Optimization is one of the biggest opportunities in quantum computing. BCG projects quantum computing could create up to $850B in economic value by 2040. Optimization alone is estimated at $100B–$220B, comparable to the global cybersecurity or semiconductor equipment markets. D-Wave’s Advantage2 annealing quantum computer has 4,400 qubits and, with hybrid solvers, can support problems with up to 2M variables. Our roadmap moves toward Advantage3 systems with 20,000 and ultimately 100,000 qubits, expanding the size and complexity of optimization problems customers can tackle. The market is large. The use cases are real. And our customers are already seeing value. $QBTS #quantumcomputing

I’ve had a number of conversations with folks inside and outside government about the current situation with Anthropic, and here is what I believe to be true: — As we know, Anthropic publicly released its Mythos class models earlier this week under the commercial name Fable. — Fable is Mythos with guardrails. But if those guardrails fail, then you’ve exposed Mythos and its advanced cyber capabilities to people who shouldn’t have them. (Keep in mind that Anthropic itself widely promoted the idea that Mythos was a cyberweapon and needed to be regulated as such. They asked for government regulation of Mythos and championed the guardrails on Fable. If there is a vulnerability — big or small — it is Anthropic’s responsibility to patch.) — A highly credible trusted partner of both Anthropic and the USG who was testing Fable came forward with a jailbreak of those guardrails. The Admin asked Dario to fix the jailbreak or de-deploy the model. Dario refused. — In their blog post, Anthropic defended its decision by saying the jailbreak isn’t serious. That is not what the trusted partner and the USG believe; nor is that kind of minimizing language consistent with Anthropic’s brand as the AI safety company. It’s difficult to fathom how they could claim a jailbreak allowing operability of a cyber weapon could be defined as not “serious.” — In the past, Anthropic has always said that safety must be top priority and taken super seriously. In this case, Anthropic prioritized the continued offering of the consumer model over safety. — In reaction, the Admin issued the export control. The Admin did this reluctantly. It’s been very surprised that Anthropic hasn’t wanted to cooperate with a reasonable safety request (ie fixing the jailbreak issue). Anthropic’s reaction is very much at odds with their branding and ethos as a safe AI research community. — The Admin’s hope now is that Anthropic remediates the safety issue, the export control is lifted, and Fable goes back into general release. The Admin wants all of this to happen as soon as possible. It is frankly bewildered that Anthropic hasn’t wanted to comply with safety requests that it previously said were its highest priority. — Those trying to misdirect and tie this action to the prior DoW/Anthropic issues are wrong. The Admin values Anthropic’s technical capabilities and feels that this issue, while serious, should be easily resolved. The ball is in Anthropic’s court.

There will be an economic dislocation. But it won’t be AI taking your job. It will be someone who knows how to use AI to do your job better than you.

Love this.

This is how democracies die. It isn’t always a coup or happen at a clear moment in time. It happens slowly as the populace allows democratic norms to be reset towards authoritarian ideals.

Last week of our legislative session. At the capitol today briefing some of our friends in the legislature about our economic strategy.

The national debt just exceeded 100% of GDP for the first time since 1946: wsj.com/economy/u-s-debt-top…

I’ve wondered aloud whether the era of great leadership is behind us. Whether in a world of always-on discourse and exhaustive histrionics the truly great contemplative leaders could still emerge. @bensasse is the leader we did not deserve. Please watch this.

Kevin Warsh just said in his confirmation hearing that most economists started as a math or physics major but realized it was too hard. Ummmmmmm guilty. youtube.com/watch?v=mKAnk2XV… youtube.com/watch?v=mKAnk2XV…

Groton, Conn., suffered after Cold War military spending dried up 30 years ago. It’s being asked to deliver again. on.wsj.com/4cWWTnd

This is the future. Well done @Benioff

The global split we are seeing at OpenClaw is wild: In America, installing OpenClaw on your work computer gets you fired. In China, not installing OpenClaw gets you fired. Two completely different theories of the next decade.

