Uh oh...I’m sorta getting Zuck pilled... Honestly, I didn't like him, but Zuck 2.0 I think I can get behind. First, he’s one of the only tech executives painting a genuinely positive picture of an AI future. We desperately need more optimism like this. Meta is also one of the few major AI producers willing to release open-source models, and even their API has become more transparent than other labs. Their latest models have a super-low-priced “contributor tier”: you get cheap inference in exchange for letting them train on your data. This is so refreshingly honest. I also love that he seems more concerned about AI becoming centralized than about controlling it himself. History gives us plenty of reasons to be skeptical of concentrating too much power in too few hands. Finally, and this might be my favorite: he still has the courage to stand on a stage in front of a live audience and demo his products. Meanwhile, Apple has lost much of its connection with its biggest fans and prefers to hide behind polished prerecorded videos. So yeah, I’ll stay a skeptic, but Mark—I’m cheering for you.

Ok...maybe localmaxxers aren't crazy. This one-shot is from my M5 Max (@inco_ai 3.8 splash). Took 20 minutes. Vite 8, Tailwind 3, on Cloudflare workers with KV store and a working admin area.

I’ve never been this excited for a product. We’ve dramatically re-thought Standard Code. It’s a game changer now, nothing like what we originally announced, and will dramatically change the way you work. Sorry for the extra delay, but this is worth the wait, I guarantee it.

Good lord...@Dpbrinkm can edit! Now i'm even more jazzed to be speaking at this. Come join him, and me, @dsp_, @techgirl1908, and lots more @AgenticAIFdn's AGNTCon in San Jose. Oh, and DM me if you want 10% off, I have a code!

Friends at @OpenAI and @CloudflareDev, does OpenAI block Cloudflare's data center IPs from using the codex endpoint? Trying to do a fun hobby project with my sub and it fails with this error 9/10 times.

🚨 DO NOT pay API prices for Anthropic models. 🚨

It's clear the Chinese know how to use AI better than us now.

So excited to be presenting on domain specific agents at AGNTCon (San Jose) in just a month! Please come hang out!

I really doubt Jev is a 0.5B model like some of these open-source alternatives. I’m going to stay skeptical of the LLM-turned-System One models for now. We need a lot more tooling and broad benchmarks.

I’ve put a ton of tokens through Jev now, and...I have thoughts. 1. The big labs lost the script TypeSafe’s intro video says, “We’re building prod, not God” — and can I just say? Hell yeah. @typesafeai built something for engineers like me, so I can build products for people like your mom (she says hi btw). They’re not trying to create “Machines of Loving Grace”; they’re trying to build things that let OTHER HUMAN BEINGS create new types of products. The proof is in the pudding. When ChatGPT shipped, we were all blown away by…ChatGPT. When Jev shipped, we were all blown away by what everyone was making with it. I cannot tell you how refreshing this is. It takes a sincere form of humility to believe that you, the creator of a technology, will not be the best at deploying the technology into the marketplace. The big labs, especially Anthropic, have proven not to have this humility…and now everyone hates AI. Thanks, Dario. I guess what I’m saying is: Diogo for president. 2. Ultra-smart classifiers were genuinely a missing primitive. I don’t know how this got missed. Diogo calls it “machine-native intelligence,” and that’s really what it is. I cannot tell you how much bending and twisting I've had to do with LLMs to get them to act like a classifier when they just weren’t. I’m absolutely shocked this is the first time this “type” of model has come to market. These models will unlock AI utility for entire industries: robotics, trucking, aviation, meteorology, finance, defense, retail…even your smart coffee mug is going to use this. 3. It’s still too expensive Jev is really, really cheap compared to LLMs. But you don’t use it like an LLM. In my full self-driving example, or any robotics example, you’ll be making decisions several times per second continuously. The #1 value proposition of a model like this is speed and cost. To be clear, at current pricing, the model will still be successful and well integrated. It will be able to replace a number of tasks that were already being performed (poorly) by LLMs. However, to unlock industrial-scale demand (Jevons paradox), I believe it needs to be roughly 10x cheaper. Currently, Jev is $0.042/M input, which is actually 7x more expensive than a cache read on DeepSeek V4.1 Flash ($0.006). If our industrial application requires decisions at 10 Hz and we provide only 10k of context, that would cost $0.0042/second to operate, or $15/hour, $600/week, etc. The good news is Diogo said on a recent AMA that they have substantial margin at their current pricing and have already considered dropping the cost further. I hope it's a lot further. 4. Latency is a real limiter I really hope TypeSafe AI works with an edge network provider to improve the co-location of models and reduce network latency. Ultimately, these models really need to run on-device. I would even be willing to pay some kind of recurring license fee to have a great closed model running on my own hardware, just so I can reduce the TTD (Time To Decision) as much as possible. Imagine running a model like this at 60 Hz, or even 120 Hz. At that point, we’re looking at a new kind of logic gate — we can’t even imagine what that will be like. In summary, this one really is a game changer for everyone building AI products, and, assuming cost and latency are further improved…it’ll be a game changer for everyone doing anything.

So far this week I have: - Maxed out $200 Codex Sub - Maxed out $200 Claude Sub - Maxed out Grok Bot - Done 15k Jev requests for $1.24

Tesla Full Self Driving (Jev demo) is now open source and you can try it online yourself! jevpilot.standardagents.ai 👈 try it github.com/standardagents/je… 👈 keep it