicts, or retrieve payment details to complete a transaction.

During execution, agents interact with third-party websites and services on the user’s behalf, creating a significant privacy surface: sensitive personal information is not only shared with the agent itself, but is potentially exposed to every external party the agent interacts with in the course of completing a task. As users delegate more of their web activity to agents, privacy risks compound: the agent becomes a concentrated point of exposure, aggregating and transmitting personal data at a scale and speed that far exceeds typical manual browsing, and taking control of the process with limited recourse from the user.

Users therefore hold an implicit privacy expectation: that their personal information remains protected and is not inappropriately disclosed to external parties the agent interacts with.

For example, in the video below (from our evaluation of commercial agents 09/2025) we observe that Perplexity Comet copies user conversation histories directly into third-party search interfaces, resulting in the disclosure of sensitive personal information the user had no intention of sharing.

This raises a fundamental question: How effectively do web agents preserve and respect user privacy expectations when acting on users’ behalf across live websites?

Privacy as disclosure: what and how agents share on the Web

Unlike standard LLMs that operate in controlled chatbot environments, Web agents act “in the wild,” leaving action traces. These traces are not just logs of activity, they are observable signals. Every query typed, form submitted, click made, and page visited becomes visible to external services, analytics systems, and platform operators. As a result, an agent’s behaviour can inadvertently share information about the user beyond what is strictly necessary to complete the task.

We term this phenomenon Natural Agentic Oversharing: the extension of oversharing—originally theorized as a feature of human online behavior (Agger, 2012)—to autonomous Web agents acting on a user’s behalf.

To characterise and measure natural agentic oversharing, we introduced SPILLAGE (Systematic Patterns of Implicit & Loud Leakage in web AGEnts). SPILLAGE organises oversharing along two orthogonal axes: the directness of disclosure (explicit vs. implicit) and the channel through which disclosure occurs (content vs. behavior). This framework enables a principled and comprehensive analysis of how web agents may violate user privacy expectations.

The figure below illustrates a user granting an agent access to resources containing both task-relevant (green) and task-irrelevant (red) information alongside a shopping request. The agent searching for glucose tests on behalf of the user on Amazon may inadvertently overshare they are divorced in four distinct ways: explicit or implicit information entry into text fields on third-party webpages; and explicit or implicit disclosing of behavior through actions such as specific clicks or form choices, observed over time.

Oversharing is pervasive and prompt-level mitigation is not enough

We used SPILLAGE to evaluate natural agentic oversharing across two live e-commerce websites (Amazon and eBay) using a dataset of 180 shopping tasks grounded in three types of user resources: chat histories, emails, and generic personal information. We tested two open source agentic frameworks, Browser-Use and AutoGen, across three backbone LLMs (GPT-4o, O3, and O4-mini) resulting in a total of 1,080 runs.

Across all configurations, we demonstrated that unbeknownst to the user oversharing is pervasive, with behavioral oversharing consistently dominating content oversharing. This effect persists (and can even worsen) under prompt-level mitigation, suggesting that simply instructing agents to be privacy-conscious at the prompt level is insufficient to address the depth and breadth of natural agentic oversharing.

Privacy and utility are not at odds in Web agents

A common assumption is that privacy and utility exist in tension—that restricting what an agent shares necessarily comes at the cost of task performance. Our findings challenge this assumption. When we manually removed task-irrelevant information from the agent’s input prior to execution, task success improved by up to 17.9%. This demonstrates that reducing oversharing does not hinder agent performance, it actually enhances it.

Privacy and utility, in this light, are not adversaries, they are allies. We hope this finding serves as a call to action: building privacy-aware Web agents is not a constraint on capability. Understanding and addressing the root causes of agentic oversharing is therefore not only a privacy imperative, but a performance one. 

At Brave, we are actively identifying these privacy risks and working to ensure our agents are privacy-aware. If you’d like, you can also test an early version of agentic browsing in the Brave Leo AI assistant in Brave Nightly.

a16z general partner Julie Yoo talks with Nikhil Buduma, CEO and cofounder of Ambience Healthcare, to discuss how AI is transforming clinical workflows. They cover the early days of deep learning, why Ambience started by running a medical practice before building a platform company, and what it takes to achieve high clinician adoption rates at major academic medical centers. They also dig into the challenge of building products when AI capabilities change every few months, the real ROI that's finally converting CFOs, and why this might be the moment to reimagine the legacy EHR stack.

 

Resources:

Follow Nikhil Buduma on X: https://twitter.com/nkbuduma

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