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[Max Branzburg @maxbranzburg]

Pre-IPO perps on Coinbase

[Brian Armstrong @brian_armstrong]

We registered the AI agent itself with the SEC as an investment advisor.

It has your complete context on your portfolio and account history. Speak to it in plain English to take action on your account. It will even prompt you with ideas you hadn’t thought of.

[Brian Armstrong @brian_armstrong]

Something that got missed in the noise last week: Coinbase got approved to offer true global crypto perps in the US. This took many years of work, and we're the first to offer this global liquidity to US users.

Backstory: For many years crypto trading has been moving offshore because the US didn't have clear rules, and perpetual futures were a superior product that traders wanted but it wasn't allowed in the US.

If we're being honest, probably ~half of all perpetual futures volume was Americans using offshore products via VPN with loose KYC controls (an open secret in the industry). Penalties for this were rarely, if ever, enforced, which as you can imagine, was frustrating for us as an American company following the rules. Others set up offshore entities and found ways around it.

After dozens of personal visits to DC, and many more from our policy team, I'm really proud we finally got approval to give US users access to true, global perpetual futures. This is important because we'll now see pooled global liquidity in perpetual futures, with the US and international markets being connected instead of fragmented.

Coinbase is strongest in the US, and the US is the largest market for trading, so there is now a chance to build a global network effect around liquidity. And US traders can now use these products in a compliant way with a US company, which hopefully provides greater customer protection.

Major credit to Chair Selig and Atkins on recognizing the importance of this for US capital markets. And we will keep working to update the system in a compliant way, and to be the best place you can trade.

[Brian Armstrong @brian_armstrong]

💪

[Brian Armstrong @brian_armstrong]

Excited to invest in @special and @natecavanaugh !

Let's bring more efficiency to the private sector as well.

[Brian Armstrong @brian_armstrong]

>1,000 enterprise merchants on @Checkout can now accept USDC and USDT, powered by Coinbase Payments.

Stablecoins are the cheapest, fastest way to move dollars globally. The more ways for people to pay with them, the better.

[Brian Armstrong @brian_armstrong]

Big day for our US-based traders, and for Coinbase.

Until now, US users have been locked out of ~80% of global crypto markets (perpetual futures and options). But not anymore!

Coinbase is the first and only regulated platform able to connect US users to global crypto options and perpetual futures (including Deribit options with >$31B in OI).

Thanks to Chairman Selig and @CFTC for making this possible.

[Brian Armstrong @brian_armstrong]

Major areas where the financial system still needs an update:

1. Tokenization of real-world assets - Real estate, stocks, bonds, funds, etc. onchain for instant settlement, fractional ownership & massive distribution.

2. 24/7 Global trading - Pooled global liquidity, every asset, every person, with great leverage and capital efficiency.

3. Next-gen payments - Near-instant, low-cost global transfers using stablecoins, including for Agentic payments.

4. AI-powered risk, credit, compliance, and advice - Better decisions, less fraud, and broader access to capital. Everyone gets access to a great financial advisor.

5. Innovation friendly regulation - Move from one-size-fits-all to risk-based rules that encourage innovation and competition instead of stifling it.

6. Expanded access - Open protocols that reduce middlemen and self-custodial wallets to expand access to everyone with a smartphone.

7. Capital formation - Low cost and turnkey for anyone to raise money for a good idea, increasing the number of startups.

8. Sound money - A refuge from inflation, when discipline is lost in fiat money.

Jobs not done until we get these working for all.

Will require lots of tech innovation and policy work to get there.

[Coinbase 🛡️ @coinbase]

Back in 2010, 10,000 Bitcoin got you 2 pizzas.

Now it would get you over 40 million.

Here's what that would look like.

[Dor @dorvonlevi]

Building an AI-native @Coinbase means rebuilding everything, especially the hardest parts. We've put a lot of time into redefining compliance, where the stakes are incredibly high, and we have to be extremely thoughtful about implementation.