The CEO of Y Combinator just open-sourced his entire AI development setup. And it is already at 72,600 stars on GitHub. Garry Tan runs Y Combinator. He has worked with Coinbase, Instacart, and Rippling when they were two people in a garage. Before that he was one of the first engineers at Palantir. He has seen more startups build product than almost anyone alive. He is now shipping 10,000 to 20,000 lines of production code per day. Part-time. While running YC full-time. In the last 60 days alone: 600,000 lines of production code. 35% of it tests. That number is not a typo. Here is exactly how he does it. He built a system called gstack — 23 AI tools that turn Claude Code into a full engineering team. He open-sourced the entire thing. Free. MIT license. One command to install. And then he posted the quote that explains why he built it: "I don't think I've typed like a line of code probably since December, basically, which is an extremely large change." — Andrej Karpathy, March 2026. When Tan heard that, he wanted to find out how. The result is gstack. Here is what the 23 tools actually do. There is a CEO tool that challenges your product framing before you write a line of code. It does not just approve your idea. It finds the 10-star product hiding inside what you described and pushes back on everything you got wrong. There is an engineering manager that locks architecture, draws ASCII diagrams of data flow, and forces hidden assumptions into the open before anything gets built. There is a designer that rates every design decision on a 0 to 10 scale, explains what a 10 looks like, and edits the plan until it gets there. It also has AI slop detection. It catches the generic AI output that looks fine and ships badly. There is a QA lead that opens a real browser, clicks through your actual app, finds bugs, writes regression tests, and verifies the fix. Not a simulation. A real browser. There is a security officer that runs OWASP Top 10 and STRIDE threat modeling with 17 false positive exclusions built in, so you only see findings that actually matter. There is a release engineer that syncs main, runs tests, audits coverage, pushes, and opens the PR. One command from approved to shipped. And then there is something Tan says was the biggest unlock of all. You can run 10 to 15 of these sprints in parallel. Each one in its own isolated workspace. One agent challenging a product idea. One implementing a feature. One doing QA on staging. Six more on separate branches. All at the same time. Tan's GitHub contribution graph for 2026 is a vertical wall. In 2013, building Bookface at YC from scratch, he made 772 contributions in a year. In 2026, he is at 1,237 — and still climbing. Same person. Different era. The difference is the tooling. One more thing. In the README, Tan quotes the number directly: 140,751 lines added. 362 commits. 115,000 net lines of code. In one week. Part-time. That is not what a solo developer looks like. That is what a team looks like. Except it is one person with 23 AI specialists and a GitHub repo you can clone right now for free. github.com/garrytan/gstack

There's never been an investment like the investment in railroads. (This graph has a log scale!)

🚨: New video shows Navy divers welcoming the Artemis II crew back home after splashdown

This is a remarkable chart about the future of computer science degrees. washingtonpost.com/technolog…

"So You Want to be a VC" Im enjoying this week in Boston visiting students promoting my new book - Runnin Down a Dream. Not surprisingly, many ask me about trying to break into venture capital. I wrote a letter answering this question 15 years ago. I would send it out when people inquired. I'm making it public for the first time - with zero modifications. 1) I think it holds up well 2) make sure and read my new book also 3) I probably can't help with followups (as suggested in the letter) Hope you find it useful. Good luck!

Running a company: 2020: can you survive a pandemic? 2021: still here? we’re going to give all of your competitors $100m series A rounds. 2022: wow, you made it? okay, all engineers cost $600,000/year now. 2023: nice job! okay, SVB failed and we’re going to take away your bank account. 2024: a survivor I see. but can you pivot from ai to crypto to defense tech back to ai-enabled defense tech in a 12 month period to stay relevant? 2025: unfortunately all of your competitors have raised $2b series B rounds. oh and only 500 engineers are relevant and they cost $100m/yr each. 2026: well, well, well. you’re still in business? let’s deploy the thunderclap of godlike LLMs from the heavens so all of your customers can rebuild your app in 2 hours. can you survive?