This prompt is amazing! 🔥🔥

Right up until we get an incredible design process with the most beautiful interfaces - only to have everything become agent-first on the Internet so no humans even see it… 🤷‍♂️

Made my portfolio's front door a cozy little computer. - No realtime 3D, just 57 Blender renders - CRT shader over the live site, 11.6 KB of JS - 0.2 ms of JS time per frame Click the screen to go in. Dunno if I'll keep it as it's not very practical, but it's cute!

A big trend with most enterprises that I talk to is deploying internal FDEs into departments in their organization to help bridge the capabilities of AI into their underlying workflows. This requires a high level of technical expertise, an understanding of AI, and the ability to understand the workflows and processes that the enterprise is trying to automate. There’s no shortcut to getting automation without this combination of skills (either in one person or multiple). What’s exciting is this is an entirely new function in most enterprises, which is going to create a ton of new roles in the economy. “Every generation of technology creates jobs that didn't exist before it, jobs that arise from an immediate need in an emergent industry. The Automation Engineer is a key example of those jobs for this generation. Nobody has ten years of experience doing this yet, because ten years ago the tools that made it possible didn't exist (it didn’t even exist two years ago).” If you have software skills and are diving into AI, this is an area to go deep on.

You can now mod Claude Code: - Change how it behaves - Customize the UI - Swap in your own features Write one with a few lines of TypeScript, or have Claude build it for you. Mods ship inside plugins, so you install them with /plugin in the CLI or desktop app. A few examples:

Today we give Atlas dexterous hands, with the strength to take on real work, and the simplicity for mass manufacturing. Like the body, the hands are designed with high fidelity simulation in mind, to enable sim-to-real RL. If you give dexterous hands to a robot, make them do dexterous things. More thoughts here Blog: bostondynamics.com/blog/robo… Video: piped.video/watch?v=4whgw2gL…

Zoom meetings are cooked, then all meetings as the AI agents can just sync up in the background constantly 💀🤷‍♂️

Protein deficiency and low muscle mass are huge drivers of mortality. Bet you never heard that from your doctor.

"Nothing sugary for 24 hours before the scan. No bread, no pasta, no fruit, no juice. Then nothing at all for six hours." Why? "We inject you with radioactive glucose. We need the tumour to be hungry for it." The tumour gets hungry? "Cancer cells take up sugar far faster than healthy tissue. That's how we find them. They light up." So if I ate a bowl of cereal first? "It would spoil the picture. The tumour would already be fed." Right. And after the scan? "You can eat normally." Normally being? "We've a trolley coming round. Tea, biscuits, a bit of cake." So for one day you'd like the tumour kept hungry. "For the scan, yes." And for the rest of the year? "A balanced diet. Plenty of starchy carbohydrates." Is it the same tumour on the other days? "...It is." Does it lose interest in sugar once the photo's been taken? "I only do the scans." Two sugars, then, is it?

My first OBSERVATIONS from Sundar's Gemini 4 Argon announcement: 1. Quantum. Google's quantum researchers gave Argon a key piece of quantum software to shrink, and in minutes it found a version that needs 40% fewer qubits and operations than the best published human solution. Quantum computers are useful ONLY once programs fit on the hardware, so this pulls that date closer from the software side, and it also shortens the time banks and governments have to switch to encryption quantum can't break. 2. Data center memory. A team of Argon agents read Google's server data, found waste, and freed over 300 TiB of memory on their own, with up to 1 PiB expected. If agents can do this everywhere, companies will point them at their cloud bills before buying more servers, and some of the huge data center buildout may turn out to need less hardware than planned. 3. Rewriting old code. Argon agents are converting Google's old C and C++ code into Rust, a safer language, including an 800K- ine operating system kernel. There are PLENTY of companies stay with outdated software vendors only because switching is painful, and once rewriting is cheap, that lock in starts to break! 4. Faster than the engineers. On one video decoder, Argon ran 100s of experiments and ended up 2.7x faster than the version Google's own engineers wrote. Speeding up your slowest code used to take a specialist team, and now it's something you can run overnight and pay for based on the savings. 5. Million-token answers. The most a model could write in one answer went from 64K tokens to 1 million, enough for a whole codebase or a full due diligence report. Obviously, nobody can carefully review that much output, so the bottleneck moves from making things to checking them, and tools that verify AI work become a big market. 6. Two versions of the same model. Vetted security teams get Argon with the cyber safety limits removed, and everyone else gets the restricted one. The best defense goes to big trusted organizations first, which leaves smaller companies more exposed and creates demand for services that get them "trusted" status. Gotta think about this more and what it means. 7. Finding bugs faster than anyone can fix them. Wiz used Argon to find a serious security hole in hospital software used worldwide that every earlier model missed. When AI can find holes this fast, the pile of known but unpatched bugs becomes the real risk, and whoever makes patching fast wins. 8. Legal work. On Harvey's legal benchmark Argon scored 19.6%, and every other top model was under 7%, the biggest gap in the whole chart!! Harvey, a startup, built that test, and now Google launches on it, so owning the benchmark in your industry gives you leverage over the labs. 9. Promo pricing. It launches at $2 in and $10 out per million tokens, about a 20% ish of GPT6's price, and then doubles. Startups that set their prices on the promo rate will see margins shrink in a few months, even though everyone assumes AI only gets cheaper. 10. Cheap memory. Reused context is 95% off. Products that keep one big shared knowledge base and reuse it across users will run far cheaper than rivals that resend everything each time. 11. Watching the model. Google seals Argon's test environment before training, watches its reasoning live, can stop it mid task, and asked other labs to keep reasoning readable. Companies running their own agents will copy this, and monitoring and permissions for AI agents turns into its own product category. 12. Government first. The US government gets access before the public through a voluntary review. DC is pretty much the first customer now, and launch dates start depending on its review, not only on when the model is ready. That's the new normal, I guess since the Fable/Mythos debacle. I'll share more on Gemini 4 as it comes out on @startupideaspod Never a dull moment in AI, isn't it?