We have invested heavily in rebuilding our compliance ops around AI with that reality as our starting constraint, not an afterthought. Here is an overview of what we've learned and what we built.

Most people assume compliance work is mostly checking whether a name appears on a sanctions list. That is the easy 5%. The other 95% is interpretive judgment under uncertainty: a customer claims their wealth came from real estate. Do the property records actually support it? Does the timeline hold? Is the documentation legitimate, or does it feel too polished? You need compliance staff and investigators who understand what “suspicious” actually looks like in context.
That's part of why compliance is so hard to automate—and so expensive.

The first obvious AI approach is to hand the model the existing procedures and ask it to run them faster. That approach misunderstands what procedures are for. Good procedures are not bad investigations; they are deliberately incomplete investigations. Their job is to create consistency, auditability, and a minimum standard across thousands of cases. They excel at saying what must happen. They are far worse at capturing everything a strong analyst actually notices: which sources they trust, when they widen the search, when a document feels off, when an explanation technically fits but still does not feel earned.

Procedures also carry the shape of the old operating model: fragmented systems, time pressure, queue pressure, and the hard limit of how much one human analyst can read, cross-reference, and hold in working memory at once. That is not a flaw in the procedure. It is how you design a process for humans.

AI changes the constraint set. Reading, searching, comparing documents, and tracing inconsistencies no longer have to be treated as scarce analyst time. Done carefully, with proper controls and human review, models can explore more context, test more hypotheses, and surface more inconsistencies than any single analyst could reasonably do case by case.

So if you simply automate the procedure exactly as written, you may gain efficiency. You will not unlock the full value of AI. You will just make the old bottleneck run faster.

The better question is not “Can AI follow the analyst playbook?”

It is: once the cost of reading, cross-referencing, and testing hypotheses collapses, what should the investigation become?

A second tempting approach: feed it historical Suspicious Activity Reports (SARs) and let it learn from outcomes. This breaks down too. You rarely have the full state of what the analyst actually saw during the investigation. A case that looks straightforward today might only look that way because information surfaced later. A fraud indictment that didn't exist when the original analyst made the call, news articles that hadn't been published yet. Hindsight can contaminate your training data. Also, regulators themselves acknowledge that SAR decisions can be subjective.

The architecture has four layers. The first is data: continuously enhancing the coverage, quality, and architecture of the signals the system depends on. The second is classical machine learning models that cluster and classify alerts to determine what type of investigation needs to run. The third is the investigation agent itself: a multi-agent system that orchestrates specialized agents to execute the investigation end to end. The fourth is a safety filter that runs independently of typology, ensuring no risk vector is missed regardless of how the alert is classified. Each layer is independently auditable and learns from the feedback provided by human reviewers.

Inside the investigation agent, specialized sub-agents run across the full case surface: alert context, customer and identity signals, access patterns, risk indicators, transaction behavior, source-of-funds, onchain activity, and public adverse media. Each writes its findings into a shared case memory. A coordinator agent reconciles and challenges them. When sub-agents disagree, such as when source-of-funds marks activity as “explained” while adverse media surfaces a recent indictment, the coordinator attempts to resolve these disagreements knowing the common patterns. The narrative agent prepares the final report with all collected evidence and suggested resolution. The last self-validation agent acts as a guardrail: if the system cannot support its conclusion with sufficient confidence or data quality, the case is routed to manual investigation instead of being surfaced as an automated result.

Before any of this touched a real customer case, we built what we call a “Golden Set” - historical cases with known right answers. "Known right answers" in compliance is harder than it sounds. It meant re-investigating old cases, getting multiple senior analysts to independently agree on what the right call would have been, then debating the disagreements until consensus. Months of work before we could even start measuring.

Here's an important part (for now) - cases currently get BOTH the AI's full investigation AND a senior human review. We didn't reduce scrutiny, in fact, we added more of it until it no longer proves valuable. Cases resolve significantly faster AND get more eyes than they ever did before. Every human correction feeds back into the model as a training signal. It gets better because it's wrong in front of people who know how to fix it.

