Introducing the Fusion API, the smartest compound model in the market. Fusion achieves Fable-level intelligence at half the price. How it works 👇

Hear the exact moment Manhattan lost its mind

My favorite @elonmusk quote that I often send friends: Do not fear losing. “You will lose,” Musk says. “It will hurt the first fifty times. When you get used to losing, you will play each game with less emotion.” You will be more fearless, take more risks.

Tesla FSD 14.3.4 rolling out now

Teams are go for launch with a $135 price per share for the SpaceX IPO → spacexipo.com/#priceannounce…

Introducing coding sessions. Linear Agent can now triage issues, investigate the cause, write the fix, open a PR, and bring the code back for review. All shared with your team in Linear.

Fresh off bond sale, Amazon borrows $17.5 billion from banks as AI spending continues techcrunch.com/2026/06/10/fr…

Fable 5 is the biggest step up I’ve felt in our models since Opus 4.5 back in November. After 4.5 came out I uninstalled my IDE when I realized that I’d been doing 100% of my coding in a terminal for a few weeks. With Fable, it’s felt like Claude has stepped up from being a coding agent to a thought and design partner in building the product. Fable has judgement, taste, and dimensionality in a way that previous models didn’t, leading me to trust it more with the most complex work. I think the first time I had this realization was when I asked Fable to debug something. It is the first model I have used that was so methodical and precise, taking measurements and adding logs then verifying that it truly fixed the issue before declaring victory. There’s nothing in claude code’s prompting telling the model to do that, it’s just part of its personality. It really has this “big model smell” that I haven’t felt before.

Most work conversations are now being recorded by default. You should probably assume that everything you say at work is getting recorded from here on out. What’s emerging is a new category of enterprise software, organized around voice instead of text. The system of record today is structured data: CRM entries, tickets, docs. But the highest-value context lives in conversation: the nuance on a customer call, the real argument in a product review, the offhand comment in a leadership meeting that quietly changes the roadmap. LLMs are uniquely good at taking that unstructured voice data and making it structured, searchable, and queryable. That’s a large enterprise opportunity, and we’re still early in understanding what the software layer looks like and who owns it. a16z GP David Haber on what AI recording means for the future of work: a16z.news/p/everything-is-re…

Our Anthropic bill is about to jump from $400K → $1.4M/yr. Not because usage exploded, but because we're about to cross 150 seats. Past 150 seats you're forced into Enterprise tier. Seats stop including any usage, every token bills at standard API rates. At our current run rate that's 3.5x overnight. Unfiltered thoughts on AI spend: 1. We should spend tokens to grow as aggressively as possible. But most people (me included) aren't conscious of what they're spending. 2. Visibility comes first. People see their personal number and they're shocked. I accidentally spent $4,000 in 3 days in Claude Code. 3. For engineering the spend is clearly worth it. Pay for the best model, it saves more than it costs. 4. For a lot of other roles it's questionable. Apps nobody uses, skills someone already built. No ROI. 5. Spend limits are coming. We already require approval for more tokens on our support team. The era of token-maxxing is coming to an end.

It's even better in slow motion 😏

This is a super exciting release - Claude Fable 5 is the same underlying model as Mythos but with added safeguards. The benchmarks are great and it's SOTA on everything by a margin but I'll add that *qualitatively* also, this is a major-version-bump-deserving step change forward (imo of the same order as Claude 4.5 was in November), peaking especially for long problem-solving sessions on very difficult problems. You can give it a lot more ambitious tasks than what you're used to, the model "gets it" and it will just go, and it's never felt this tempting to stop looking at the code at all (but don't do this in prod!). The model still has quirks that people will run into and the safeguards are configured to be a little too trigger happy for launch, which can hopefully be tuned over time. I feel a lot of things changing as working software increasingly comes out on a tap. The Jevon's paradox kicks in and I feel my own demand for software growing substantially. You can ask for anything - explainers, visualizers, dashboards, bespoke single-use apps (e.g. a full wandb that is hyper-specific just for your project), you can 10X your test suite, auto-optimize code, run giant research projects with custom HTML for the results, anything! "Free your mind" (Matrix ref). Really looking forward to all the things people build!

