Not wrong at all, that’s why I’m building my own platform for this. That’s also why I haven’t publicly done much on First Cut yet. I’m using my platform to actually build the product, so the intent is that I use my expertise and oversight to ensure it’s not just slop code. So most of the effort has gone into building that platform, which has made building First Cut itself slower. But I’ve actually got my platform running well-enough that now my team is able to get involved, and I can start to work on First Cut again, which means that I should be able to answer your “concern” definitively. I share it.

I am having the greatest time professionally with AI coding. I now have the engineering team I’ve always dreamed of. In the last 2 months I have created:

- a web-based app for a F500 client for a workflow they’ve been trying to build for 2 years; won the contract

- built an iPad app for same client for their sales teams to use

- built the engineering agent platform that I’m going to raise funding

- a side project to do rough cuts of family travel videos (https://usefirstcut.com, soft launch video: https://x.com/xitijpatel/status/2026025051573686429)

I see a lot of people in this thread struggling with AI coding at work. I think my platform is going to save you. The existing tools don’t work anymore, we need to think differently. That said, the old engineering principles still work; heck, they work even better now.

Having incorporated libghostty into my current web-based project, I can't say enough thanks. I've lived in the terminal since 2003, resisting IDEs, VSCode, everything because I'm a die hard Vim + tmux guy. Vibe coding coming back to the terminal, and being able to use libghostty to facilitate that is a serious vindication of my steadfast resistance to move away from the terminal.

I'm sure you feel the same watching Ghostty become what it has. Big thank you.

So I know these are just benchmarks, but apparently Elixir is one of the best languages to use with AI, despite having a smaller training dataset: https://www.youtube.com/watch?v=iV1EcfZSdCM and https://github.com/Tencent-Hunyuan/AutoCodeBenchmark/tree/ma...

Furthermore, it's actually kind of annoying that the LLMs are not better than us, and still benefit from having code properly typed, well-architected, and split into modules/files. I was lamenting this fact the other day; the only reason we moved away from Assembly and BASIC, using GOTOs in a single huge file was because us humans needed the organization to help us maintain context. Turns out, because of how they're trained, so do the LLMs.

So TypeScript types and tests actually do help a lot, simply because they're deterministic guardrails that the LLM can use to check its work and be steered to producing code that actually works.

You know, I love this comment because you are where I was 15 years ago when I naively decided that I wanted to do my master's in medical biophysics and try to use NVIDIA CUDA to help accelerate some of the work that we were doing. So I have a very... storied history with NVIDIA CUDA, but frankly, it's been years since I've actually written C code at all, let alone CUDA.

I have to admit that I wrote none of the code in this repo. I asked Codex to go and do it for me. I did a lot of prompting and guidance through some of the benchmarking and tools that I expected it to use to get the result that I was looking for.

Most of the plans that it generated were outside of my wheelhouse and not something I'm particularly familiar with, but I know it well enough to understand that its plan roughly made sense to me and I just let it go. So the fact that this worked at all is a miracle, but I cannot take credit for it other than telling the AI: what I wanted, how to do it, in loose terms, and helping it when it got stuck.

BTW, everything above was dictated with the code we generated, except for this sentence. And I added breaklines for paragraphs. That's it.