None of this would have shipped without clearing structural blockers most financial institutions are still stuck on. Security and privacy sign-off to send customer data to LLMs at all. Senior compliance officer alignment on AI-assisted human decision making. Model Governance team embedded since December - they observed the entire Golden-Set Evaluation process and are running a formal validation review with our Internal Audit team now.

Today this handles roughly 55% of our US fraud case volume with significantly less analyst time per case. Time freed goes to the harder cases AI can't yet handle - and to teaching it.

Our internal compliance and quality teams are the ones who are building this system with the engineers, training it, validating it, and continuing to shape how it improves. In the process, they've developed skills that are incredibly valuable: how to design evals, how to think about model bias, how to think about human bias, how to architect human-in-the-loop systems, skills that are becoming among the most valuable at any company.

This entire project started ~6 months ago with a whiteboarding session between @galpa42 and I, and was built by an AI-pilled cross-functional and it’s just the first pod - there's a multi-month roadmap,rebuilding compliance from the ground up with AI. Huge thanks to everyone involved and congratulations to @galpa42 for shipping two babies to production this month :)

The future of high-stakes work is not AI replacing judgment. It is AI making judgment scalable, auditable, and continuously improvable.

[Emilie Choi 🛡️ @emiliemc]

Coinbase is the settlement, distribution, and commerce layer for the agent economy.

[Max Branzburg @maxbranzburg]

The Everything Exchange means Everything

Coinbase is the best place to trade every asset class - millions of crypto assets, equities, commodities, perps, prediction markets, and more

Trade it all out of a single account without having to transfer funds

[Cathie Wood @CathieDWood]

In our view, $TSLA, $PLTR, $COIN, and $SHOP are at the tip of the spear as technologically-enabled innovation disrupts and displaces the old world in equity benchmarks. Benchmarks are likely to chase innovation at an accelerated rate in the years ahead.

[Coinbase Support @CoinbaseSupport]

Reminder: Beware of recovery phrase scams.

We're aware of new phishing emails going around pretending to be Coinbase and Coinbase Wallet.

We will never send you a recovery phrase, and you should never enter a recovery phrase given to you by someone else.

[Max Branzburg @maxbranzburg]

We’re excited to bring Coinbase One onchain alongside some great partners like @MorphoLabs, @AerodromeFi, @MoonwellDeFi, and a whole lot more.

This is rolling out over the next couple of days. Stay tuned.

[Paul Grewal @iampaulgrewal]

We finally got the unredacted OCP 2.0 letters from @FDICgov. It took a Court order but you can now read them for yourself below. They show a coordinated effort to stop a wide variety of crypto activity — everything from basic BTC transactions to more complex offerings. 1/3

[Brian Armstrong @brian_armstrong]

This would help

Honestly, getting rid of individual income tax entirely would be ideal, shifting tax reporting burden to businesses instead. Try to generate equivalent revenue via a sales tax, or on business income, etc.

It's kind of crazy that we ask every adult in the U.S. to figure out how to pay their taxes - the tax code is ~150k pages long and no single person fully understands it. Would be better to offload this burden to the 10k largest companies, instead of asking 200m adults to figure out a complex accounting task annually.

[Senator Cynthia Lummis @SenLummis]

We are building a pro-crypto army in Congress.

[Paul Grewal @iampaulgrewal]

71 House Democrats. Let that sink in— 71 House Democrats just joined Republicans to defeat the scape goating, fear mongering and ignorance of fellow legislators who refused to legislate. Thank you Congress— FIT21 is real progress.

[Coinbase 🛡️ @coinbase]

Thanks to you, FIT21 has passed with strong bipartisan support in the House.

This Act will protect consumers and foster innovation & job creation by providing clear rules for crypto.

And while this is just step 1 in turning the Act into law, let’s celebrate this historic win.