AI doesn't generate working products, that's still your job

Post by fluidcruft » Sat, Aug 01, 2026, 4:03 PM UTC

luckylion wrote: post #215

whstl wrote: post #158

Earlier quoted context omitted.

I would say they're great until they aren't. Which means at some point in a session or in a long-lived-project they will resist very hard being steered like it would be done by another developer, product manager, a designer, or just the market in general. Most people don't find this to happen because the size of projects and the granularity of the expectations are wildly different.

I found that agents help, even if you don't parallelize. Having one agent control another and verify its results against rules you set has worked well for me because the controlling agent has no incentive to cut corners, and the implementor might, but it is being controlled. My usage might be much simpler than what you do, but it went from "but I gave a list of things to do, you only did 5 of them" - "okay, here are…

Post by unknownfuture » Sat, Aug 01, 2026, 4:12 PM UTC

discreteevent wrote: post #235

baq wrote: post #160

Earlier quoted context omitted.

Probabilistic algorithms are not new. If the distribution is known you can bend surprisingly many things to your will in the long run - and the most interesting part is the long run can be unexpectedly short. LLMs are quite interesting in that regard because you have a lot of levers to influence the shape of the distribution; the ways are different for each model, so it’s a very experimental science, but applying the…

The scientific method is not about running experiments and then trying to work out the gist of something. It's about understanding and theory building and then doing experiments to verify your model. The end result is not an experimental result but a model that you understand and can use to build solutions etc. LLMs are bringing us back to pre- science correlations and superstitions. That's why all the conversations…

Post by adamddev1 » Sat, Aug 01, 2026, 4:18 PM UTC

discreteevent wrote: post #235

baq wrote: post #160

Earlier quoted context omitted.

Probabilistic algorithms are not new. If the distribution is known you can bend surprisingly many things to your will in the long run - and the most interesting part is the long run can be unexpectedly short. LLMs are quite interesting in that regard because you have a lot of levers to influence the shape of the distribution; the ways are different for each model, so it’s a very experimental science, but applying the…

The scientific method is not about running experiments and then trying to work out the gist of something. It's about understanding and theory building and then doing experiments to verify your model. The end result is not an experimental result but a model that you understand and can use to build solutions etc. LLMs are bringing us back to pre- science correlations and superstitions. That's why all the conversations…

Post by maxnevermind » Sat, Aug 01, 2026, 4:33 PM UTC

Post by eudamoniac » Sat, Aug 01, 2026, 4:48 PM UTC

zulban wrote: post #217

ThePhysicist wrote: post #46

I'm about to throw away multiple months of LLM generated code for one of my side projects. I was really careful writing design specs and it wasn't even a new code base the LLM worked on, but still after several months of AI changes I feel my code degraded more and more into a subtle mess. Hard to explain, each individual change looked good and logical and on the surface the codebase looks fine, but looking at the who…

It's hard to take criticism like this seriously when you didn't say the model you used. It's like someone complaining about a car's performance but they leave out the brand and year. If you don't think that's relevant I just can't take you seriously.