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[return to "ChatGPT Containers can now run bash, pip/npm install packages and download files"]
1. behnam+sj[view] [source] 2026-01-26 20:58:52
>>simonw+(OP)
I wonder if the era of dynamic programming languages is over. Python/JS/Ruby/etc. were good tradeoffs when developer time mattered. But now that most code is written by LLMs, it's as "hard" for the LLM to write Python as it is to write Rust/Go (assuming enough training data on the language ofc; LLMs still can't write Gleam/Janet/CommonLisp/etc.).

Esp. with Go's quick compile time, I can see myself using it more and more even in my one-off scripts that would have used Python/Bash otherwise. Plus, I get a binary that I can port to other systems w/o problem.

Compiled is back?

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2. koe123+i11[view] [source] 2026-01-27 01:09:18
>>behnam+sj
> But now that most code is written by LLMs

Am I in the Truman show? I don’t think AI has generated even 1% of the code that I run in prod, nor does anyone I respect. Heavily inspired by AI examples, heavily assisted by AI during research sure. Who are these devs that are seeing such great success vibecoding? Vibecoding in prod seems irresponsible at best

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3. empath+Vx2[view] [source] 2026-01-27 14:01:50
>>koe123+i11
For the last 2 or 3 months we made a commitment as a team to go all in on claude code, and have been sharing prompts, skills, etc, and documented all of our projects and at this point, claude is writing a _large_ percentage of our code. Probably upwards of 70 or 80%. It's also been updating our jira tickets and github PRs, which is probably even more useful than writing the code.

Our test coverage has improved dramatically, our documentation has gotten better, our pace of development has gone up. There is also a _big_ difference between the quality of the end product between junior and senior devs on the team.

Junior devs tend to be just like "look at this ticket and write the code."

Senior devs are more like: Okay, can you read the ticket, try to explain to to me in your own words, let's refine the description, can you propose a solution -- ugh that's awful, what if we did this instead.

You would think you would not save a lot of time that way, but even spending an _hour_ trying to direct claude to write the code correctly is less than the 5-6 hours it would take to write it yourself for most issues, with more tests and better documentation when you are finished.

When you first start using claude code, it feels like you are spending more time to get worse work out of it, but once you sort of build up the documentation/skills/tools it needs to be successful, it starts to pay dividends. Last week, I didn't open an IDE _once_ and I committed several thousands lines of code across 2 or 3 different internal projects. A lot of that was a major refactor (smaller files, smaller function sizes, making things more DRY) that I had been putting off for months.

Claude itself made a huge list of suggestions, which I knocked back to about 8 or 10, it opened a tracking issue in jira with small, tractable subtasks, then started knocking out one at a time, each of them being a fairly reviewable PR, with lots of test coverage (the tests had been built out over the previous several months of coding with cursor and claude that sort of mandated them to stop them from breaking functionality), etc.

I had a coworker and chatgpt estimate how long the issue would take if they had to do it without AI. The coworker looked at the code base and said "two weeks". Both claude and chat GPT estimate somewhere in the 6-8 weeks range (which I thought was a wild over estimate, even without AI). Claude code knocked the whole thing out in 8 hours.

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