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Introducing Gemini 4 Argon – our new frontier model. It’s built for complex workflows across coding, enterprise knowledge work, and cybersecurity defense – rolling out today to a set of trusted testers through our Fairwind Program.

For Plus users: give GPT-6.1 Sol a real shot through ChatGPT Work or Codex. The model is seriously good, extremely capable, and barely eats through your usage. That means even on Plus, you can actually get a lot of real work done with it without constantly worrying about burning through your limits.

Using a version of this prompt with @Muse is really cool 😎

- Updates to the app are nice but don’t need an event - Sol 6.1 is what Sol 6 should have been, so that’s just a fix - Dots should have been a beta for Pro users right after Grokbot came out, but now Muse will eat their lunch by the time OpenAI offers it all the way down to free tier (if they even can) 🤷‍♂️

OpenAI have accidentally hit publish on their complete DevDay summary early openai.com/index/devday-2026…

Today we’re launching America.gov, a single front door to the federal government. Instead of opening a bunch of tabs across different agency sites and trying to figure out which information actually matters to you, you can ask America a question and get the relevant answer from across 29,000+ official government websites, with the source and what to do next.

Henry Malukas, co-founder of HMD Trucking, which operates a fleet of ~700 diesel semi trucks, says the company has ordered 50 @Tesla Semi trucks. "It’s an amazing product. It’s efficient, low maintenance, also the fuel cost. It's unbelievable. And for the driver, I think it’s a dream come true. Yeah, it’s like nothing we’ve ever seen, and I don’t think anybody is going to see for a while, anything like that. It’s just going to be next level,” said Malukas. "It works for a long haul; any kind of trucking, for any kind of use; it’s going to be electric. I think for the [electric] cars, when they came out, people had a preference; they had their emotional attachments. Here, when this rolls out to businesses, when they understand what it does, and the costs and all that stuff, that will take off in the market because there are no emotions. The owners of the company look at the bottom line, and we’re going to excel at the next level. I mean, this is a miracle in my eyes. I test drove the thing, and it’s a dream. This is a game changer that’s coming, 100 percent. And I hope everybody else will catch up to give Tesla some competition. But right now, everybody is far behind,” said Malukas. motortrend.com/features/why-…

Today we are launching Muse for Small Business, a collection of connectors that allows businesses to run, grow, and create new opportunities. Every great American boom is the same story: scarcity becomes abundance, and GDP takes off. In 1865, moving goods across America was scarce. Then rail track grew from 35,000 miles to over 192,000 by 1900, freight volumes tripled in thirteen years, and a farmer in Kansas could suddenly sell to a buyer in Boston. Communication went from scarce to abundant with the telegraph, then the telephone, so a shopkeeper could check prices, place orders, and chase debts without leaving the counter. Steel went from precious to plentiful: by 1913, American mills out-produced all of Europe, which meant cheaper buildings, cheaper machines, and cheaper tools for every workshop in the country. Each scarcity that fell unlocked a wave of small enterprises, and AI is giving us another wave. Building Muse for Small Business is a step toward how we make that abundance again: every business owner gets the tools and firepower that used to only belong to large companies. We've seen this movie before, and it always ends with more prosperity than the pessimists thought possible. The future is for everyone and today we're excited to accelerate that future muse.ai/business

Sonnet 5.5 C++ skate game, self contained no deps.