Comment by fxtentacle
1 month ago
“When AI labs raise prices, big spending on AI could shift from a flex to a liability.”
because companies will need
“proof of productivity gains or metrics that show a clear return for all this AI investment.”
which in my opinion is simply not true. I haven’t seen any good study that showed AI to actually improve productivity overall. It massively helps in some areas, but then promptly gets stuck in others. So you still need an expert to guide it.
> I haven’t seen any good study that showed AI to actually improve productivity overall.
AI is overhyped, but on the other hand, I think it would be difficult to deny the significant productivity increases when used appropriately.
For some tasks, it's huge. Some tasks that I might've spent 8 hours on, I can do in 20 minutes. That's very real and huge.
At the same time, that's not the average that I experience. Some things are pretty much a wash. Others might be 2x or 3x faster which is quite nice, but short of the hype. And some things can be very clearly slower with AI. Also some things are more unreliable with AI.
We need to get to a maturity point where we realize it's just another tool. An incredibly powerful one for many tasks, yes. But it's not magically the right tool for everything and not always the right answer.
Yup.
I think we have all heard of (or are living through) mandates to prove that AI makes us more productive, or else...
We'll see how many of these actually works out.
I use a.i to build my startup and it massively helps but i still spend hours reviewing and fixing what is genertes.
At this point it’s undeniable for my use cases.
After I discovered how to use git worktrees in Codex to work in three conversations in parallel, I am able to build apps with a scope that simply was not realistic before.
You obviously are not reviewing the generated code in any detail before merging it. This is not sustainable for the project as it will grow to be too large for what it needs to be.
I will see if that becomes a blocker.
There was one feature/screen that Codex built in a single 5k LOC file.
It was still perfectly capable of developing the feature and it was working as expected.
I had it break it down into multiple files, but if I wouldn’t have seen it during the MR review, I would not have noticed. The large file did not seem to degrade the performance of the agent.
1 reply →
Three? Across how many projects?
One, thus the git worktrees.
You might think that this would lead to a mess with merge conflicts, but the agent can resolve them automatically.
I added an instruction to AGENTS.md so that before handoff it fetches and rebases, resolving conflicts if needed plus rerunning the tests.
And that expert will not have their knowledge from learning through AI
why not?