BREAKING: Anthropic just dropped Claude Fable 5—this is Mythos, made safe for public release. It is the best coding model in the world. We've been testing it internally @every for the last week or so across coding, writing, marketing, editing, and more—here's our vibe check: - It broke our benchmarks. Fable scored a 91/100 on our Senior Engineer benchmark—this is human senior engineer level. The previous high score was Opus 4.8 at 63. GPT-5.5 is a 62. - It's a one-shot wonder. You can set it and forget for hours or overnight on huge coding tasks, and come back to completed work. It cleared entire production bug backlogs, built a playable 3D, and even made a 2-minute animated film—all one-shot. - Taste and attention to detail. In coding and knowledge work tasks, it has much better taste and attention to detail than we've ever seen. It gets subtle things right, adds little features you might not have thought of, and generally understands the assignment in ways that surprised us. - Great use of context. We set it loose analyzing customer feedback surveys and our website data and it came back with a crisp, clean report that identified a. our biggest problem and b. a concrete testable solution—and then we sent it off to build that. - It's best for power users. If you're already used to orchestrating multiple agents in your work, this model can do things that you've never seen before. If you're a knowledge worker or vibe coder with a more basic setup, you're not going to notice a huge difference—in fact, it probably isn't the right model for you. - It's very slow, token-hungry. Using this thing for regular knowledge work is like squashing an ant with a rocket launcher. It also routinely uses 500k to 1M tokens on tasks. That's why it's best for your heaviest jobs—but not as good for tasks like collaborative writing. - It's expensive. It's about twice as expensive as Opus, and it's also incredibly token hungry—so expect it to be something you'll use sparingly unless your company pays for it. Overall, I think of it like a warp drive for coding: It can get you across the galaxy in a few hours, when it used to take months or years. But it's not appropriate for getting around town—you need something faster, cheaper, and more maneuverable. The ceiling is extraordinarily high on this model though. Even our most advanced testers like @kieranklaassen felt like they were only scratching the surface of it. Want our full vibe check with all of our testing and benchmarks? Read it on @every: every.to/vibe-check/anthropi…

AI won’t make most human skills obsolete—but it will change how they’re used. Negotiation, leadership, and problem solving may become even more important as AI changes how work gets done. The question now is which skills matter most next. mck.co/4e6MPID.

the new world order

It's very cool that Apple shipped a 20B parameter on-device. You can't put 20B parameters in RAM at any reasonable precision. To make it work they are using pretty exotic architecture by today's standards. A small model predicts from the query (or prompt) which experts to load from Nand into RAM. The key distinction from a typical MoE is that you do this once per query and then generate all the tokens with the same experts (instead of switching the experts for every token).

