[refulgentis]

This is a 30KLOC 6 platform flutter app that's, in this user story, doing VOIP audio, running 3 audio models on-device, including in your browser. A near-replica of the Google Assistant audio pipeline, except all on-device.

It's a real system, not kindergarten "look at the React Claude Artifacts did, the button makes a POST request!"

The 1500 loc websocket / session management code it refactored and tested touches on nearly every part of the system (i.e. persisting messages, placing search requests, placing network requests to run a chat flow)

Also, it's worth saying this bit a bit louder: the "just throwing files in" I mention is key.

With that, the quality you observed being in reverse is the distinction: with o1 thinking, and whatever Sonnet's magic is, there's a higher payoff from working a larger codebase.

For example, here, it knew exactly what to do for the web because it already saw the patterns iOS/Android/macOS shared.

The bend I saw in the curve came from being ultra lazy one night and seeing what would happen if it just had all the darn files.

[noch]

> This is a 30KLOC 6 platform flutter app […] It's a real system, not kindergarten "look at the React Claude Artifacts did, the button makes a POST request!"

This is powerful and significant but I think we need to ground ourselves on what a skilled programmer means when he talks about solving problems.

That is, honestly ask: What is the level of skill a programmer requires to build what you've described? Mostly, imo, the difficulties in building it are in platform and API details not in any fundamental engineering problem that has to be solved. What makes web and Android programming so annoying is all the abstractions and frameworks and cruft that you end up having to navigate. Once you've navigated it, you haven't really solved anything, you've just dealt with obstacles other programmers have put in your way. The solutions are mostly boilerplate-like and the code I write is glue.

I think the definition of "junior engineer" or "simple app" will be defined by what LLMs can produce and so, in a way, unfortunately, the goal posts and skill ceiling will keep shifting.

On the other, hand, say we watch a presentation by the Lead Programmer at Naughty Dog, "Parallelizing the Naughty Dog Engine Using Fibers"[^0] and ask the same questions: what level of skill is required to solve the problems he's describing (solutions worth millions of dollars because his product has to sell that much to have good ROI):

"I have a million LOC game engine for which I need to make a scheduler with no memory management for multithreaded job synchronization for the PS4."

A lot of these guys, if you've talked to them, are often frustrated that LLMs simply can't help them make headway with, or debug, these hard problems where novel hardware-constrained solutions are needed.

---

[^0]: https://www.youtube.com/watch?v=HIVBhKj7gQU

[refulgentis]

It's been pretty hard, but if you reduce it to "Were you using a framework, or writing one that needs to push the absolute limits of performance?"...

...I guess the first?...

...But not really?

I'm not writing GPU kernels or operating system task schedulers, but I am going to some pretty significant lengths to be running ex. local LLM, embedding model, Whisper, model for voice activity detection, model for speaker counting, syncing state with 3 web sockets. Simultaneously. In this case, Android and iOS are no valhalla of vapid-stackoverflow-copy-pasta-with-no-hardware-constraints, as you might imagine.

And the novelty is, 6 years ago, I would have targeted iOS and prayed. Now I'm on every platform at top-tier speeds. All that boring tedious scribe-like stuff that 90% of us spend 80% of our time on, is gone.

I'm not sure there's very many people at all who get to solve novel hardware-constrained problems these days, I'm quite pleased to brush shoulders with someone who brushes shoulders with them :)

Thus, smacks more of no-true-scotsman than something I can chew on. Productivity gains are productivity gains, and these are no small productivity gain in a highly demanding situation.

[noch]

> Thus, smacks more of no-true-scotsman than something I can chew on.

I wasn't making a judgement about you or your work, after all I don't know you. I was commenting within the context of an app that you described for which an LLM was useful, relative to the hard problems we'll need help with if we want to advance technology (that is, make computers do more powerful things and do them faster). I have no idea if you're a true Scotsman or not.

Regardless: over the coming years we'll find out who the true Scotsmen were, as they'll be hired to do the stuff LLMs can't.

[geerlingguy]

The challenging projects I've worked on are challenging not because slamming out code to meet requirements is hard (or takes long).

It's challenging because working to get a stable set of requirements requires a lot of communication with end users, stakeholders, etc. Then, predicting what they actually mean when implementing said requirements. Then, demoing the software and translating their non-technical understanding and comments back into new requirements (rinse and repeat).

If a tool can help program some of those requirements faster, as long as it meets security and functional standards, and is maintainable, it's not a big deal whether a junior dev is working with Stack Exchange or Claude, IMO. But I do want that dev to understand the code being committed, because otherwise security bugs and future maintenance headaches creep in.

[achierius]

I've definitely noticed the opposite on larger codebases. It's able to do magical things on smaller ones but really starts to fall apart as I scale up.