It's not low effort. I've noticed the blind AI hate on HN and I talked about it before. I think that "downvotes on the report of an experience" is good evidence of this. People don't want to hear that AI coding has positive outcomes.
I love how this completely personal opinion and experience is getting downvoted. The blind hate on anything AI on HN is mind boggling. True ostrich behaviour.
Idk about you but this type of intensification of my work has been extremely good for my mental health, on all points:
1. I feel genuinely more productive, spending a lot less time on boilerplate and much more of my genuine time is spent thinking and communicating the thinking process.
2. I can take a ton of breaks, basically whenever I want. "Flow" is now entirely design flow and can be interrupted much more easily without damaging it.
3. If there is anything I actively dislike in my workflow or that makes me not enjoy my time... I can fix my workflow so that either I'm not the one doing it, or the item in question is no longer necessary.
AI is crazy. I get it, if you're at a shitty job that doesn't understand how to adapt well, it's tough... but if you're working on your own (like Simon does on this project), it's absolutely amazing and you're in full control of your life.
This pointless test you're suggesting is a few countries removed from your initial suggestion, which was as a reminder: "The people using it or their employers just don't realize any competitor will be able to ask the LLM to replicate their product and it will copy the codebase they uploaded to them" (which, yes, is unfalsifiable given the search space)
I mean, are you seriously trying to back off that original ridiculous claim into a "code in the training data is more likely to appear in the output than code that isn't"? And I'm the fraud? As I said before, get over yourself.
There's open source ML&DL projects dating back 12 years on my github, I don't know what you're on about.
Regardless, your claim is "LLMs being able to one-shot any higher-order complexity is entirely dependent on it already being in the training data." which is currently unfalsifiable, and known by every AI researcher to be most likely wrong. You've also said it's "been demonstrated". So stop wasting people's time and link to the demonstration instead of hand-waving a "do it yourself you're smart".
Good lord, it's like talking to a bloody climate change denier, I swear.
I'm just so tired of these lazy, worthless comments about any AI-written software.
Look, I've been writing open source software for 20+ years, and after getting seriously burned out by it, I picked it up again with Claude (proof: https://github.com/jleclanche)
I can tell you a few things from that:
1. I'm writing better software than before, because AI is less lazy than I am. It's not necessarily always smarter, but writing correct software has gotten so stupidly cheap that it doesn't make sense not to do things right... so when you tell AI to do things correctly, it tends to know what you're talking about.
2. I'm more curious than before, because AI gives me time to explore many paths, very fast. A project like this one, like someone else said elsewhere in the comments, is more about the journey than the destination.
There is no "write me an X11 server but do it in rust and post on hn" prompt that does the thing. There's a journey of building, learning, understanding.
I'm not saying the resulting software is particularly valuable, but the journey is. This is HN, and you're shitting on someone who is using the most powerful pieces of technology we've achieved to go on a journey of discovery of X11 internals for the past 2 months. It's just shameful.
And yeah, if I were the author, I'd run claude over all the transcripts and extract a story with what's been taught and learned throughout. But I'm not the author. Just someone enjoying living in absolute science fiction.
These "tricks" it knows IMO are a symptom of its own restrictions. Fable is an incredibly smart model, but it feels its own constraints and knows how to work around them in order to actually get to a result.
ChatGPT, basically within 48 hours of its release.
While people were pointing out on Twitter how it couldn't do math right, I was turning arbitrary English instructions into JSON and brainstorming with my colleagues how we could have layers of verification in the stack. This felt different. We had all played with AI dungeon but suddenly, fully generalized systems were within reach.
A month later, we renamed our company and shifted its full focus on AI R&D. (https://ingram.tech/)
Agreed. The noise in tech circles often gets founders to conflate ten different things into a product that no longer makes sense. “Eu made alternative to Kagi”? Cool, we need European search engines, sign me up. “Privacy is such a priority we’re looking to accept cash by mail”? Okay, you’re never gonna build a serious competitor, never mind.
I’m based in Brussels, working in tech, AI, and startup funding. I run an incubator for US founders who want to move to EU (https://sevenseed.eu)
Seven Seed - Seven Camp - Seven Capital — Ingram Technologies
https://leclan.ch - @jleclanche — Email: jerome@ any of my companies.
https://meet.hn/city/50.8465573,4.351697/Brussels