I've noticed an interesting trend:

Most people who are happy with LLM coding say something like "Wow, it's awesome. I asked it to do X and it did it so fast with minimal bugs, and good code", and occasionally show the output. Many provide even more details.

Most people who are not happy with LLM coding ... provide almost no details.

As someone who's impressed by LLM coding, when I read a post like yours, I tend to have a lot of questions, and generally the post doesn't have the answers.

1. What type of problem did you try it out with?

2. Which model did you use (you get points for providing that one!)

3. Did you consider a better model (compare how Gemini 2.5 Pro compares to Sonnet 3.7 on the Aider leaderboard)?

4. What were its failings? Buggy code? Correct code but poorly architected? Correct code but used some obscure method to solve it rather than a canonical one?

5. Was it working on an existing codebase or was this new code?

6. Did you manage well how many tokens were sent? Did you use a tool that informs you of the number of tokens for each query?

7. Which tool did you use? It's not just a question of the model, but of how the tool handles the prompts/agents under it. Aider is different from Code which is different from Cursor which is different form Windsurf.

8. What strategy did you follow? Did you give it the broad spec and ask it to do anything? Did you work bottom up and work incrementally?

I'm not saying LLM coding is the best or can replace a human. But for certain use cases (e.g. simple script, written from scratch), it's absolutely fantastic. I (mostly) don't use it on production code, but little peripheral scripts I need to write (at home or work), it's great. And that's why people like me wonder what people like you are doing differently.

But such people aren't forthcoming with the details.