His team is basically him and two other humans, powering an ambitious well-known project so successful an industry titan ended up acquihiring him/them. That's pretty lean, no?
The ambitious idea is actually giving a chatbot/agent access to a bunch of personal data and having it self-modify its harness and context to some extent.
But it costs $1.3m USD a month to run, not including their salaries. That's the cost of a team of 50-200 staff, depending on where you're hiring.
I don't think there's any way most people would call that lean. It's lean in exactly 1 axis which is people, but no one really cares about that, people is always a proxy for cost.
He said in another thread there's 6 people involved. 6 people for this project doesn't feel lean, without even considering the enormous LLM spend/complexity
Where is that figure from? I would be extremely surprised if that doesn't drop at least an order of magnitude as the hype wears off. Assuming it's even representative of today and not two months ago
If these methods prove successful it isn't going to matter. A user doesn't care if code is 'slop' or artisanal, so long as the app/site/whatever works.
If you can combine autonomous flows (and millions of dollars in tokens) to produce work comparable to a traditional engineering team, then why would the user care which wrote the app/site/whatever?
Yeah, of course hunans will still be writing code in a 100 years. I am certain we still won't have flying cars either.
Agricultural mechanisation didn't eliminate human labor over the 20th century. A huge fraction of the world's farmers have little or no mechanization today, well over a century after the invention of the revolutionary farm tractor.
With apologies to Ada Lovelace, but humanity has been writing code in anger for only like, 80 years? We'll still be at it in a 100 more.
I think you have a fair point. It is possible that LLMs won't scale/advance enough and a fundamentally new approach is needed.
I'm personally just impressed with the rate of improvement and _hope_ that it will continue, and that inference prices will fall (or on-device LLM become more feasible/powerful).
Anyway I appreciate your perspective even though I don't necessarily share it
