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Comment by simonw

6 hours ago

One of the big open questions for me right now concerns how library dependencies are used.

Most of the big ones are things like skia, harfbuzz, wgpu - all totally reasonable IMO.

The two that stand out for me as more notable are html5ever for parsing HTML and taffy for handling CSS grids and flexbox - that's vendored with an explanation of some minor changes here: https://github.com/wilsonzlin/fastrender/blob/19bf1036105d4e...

Taffy a solid library choice, but it's probably the most robust ammunition for anyone who wants to argue that this shouldn't count as a "from scratch" rendering engine.

I don't think it detracts much if at all from FastRender as an example of what an army of coding agents can help a single engineer achieve in a few weeks of work.

I think the other question is how far away this is from a "working" browser. It isn't impossible to render a meaningful subset of HTML (especially when you use external libraries to handle a lot of this). The real difficulty is doing this (a) quickly, (b) correctly and (c) securely. All of those are very hard problems, and also quite tricky to verify.

I think this kind of approach is interesting, but it's a bit sad that Cursor didn't discuss how they close the feedback loop: testing/verification. As generating code becomes cheaper, I think effort will shift to how we can more cheaply and reliably determine whether an arbitrary piece of code meets a desired specification. For example did they use https://web-platform-tests.org/, fuzz testing (e.g. feed in random webpages and inform the LLM when the fuzzer finds crashes), etc? I would imagine truly scaling long-running autonomous coding would have an emphasis on this.

Of course Cursor may well have done this, but it wasn't super deeply discussed in their blog post.

I really enjoy reading your blog and it would be super cool to see you look at approaches people have to ensuring that LLM-produced code is reliable/correct.

  • Yeah, I'm hoping they publish a lot more about this project! It deserves way more then the few sentences they've shared about it so far.

Why attempt something that has abundant number of libraries to pick and choose? To me, however impressive it is, 'browser build from scratch' simply overstates it. Why not attempt something like a 3D game where it's hard to find open source code to use?

  • There are a lot of examples out there. Funny that you mention this. I literally just last night started a "play" project having Claude Code build a 3D web assembly/webgl game using no frameworka. It did it, but it isn't fun yet.

    I think the current models are at a capability level that could create a decent 3D game. The challenges are creating graphic assets and debugging/Qa. The debugging problem is you need to figure out a good harness to let the model understand when something is working, or how it is failing.

  • Is something like a 3D game engine even hard to find source code for? There's gotta lots of examples/implementations scattered around.

Any views on the nature of "maintainability" shifting now? If a fleet of agents demonstrated the ability to bootstrap a project like that, would that be enough indication to you that orchestration would be able to carry the code base forward? I've seen fully llm'd codebases hit a certain critical weight where agents struggled to maintain coherent feature development, keeping patterns aligned, as well as spiralling into quick fixes.

  • Almost no idea at all. Coding agents are messing with all 25+ years of my existing intuitions about what features cost to build and maintain.

    Features that I'd normally never have considered building because they weren't worth the added time and complexity are now just a few well-structured prompts away.

    But how much will it cost to maintain those features in the future? So far the answer appears to be a whole lot less than I would previously budget for, but I don't have any code more than a few months old that was built ~100% by coding agents, so it's way too early to judge how maintenance is going to work over a longer time period.

  • I think there's a somewhat valid perspective that the Nth+1 model can simply clean up the previous models mess.

    Essentially a bet that the rate of model improvement is going to be faster than the rate of decay from bad coding.

    Now this hurts me personally to see as someone who actually enjoys having quality code but I don't see why it doesn't have a decent chance of holding