There's no way to know if a new maintainer will live up to whatever standards they've kept to date. Archiving should be the default decision, unless there's formal and elaborate handover.
More like he wants to ban accelerator chip sales to China, which may be about “national security” or self preservation against a different model for AI development which also happens to be an existential threat to Anthropic. Maybe those alternatives are actually one and the same to him.
Annecotal, but I saw a tweet from someone who interviewed at Anthropic, and was explicity rejected because of cultural mismatch because they were not against open weight models.
It's hard not to see Anthropic's messaging of "this tech that we're pushing on you is going to take your job and maybe kill you" as being about anything other than regulatory capture, with the goal of the government shutting down competitors.
I think OpenAI and Anthropic are both really in a tough spot - spending so much on what is becoming a commodity product for which neither seems positioned to be low cost producer. Maybe a bit like the UK-France channel tunnel project where the product itself is a success but a bloodbath for those who invested to build it.
Notion, as any other thin-AI product out there, is now in Anthropic/OpenAI/Google's crosshairs. Unless one has a moat the size of SharePoint or Google Docs or OneDrive, it's just a feature away.
I don't think they have added a Obsidian Bases / Notion Database like feature yet, right? Saw some discussion of adding a NocoDB integration, but also didn't see that happen yet.
I know this is probably out of scope, but I'd love it as well if Notion could slowly accrete the features of Airtable... at least expose some form of programmatic access to tables!
It works, but models seem to have these insane long traces to do the most basic things. I had to create a couple of skills so they know how to properly use the thing without breaking, so they don't always try to pass the wrong parameters to it.
It also doesn't let us change a couple of things (like icons). Or, if it does, not even Opus 4.6 can figure out how to do it.
For tsonic (https://github.com/tsoniclang/tsonic) which is trying to convert TS to C# and then to native binary via NativeAOT, I took almost the opposite tradeoff from JSIR.
JSIR is optimizing for round-trips back to JavaScript source. But since in language to language conversion teh consumer is a backend emitter (C# in my case), instead of preserving source structure perfectly, my IR preserves resolved semantic facts: types, generic substitutions, overload decisions, package/binding resolution, and other lowering-critical decisions.
I could be wrong, but I suspect transpilers are easier to build if it's lowering oriented (for specific targets).
Show us the code, or an obfuscated snippet. A common challenge with coding-agent related posts is that the described experiences have no associated context, and readers have no way of knowing whether it's the model, the task, the company or even the developer.
Nobody learns anything without context, including the poster.
A pretty easy way to construct a bug that is easy for a human to solve but difficult for an AI is to have it to do something with z-indexes. For instance, if your element isn't rendering because something else is on top of it, Claude will struggle, because it's not running a browser, so the only way it could possibly know there was a bug would be to read every single CSS and HTML file in your entire repo. On the other hand, a human can trivially observe the failure in a browser and then fix it.
This is a pretty simple thing, but you can imagine how CSS issues get progressively more difficult for AIs to solve. A CSS bug can be made to require reading arbitrarily much code if you solve by only reading code, but by looking at relatively few elements, if you look at the page with your eyes.
This can be somewhat solved by hooking up a harness to screenshot the page and feed it into the AI, but it isn't perfect even then.
That's hard to believe in my case. I tried a variety of prompts, 3 different frontier models, provided manual screenshot(s), the agent itself also took its own screenshots from tests during the course of debugging. Nothing worked. I have now fixed the bug manually after 15-20 minutes of playing around with a codebase where I don't know the language and didn't write a single line of code until now.
It really is, for complex tasks. Claude excels at low-mid complexity (CRUD apps, most business apps). For anything somewhat out of the distribution, codex at the moment has no peer.
I have always used Claude at max thinking levels since it launched. It has never been up to the task. For clarity, the task being this: https://github.com/tsoniclang/tsonic
Meanwhile, there are half a dozen other projects (business apps, web apps etc) where it works well.
Microsoft's biggest mistake was .Net being a Java competitor when it should have just been like golang producing native binaries. Especially since .Net was realistically only going to succeed on x86/64 at that point (late 90s and 2000s). This shut the door on C# for consumer UIs, and people stuck to Visual Basic and MFC.
It took them more than 2 decades to finally support pure native binaries (via NativeAOT). And it's fantastic for servers on Linux.
The problem was in the early 2000s it was basically accepted x86 was a dead end whose days were numbered.
Itanium was the heir apparent but importantly basically vaporware. How do you develop software NOW and more importantly sell and ship software NOW that'll work on a CPU you don't have access to and for which good compilers don't really exist yet? I remind you in the days where online updates were a luxury at best.
Processor agnostic CIL/JIT code was the prescribed solution at the time. Java had lit the way, and it was the only "clear" path forward for better or worse.
Little did we know Itanium would implode, and x86-64 would rise and give 20+ more years of binary compatibility.
They were recovering from all of the security fiascos of software that wasn’t being updated. So they pushed as much as they could into the core libraries and forced only one version to be installed at a time- so they could easily push security fixes.
This led to one of the trickiest things for early .NET consumer apps- getting the latest runtime installed.
Anyone who can't get any better AI accelerators elsewhere? Last I heard, these things were sold out for years on end. And anyone who can make one, can sell them.
C#'s LINQ (code as data, like LISP) wins over golang for any type of data access. Strongly-typed, language-native queries. Go has its own advantages though.
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