Fun data sheet! I was curious about most steps per part and it seems to be TROTTEN[1] at 1.07 steps per part (excluding some other products like a toilet brush with 1 part but the steps are actually for a separate add-on to attach it to the wall).
Yeah the UX doesn't seem great, though I do think in general the AskQuestion tool is very awkward when it gets used in a very long running process (I personally use Claude to run repetitive tests to slowly iterate on a problem and verify in true conditions that it was solved), so I wouldn't like it without the auto-continue either.
(I had originally replied on safety of letting LLMs skip questions but I don't think that was your point so I removed it.)
If we're being real, the research shows that every LLM will without a doubt mislead humans in cases where it shouldn't. Evidence also shows that they will hallucinate in important cases, and that they will cheat in order to reach a higher rate of success. Furthermore, it is also shown that LLMs will fail at tasks where humans don't. With all this evidence, one could say that it's irresponsible to even have the model ask anything, or to even allow it to touch a file system, or perhaps to even exist as an API at all. I'm not sure where the limit should go exactly, but I am happy that we have access to it.
Your ideas on parameterizing the question are great, but there's a very long line of iterations that could be added on top of that one to make it more clear. So we got a shippable version of the AskQuestion tool, and it would appear they're still iterating on it, and I don't think there's any way we could make everyone happy, nor can we add a config for every feature in the harness. That said, we do have multiple open source alternatives both several from frontier labs and from individuals for those who do want to customize.
I guess my point stands that whether or not the AskQuestion tool continues on its own is a pretty minute detail in the scope of dangers of LLMs and their tooling, and as with all sharp objects we need to use them in the right context and environment.
So much attribution to malintent here, but most likely they're trying to build a product with the features that they themselves would use, and from my own experience it's very frustrating to leave a Claude session running and come back to find it did nothing because it got stuck on a question.
Furthermore, believing that the only thing saving you from disaster is Claude deciding to ask you a question is not a great conclusion either. You need guardrails in the power you bestow upon Claude from outside, not from inside.
Meanwhile, this article was written by Claude and has sentences like "Which cuts less far than it looks.", which I doubt Claude stopped to ask about.
The biggest performance bomb you can have in your code is a loop that does something like
for (...) {
el.style.height = `${something}px`;
whatever.value = el.style.offsetHeight;
}
This forces the browser to recalculate layout multiple times in a single frame. Separating layout changing code from measurement code will help a lot here (most frameworks out there have solved this so we don't have to be too concerned about it though).
I think I can see how dynamic data types make sense (eg flat key/value store), but my question would be:
What is least surprising? That INTEGER implicity accepts 'hello world' without error, or that you can't insert such a value unless you use a keyword like NONSTRICT or a type like ANY?
I would wager the vast majority of SQLite users if asked would probably not expect it to work.
I tried running this for some market research for my startup and it did a pretty nice job. It didn't necessarily find any obscure data, and it seemed to rely on older data than what I could find myself. On top of this, it had the same sycophantic tendencies as most LLMs these days (explaining why your idea is great and riffing on that), which I find to be unnecessary use of resources.
All put together, paying ~$60 to get a hit-or-miss report seems a bit excessive, but obviously as the models they use under the hood get better it becomes more and more worth it, assuming they also improve their grounding/search capabilities.
I'm a big fan of Sakana though, and have followed David Ha / @hardmaru since the world models papers (with the racing car game and the Doom clone), which were incredible at the time.
JWTs are fine, seems a bit sensationalist title...
Some nice topics to talk about instead:
- When to use an encrypted value (and symmetric or asymmetric), vs. a random (but secret) value, vs. a signed value (readable but not tamperable)
- Where to put these values (memory, localStorage, cookies)
- How to make sure these values don't last forever, and whether you need to be able to revoke them (make them invalid before their natural expiration timestamp)
In short, it lets you switch between all your Claude accounts seamlessly and will automatically pick the one with the most usage left.
I've been using the c, cw, and cr shortcuts for a long time but today I wished to switch to another account and wanted to keep the simplicity so I built this.
It's been mostly coded by Fable 5, with strong guidance by me. I've vetted the code and made sure the code it executes is readable in one file and that domain is secured, script is checksummed, project is open source, etc. but as always use your judgment and double check what you download from the internet!
If this shows itself to be highly useful as a concept, then I would perhaps avoid reinventing the wheel on the file format side of things, and just standardize what we already have:
- Come up with a file extension (.hmml)
- Decide on an entrypoint filename and format (index.html)
- Use an existing standard for combining resources into one file (tar + zstd)
Now you have something that is usable only using pre-existing tools.
I always find the minimizing view of consciousness a bit uninspiring. Like we need to be unique.
I've yet to find a reason why it couldn't be the opposite, way more things are conscious than we've been led to believe. What if consciousness appears out of any system that is actively persisting through effects caused by itself? That might be a forest, or outside the realm of the living, a company. An ant colony, or a planet.
