> 3. Regarding me specifically, I work on the LessWrong codebase which is technically open-source. I feel like calling myself an "open-source developer" has the wrong connotations, and makes it more sound like I contribute to a highly-used Python library or something as an upper-tier developer which I'm not
That’s very interesting! This kinda matches what I see at work:
- low performers love it. it really does make them output more (which includes bugs, etc. it’s causing some contention that’s yet to be resolved)
- some high performers love it. these were guys who are more into greenfield stuff and ok with 90% good. very smart, but just not interested in anything outside of going fast
- everyone else seems to be finding use out of it, but reviews are painful
> Anthropic claims they solely use agents to code and don't modify any code manually.
Have you used CC? It shows. They did not make their fortune off this, and it’s at least lost me a customer because of how sloppy it is. The model is good, and it’s why they have to gate access to it. I’d much rather use a different harness.
I do think you’re on to something though. As societal wealth further concentrates among the few, we’re going to get more and more slop for the rest of us because we have no money (relatively speaking). Agentic coding is here to stay because we as a society are forced more and more slop. It’s already rampant, this is just automating it.
> As people say - something changed around Dec/Jan
Yes, Anthropic decided they wanted to IPO and got the hype machine in full swing.
Don’t get me wrong LLMs are here to stay but how we’re currently using them is likely going to change a lot. Stuff like this:
> in general everybody has to do bottom up cleanup and documentation of all their projects, setup skills and whatnot and that's assuming their corp is ok with it, not blocking it
Is not needed to get a lot out of AI, and is mostly snake oil. Integrating them with actionable feedback is, but that takes a lot of time and rethinking of some existing systems.
I don’t like the Internet analogy cause that’s like producing a new raw material, but AI is gonna be like Excel eventually (one of the most important pieces of software in the world).
Only a personal anecdote, but the humans I know that have used it are all aware of how buggy it is. It feels like it was made in 2 weeks.
Which gets back to the outsourcing argument: it’s always been cheap to make buggy code. If we were able to solve this, outsourcing would have been ubiquitous. Maybe LLMs change the calculus here too?
Yeah, it’s odd watching the outsourcing debate play out again. The results are gonna be the same.
Which is a shame, cause I think LLMs have a lot more use for software dev than writing code. And that’s really what’s going to shift the industry - not just the part willing to cut on quality.
AI has been a lifesaver for my low performing coworkers. They’re still heavily reliant on reviews, but their output is up. One of the lowest output guys I ever worked with is a massive LinkedIn LLM promoter.
Not sure how long it’ll last though. With the time I spend on reviews I could have done it myself, so if they don’t start learning…
That’s very interesting! This kinda matches what I see at work:
- low performers love it. it really does make them output more (which includes bugs, etc. it’s causing some contention that’s yet to be resolved)
- some high performers love it. these were guys who are more into greenfield stuff and ok with 90% good. very smart, but just not interested in anything outside of going fast
- everyone else seems to be finding use out of it, but reviews are painful