[macNchz]

Using all of the popular coding models pretty extensively over the past year, I've been having great success with Gemini 2.5 Pro as far as getting working code the first time, instruction following around architectural decisions, and staying on-task. I use Aider and write mostly Python, JS, and shell scripts. I've spent hundreds of dollars on the Claude API over time but have switched almost entirely to Gemini. The API itself is also much more reliable.

My only complaint about 2.5 Pro is around the inane comments it leaves in the code (// Deleted varName here).

[ZeWaka]

If you use one of the AI static instructions methods (e.g., .github/copilot-instructions.md) and tell it to not leave the useless comments, that seems to solve the issue.

[macNchz]

I've been intending to try some side by side tests with and without a conventions file instructing it not to leave stupid comments—I'm curious to see if somehow they're providing value to the model, e.g. in multi-turn edits.

[luckydata]

it's easier to just make it do a code review with focus on removing unhelpful comments instead of asking it not to do it the first time. I do the cleanup after major rounds of work and that strategy seems to work best for me.

[jjani]

This was not my experience with the earlier preview (03), where its insistence on comment spam was too strong to overcome. Wonder if this adherence improved in the 05 or 06 updates.

[sans_souse]

can you elaborate on this?

[dominicrose]

I don't mind the comments, I read them while removing them. It's normal to have to adapt the output, change some variable names, refactor a bit. What's impressive is that the output code actually works (or almost). I didn't give it the hardest of problems to solve/code but certainly not easy ones.

[macNchz]

Yeah I've mostly just embraced having to remove them as part of a code review, helps focus the review process a bit, really.

[avereveard]

I'm using pro for backend and claude for ux work, claude is so much thoughtful about how user interact with software and can usually replicate better the mock up that gpt4o image generator produces, while not being overly fixated on the mockup design itself.

My complaint is that it catches python exceptions and don't log them by default.

[miki123211]

And the error handling. God, does it love to insert random try/except statements everywhere.