I'm a cardiologist. I've held dying hearts in my hands in the cath lab at 3 AM. And I need to tell you something that changes everything about how we prevent heart attacks. For decades, the entire field was built on one target: lower LDL cholesterol. Statins save lives — that's settled science. But too many of my patients did everything right — took their statins, hit their numbers, lived clean — and still ended up on my table with a ruptured artery. We were treating the smoke while the fire kept burning. The fire is inflammation. And the evidence is now overwhelming. The CANTOS trial proved it first — lowering inflammation independent of cholesterol reduced cardiac events. But the newer data is what keeps me up at night. AI-enhanced CT angiography can now detect inflamed arteries by measuring changes in the fat surrounding your coronary vessels — the perivascular fat attenuation index. Higher inflammation in the fat around even one artery independently predicts cardiac death. When multiple arteries show inflammation, the risk multiplies dramatically — even in patients whose cholesterol looks perfect. This isn't theoretical. This is measurable. Right now. On a scan you can get this month. Low-dose colchicine — a drug that's been around for centuries for gout — is now FDA-approved specifically for reducing cardiovascular events. It works by quieting the inflammatory cascade that destabilizes the plaque sitting in your arteries. A pill that costs pennies is saving lives the statins couldn't reach. And the next wave is already in Phase 3 trials. Ziltivekimab — an IL-6 inhibitor — targets the central inflammatory pathway driving atherosclerosis. Phase 2 data showed a 90% reduction in hsCRP. The ZEUS cardiovascular outcomes trial is enrolling now, with results expected late 2026 into 2027. If positive, anti-inflammatory therapy will become standard in managing heart disease alongside lipid-lowering. The era of inflammation-targeted cardiology is arriving. But it goes deeper than drugs. AI is now predicting heart failure and cardiac events 5 years before symptoms — integrating CT imaging, electronic health records, and genetic data with accuracy that jumps far beyond traditional risk calculators. And polygenic risk scores — a simple genetic test that flags inherited cardiovascular risk — are now formally recognized as a risk-enhancing factor in the 2026 ACC/AHA guidelines. A single blood draw can reveal risk that's been silently building since birth. Decades before the first chest pain. Here's what this means for you right now — today: Ask your doctor for a high-sensitivity CRP test. It's cheap, routine, and measures the systemic inflammation that standard cholesterol panels completely miss. You can have perfect LDL and inflamed arteries that are quietly preparing to rupture. If your hsCRP is elevated, discuss low-dose colchicine with your physician. It's FDA-approved for exactly this. Push for a coronary CT angiography with AI plaque and inflammation analysis if you have risk factors. This isn't the stress test your parents got. This is 3D visualization of your actual arteries — with AI quantifying not just how much plaque you have, but what kind it is and whether the surrounding tissue is inflamed. Consider polygenic risk score testing — especially with a family history of early heart disease. It's now guideline-supported. And the foundation that never changes: move daily, eat real food, sleep 7-9 hours, manage stress, and know your numbers — ApoB, Lp(a), hsCRP, fasting insulin. I left Iran as a child with nothing. I rebuilt everything in a country that gave me the freedom to become a physician. I've spent twenty years watching patients get second chances. The ones who haunt me aren't the ones who died on my table. They're the ones who survived but never acted on what the science was telling them — years before the event that didn't have to happen. You can have perfect cholesterol and still have a heart attack. Inflammation plus genetics can drive plaque rupture in arteries that look "fine" on a standard panel. The myth that normal cholesterol means you're safe has cost more lives than I can count. We now have the tools to detect the fire — not just the smoke. AI to see it. Genetics to predict it. Drugs to quiet it. And the ancient basics — movement, real food, sleep, purpose — to prevent it from starting. Prevention is the new cure. And the science to make it real is no longer coming. It's here.

SpaceX has just officially unveiled its AI1 satellite, the first generation of its AI satellite. Overall Specs: • 150 kW peak compute payload • 120 kW average compute payload • 70 kW per ton • Compute provider interchangeable Dimensions: • Wingspan: 70 meters • Deployed height: 20 meters Thermal System: • 110 m² deployable liquid radiator • Redundant pumping loops • Integrated micrometeoroid shielding • Deployable liquid radiators Solar Power System: • 150 kW solar array • 250 W/m² • SpaceX-manufactured solar technology from Bastrop, Texas Architecture: • Centralized compute module • Large deployable solar arrays • Deployable liquid-radiator thermal management system • AI-focused compute satellite design ("AI1 satellite") Elon: "The AI satellite is much simpler than a Starlink satellite. The AI satellite is essentially a lot of solar cells, you still need some laser links, but you don't have all of the super complex antennas that you have on a Starlink satellite. The easier one to design for is the AI satellite. It's bigger. A lot of this is technology we've already made with the Starlink V3 satellites."

Knicks Game 2 celebrations can literally be heard from NJ #whatisnewyork