Ask HN: How is AI-assisted coding going for you professionally?

I find that the default Claude Code harness deals with the ambiguity best right now with the questionnaire system. So you can pose the core of the problem first and then specify only those implementation details that matter.

Link? Genuinely curious to check it out.

Im at a public, well known tech company.

We got broad and wide access to AI tools maybe a month ago now. AI tools meaning claude code, codex, cursor and a set of other random AI tools.

I use them very often. They've taken a lot of the fun and relaxing parts of my job away and have overall increased my stress. I am on the product side of the business and it feels necessary for me to have 10 new ideas and now the ones with the most ideas will be rewarded, which I am not as good at. Ive tried having the agents identify opportunities for infra improvements and had no good luck there. I haven't tried it for product suggestions but I think it would be poor at that too.

I get sent huge PRs and huge docs now that I wasnt sent before with pressure to accept them as is.

I write code much faster but commit it at the same pace due to reviews taking so long. I still generate single task PRs to keep them reviewable and do my own thorough review before hand. I always have an idea in ny head about how it should work before getting started, and I push the agent to use my approach. The AI tools are good at catching small bugs, like mutating things across threads. I like to use it to generate plans for implementation (that only I and the bots read, I still handwrite docs that are broadly shared and referenced).

Overall, AI has me nervous. Primarily because it does the parts that I like very well and has me spending a higher portion of my job on the things I dont like or find more tiresome.

I don’t find it baffling at all and both your experiences perfectly match mine.

Asking AI to solve a problem for you is hugely non-linear. Sometimes I win the AI lottery and its output is a reasonable representation of what I want. But mostly I loose the AI lottery and I get something that is hopeless. Now I have a conundrum.

Do I continue to futz with the prompt and hope if I wiggle the input then maybe I get a better output, or have I hit a limit and AI will never solve this problem? And because of the non linear nature I just never know. So these days I basically throw one dart. If it hits, great. If I miss I give up and do it the old fashioned way.

My work is in c++ primarily on what is basically fancy algorithms on graphs. If it matters.

I used to experience those issues a lot. I haven't in a while. Between having good documentation in my projects, well-defined skills for normal things, simple to use testing tools, and giving it clear requirements things go pretty smoothly.

I'd say it still really depends on what you're doing. Are you working in a poorly documented language that few people use solving problems few people have solved? Are you adding yet another normal-ish kind of feature in a super common language and libraries? One will have a lot more pain than the other, especially if you're not supplying your own docs and testing tools.

There's also just a difference of what to include in the context. I had three different projects which were tightly coupled. AI agents had a hard time keeping things straight as APIs changed between them, constantly misnaming them and getting parameters wrong and what not. Combining them and having one agent work all three repos with a shared set of documentation made it no longer make mistakes when it needed to make changes across multiple projects.