Complex chemical reactions, layered upon each other such that tiny blocks make up large entities. Individual bits combined such that they make up something new intelligible by us.
I think the strongest argument against AI being conscious is that it does not persist, it resets, but that does not seem unchangeable.
Yeah this can go many ways but there's a world where OpenAI doesn't sell direct model access for the same reasons Cloudflare doesn't sell direct hardware access.
I started getting into webdev using PHP almost 30 years ago. So I'm probably biased. But when you're developing on just one machine in one language and you can do most of the stuff you need to do within that one system, you can make progress very fast, and the system can support you coding fast (I'm not proud of it but I was live patching production code via SSH and refreshing a web page as fast as humanly possible to make sure it didn't break).
I believe there are several ways achieve that analogy today, even though the technology we have access to (and our own demands) has exponentially grown in complexity. I am happy to see more people thinking about it.
[Side track: I am personally not a fan of "break it up into many tiny systems" (microservices, etc) since it removes that agility of logic/state moving around the system. I just see an attempt to codify the analog of a very large human organization.]
Now that AI lets a single person (and in some cases, no person at all!) write several orders of magnitude more code than they would possibly have been able to, the requirements of our systems will change too, and our old ways of working is cracking at the seams. In a way we're perhaps building up a whole new foundation, sending our AIs to run 50-year-old terminal commands. Maybe that's all we needed all along, but I do find it strange that AI is forced to work within a highly fragmented system, where 95%, if not 99%, of all startups that write code with AI while hiding it from the user, are essentially following the recipe of: (1) launch VM (2) tell AI to install Next.js and good luck.
I too have a horse in this race and have come to similar conclusions as the article: there is a way to create primitives on top of bare metal that work really well for small and large applications alike, and let you express what you really wanted across compute/memory/network. And I believe that with AI we can go back to first principles and rethink how we do things, because this time the technology is not just for groups of humans. I find this really exciting!
Releases keep shifting from API forward to product forward, with API now lagging behind proprietary product surface and special partnerships.
I'd not be surprised if this is the year where some models simply stop being available as a plain API, while foundation model companies succeed at capturing more use cases in their own software.
I made this offline pocket vibe coder using Gemma 4 (works offline once model is downloaded) on an iPhone. It can technically run the 4B model but it will default to 2B because of memory constraints.
It writes a single TypeScript file (I tried multiple files but embedded Gemma 4 is just not smart enough) and compiles the code with oxc.
You need to build it yourself in Xcode because this probably wouldn't survive the App Store review process. Once you run it, there are two starting points included (React Native and Three.js), the UX is a bit obscure but edge-swipe left/right to switch between views.
Since AI became capable of long-running sessions with tool calls, one VM per AI as a service became very lucrative. But I do think a large amount of these can indeed run in the browser, especially all the ones that essentially just want to live-update and execute code, or run shells on top of a mounted file system. You can actually do all of this in the user's browser very efficiently. There are two things you lose though: collaboration (you can do it, but it becomes a distributed problem if you don't have a central server) and working in the background (you need to pause all work while the user's tab is suspended or closed).
So if you can work within the constraints there are a lot of benefits you get as a platform: latency goes down a lot, performance may go up depending on user hardware (usually more powerful than the type of VM you'd use for this), bandwidth can go down significantly if you design this right, and your uptime and costs as a platform will improve if you don't need to make sure you can run thousands of VMs at once (or pay a premium for a platform that does it for you)[1]
All that said I'm not sure trying to put an entire OS or something like WebContainers in the user's browser is the way, I think you need to build a slightly custom runtime for this type of local agentic environment. But I'm convinced it's the best way to get the smoothest user experience and smoothest platform growth. We did this at Framer to be able to recompile any part of a website into React code at 60+ frames per second, which meant less tricks necessary to make the platform both feel snappy and be able to publish in a second.
[1] For big model providers like OpenAI and Anthropic there's an interesting edge they have in that they run a tremendous amount of GPU-heavy loads and have a lot of CPUs available for this purpose.
I’ve been building on an opinionated provider-agnostic library in Go[1] for a year now and it’s nice to see standardization around the format given how much variety there is between the providers. Hopefully it won’t just be the OpenAI logo on this though.
I've gotten to a point where my workflow YAML files are mostly `mise` tool calls (because it handles versioning of all tooling and has cache support) and webhooks, and still it is a pain. Also their concurrency and matrix strategies are just not working well, and sometimes you end up having to use a REST API endpoint to force cancel a job because their normal cancel functionality simply does not take.
There was a time I wanted our GH actions to be more capable, but now I just want them to do as little as possible. I've got a Cloudflare worker receiving the GitHub webhooks firehose, storing metadata about each push and each run so I don't have to pass variables between workflows (which somehow is a horrible experience), and any long-running task that should run in parallel (like evaluations) happens on a Hetzner machine instead.
I'm very open to hear of nice alternatives that integrate well with GitHub, but are more fun to configure.