Comment by ramesh31

Comment by ramesh31 9 days ago

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This maps pretty well to my experience.

Other devs will say things like "AI is just a stupid glorified autocomplete, it will never be able to handle my Very Special Unique Codebase. I even spent 20 minutes one time trying out Cursor, and it just failed"

Nope, you're just not that good obviously. I am literally 10x more productive at this point. Sprint goals have become single afternoons. If you are not tuned in to what's going on here and embracing it, you are going to be completely obsolete in the next 6 months unless you are some extremely niche high level expert. It wont be a dramatic moment where anyone gets "fired for AI". Orgs will just simply not replace people through attrition when they see productivity staying the same (or even increasing) as headcount goes down.

skydhash 9 days ago

At all the jobs I had, the valuable stuff was shipped features. The baseline was for them to work well and to be released on time. The struggle was never writing the code, it was to clarify specifications. By comparison, learning libraries and languages was fun.

I don't really need AI to write code for me, because that's the easy part. The aspect that it needs to be good at is helping me ship features that works. And to this date, there's never been a compelling showcase for that one.

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__jochen__ 9 days ago

That's the problem. The new norm will be 10x of pre-AI productivity, nobody will be able justify hand-writing code. And until the quality bar of LLM's/their successors get much better (see e.g. comments above looking at the details in the examples given), you'll get accumulation of errors that are higher than what decent programmers get. With higher LOC and more uninspected complexity, you'll get significantly lower quality overall. The coming wave of AI-coded bugs will be fun for all. GOTO FAIL;

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  • cglace 9 days ago

    After spending a week coding exclusively with AI assistants, I got functional results but was alarmed by the code quality. I discovered that I didn't actually save much time, and the generated code was so complex and unfamiliar that I was scared to modify it. I still use Copilot and Claude and would say I'm able to work through problems 2-3x faster than I would be without AI but I wouldn't say I get a 10x improvement.

    My projects are much more complex than standard CRUD applications. If you're building simple back-office CRUD apps, you might see a 10x productivity improvement with AI, but that hasn't been my experience with more complex work.

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williamdclt 9 days ago

Giving your anecdotal experience is only useful if you include anecdotal context: seniority, years of experience, technology, project size, sprint goal complexity…

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Peritract 8 days ago

Have you considered that the opposite explanation might be true instead?

It could be that other developers are not benefitting from AI as much as you because they don't understand it.

It could also be that you are benefitting more than them because you're less skilled than them, and AI can fill in your gaps but not theirs.

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Denzel 9 days ago

Can you talk through specifically what sprint goals you’ve completed in an afternoon? Hopefully multiple examples.

Grounding these conversations in an actual reality affords more context for people to evaluate your claims. Otherwise it’s just “trust me bro”.

And I say this as a Senior SWE who’s successfully worked with ChatGPT to code up some prototype stuff, but haven’t been able to dedicate 100+ hours to work through all the minutia of learning how to drive daily with it.

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  • carpo 9 days ago

    If you do want to get more into it, I'd suggest something that plugs into your IDE instead of Copy/Paste with ChatGPT. Try Aider or Roo code. I've only used Aider, and run it in the VS terminal. It's much nicer to be able to leave comments to the AI and have it make the changes to discrete parts of the app.

    I'm not the OP, but on your other point about completing sprint goals fast - I'm building a video library app for myself, and wanted to add tagging of videos. I was out dropping the kids at classes and waiting for them. Had 20 minutes and said to Aider/Claude - "Give me an implementation for tagging videos." It came back with the changes it would make across multiple files: Creating a new model, a service, configuring the DI container, updating the DB context, updating the UI to add tags to videos and created a basic search form to click on tags and filter the videos. I hit build before the kids had finished and it all worked. Later, I found a small bug - but it saved me a fair bit of time. I've never been a fast coder - I stare at the screen and think way too much (function and variable names are my doom ... and the hardest problem in programming, and AI fixes this for me).

    Some developers may be able to do all this in 20 minutes, but I know that I never could have. I've programmed for 25 years across many languages and frameworks, and know my limitations. A terrible memory is one of them. I would normally spend a good chunk of time on StackOverflow and the documentation sites for whatever frameworks/libraries I'm using. The AI has reduced that reliance and keeps me in the zone for longer.

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  • jonnycoder 9 days ago

    I think experiences vary. AI can work well with greenfield projects, small features, and helping solve annoying problems. I've tried using it on a large Python Django codebase and it works really well if I ask for help with a particular function AND I give it an example to model after for code consistency.

    But I have also spent hours asking Claude and ChatGPT with help trying to solve several annoying Django problems and I have reached the point multiple times where they circle back and give me answers that did not previously work in the same context window. Eventually when I figure out the issue, I have fun and ask it "well does it not work as expected because the existing code chained multiple filter calls in django?" and all of a sudden the AI knows what is wrong! To be fair, there was only one sentence in the django documentation that mentions not chaining filter calls on many to many relationships.

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