Comment by sothatsit | Hacker News Reader

Comment by sothatsit | Hacker News Reader

AI building complex visualisations for you on-the-fly seems like a great use-case.

For example, if you are debugging memory leaks in a specific code path, you could get AI to write a visualisation of all the memory allocations and frees under that code path to help you identify the problem. This opens up an interesting new direction where building visualisations to debug specific problems is probably becoming viable.

This idea reminds me of Jonathan Blow's recent talk at LambdaConf. In it, he shows a tool he made to visualise his programs in different ways to help with identifying potential problems. I could imagine AI being good at building these. The talk: https://youtu.be/IdpD5QIVOKQ?si=roTcCcHHMqCPzqSh&t=1108

Independently of visualizations, I think LLMs allow in general the creation of ad-hoc tools.

I've experienced the case where asking for a quick python script was faster and more powerful than learning how to use a cli to interact with an API.

Anecdotally, the low time to prototype has had me throwing usable tool projects up on my local network. I wrote a meal planner and review tool for our weekly vegetable share, and local board game / book library that guests can connect to and reference.

It scratches the itch to build and ship with the benefit of a growing library of low scope, high performance, highly customized web tools I can write over a few hours in an evening instead of devoting weekends to it. It feels like switching from hand to power tools

Same. It's very handy to be able to ask for one-off tools for things that I _could_ try to figure out, but probably wouldn't be worth the time. My favorite example so far was a Python script to help debug communication between a microcontroller and a motor driver. I was able to dump the entire datasheet PDF for the driver into Gemini and ask it for a Python CLI to decode communication traffic, and 30 seconds later it was done. Fantastic bang/buck ratio!

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