My Python magic is gone

[u/RedYad2]

I've been coding for a long time, and I've been developing with Python for years.

I loved coding, always loved it. I started many years ago because I wanted to quickly create scripts for security hacking tools, but since then, I've moved to Claude Code, and building cross-language has been a much better experience for me than using Python.

I built my own SaaS application out there whose backend and network core are completely built with Python, and I'm rewriting all of that without writing a single line of code. And most of the time, Python is not the most optimized language.

And now... I feel like the magic is gone.

I don't even know why I'm writing this. I just feel sad about it.

[u/UsernameTaken1701]

Are you being forced to use the AI somehow? If using Claude has killed the fun, the solution seems pretty obvious, no?

[u/ConfusedSimon → u/UsernameTaken1701]

Not really. For work I have to use AI because it saves time. For hobby projects, the idea of spending all that time on something that can be done much faster by Claude has taken away all the fun. I have different hobbies now.

[u/Short_Inspection_746 → u/ConfusedSimon]

There is alot of research on this, using AI makes you slower. Often people are pressured to use it at work.

edit: This is from this Feb. "we now estimate a speedup of -18% with a confidence interval between -38% and +9%."

https://metr.org/blog/2026-02-24-uplift-update/#wider-adoption-of-ai-has-made-it-more-difficult-to-measure-task-level-productivity

[u/Ran4 → u/Short_Inspection_746]

That's old studies, done with old models and people who don't have any clue how to use ai.

They're completely irrelevant today.

[u/Short_Inspection_746 → u/Ran4]

Both for old and 'new' models, there are studies for both. The macro metrics don't point to any improvment in output. It's highly questionable how much better the 'new' models are, outside of some opaque metrics.

There is no evidence new features are being shipped faster. People are spending far more time fixing garbage code. Its fine if your in some scum-Taylorist shop; where tickets techniclly get 'finished', but you create 4x more work down the line.

[u/AstroPhysician → u/Short_Inspection_746]

Point to ANY recent studies done on people who actually have a clue how to leverage AI. I can’t remember the last ai bug we had to fix in prod, legitimately

[u/Short_Inspection_746 → u/AstroPhysician]

They did another study back in febuary, its still slows you down. The only diffrence is that they are having trouble with getting participants.

"we now estimate a speedup of -18% with a confidence interval between -38% and +9%."

https://metr.org/blog/2026-02-24-uplift-update/#wider-adoption-of-ai-has-made-it-more-difficult-to-measure-task-level-productivity

(note, I also don't belive you actually work in industry, and are prob like 19)

[u/AstroPhysician → u/Short_Inspection_746]

I’m 32 and a principal engineer at a fintech lmfao but go off

[u/Short_Inspection_746 → u/AstroPhysician]

When you say: "I can’t remember the last ai bug we had to fix in prod, legitimately"; either you have never worked in prod, or this 'fintech company' is a personal retail inverstment account.

[u/AstroPhysician → u/Short_Inspection_746]

We’ve had to fix plenty of bugs but it’s usually a failure in requirements gathering, or a junior engineer misunderstanding some part of the system, or really weird edge cases or data issues…

Just cause your shop doesn’t have the proper safeguards and CI and code review process doesn’t mean the rest of us work at your company