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432 points tosh | 1 comments | | HN request time: 0.296s | source
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vander_elst ◴[] No.39998806[source]
With all these AI tools requiring a prompt, does it really simplify/speed up things? From the example: I have to write "add a name param to the 'greeting' function, add all types", then wait for the result to be generated, read it carefully to be sure that it does what I want, probably reiterate if the result does not match the expectation. This seems to me more time consuming than actually do the work myself. Does anyone has examples where promoting and double checking is faster than doing it on your own? Is it faster when exploring new solutions and "unknown territory" and in this case, are the answers accurate (from what I tried so far they were far off)? In that case how do you compare it with "regular search" via Google/Bing/...? Sorry for the silly question but I'm genuinely trying to understand
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1. anotherpaulg ◴[] No.40001669[source]
Thanks for checking out aider.

That demo GIF is just showing a toy example. To see what it's like to work with aider on more complex changes you can check out the examples page [0].

The demo GIF was just intended to convey the general workflow that aider provides: you ask for some changes and aider shares your existing code base with the LLM, collects back the suggested code edits, applies them to your code and git commits with a sensible commit message.

This workflow is generally a big improvement over manually cutting and pasting bits of code back and forth between the ChatGPT UI and your IDE.

Beyond just sending the code that needs to be edited, aider also sends GPT a "repository map" [1] that gives it the overall context of your codebase. This makes aider more effective when working in larger code bases.

[0] https://aider.chat/examples/

[1] https://aider.chat/docs/repomap.html