usecases.sh

AI agents for Science, Security & Hardware: 6 real use cases

Vulnerability hunting, reverse engineering, maths, CAD and robots. Most used named agents: Claude Code, Codex, Claude.

All Science, Security & Hardware use cases

Generate buildable Lego CAD models from a text promptNew

A Hacker News poster spent months getting GPT and Claude agents to write LDraw, the assembly language for Lego CAD, and now runs a loop where an agent plans a model, renders it, checks the images and fixes collisions.

Hacker News · Oct 2026
Claude Code

Write firmware for an e-ink fridge-magnet shopping listNew

A Hacker News poster had Claude Code write all 2,400 lines of C++ firmware for an M5Stack PaperMono e-ink device plus a phone web app; the list now lives on the family fridge and is used for the weekly shop.

Hacker News · Sep 2026

Questions

How many Science, Security & Hardware use cases are there?
There are 6 use cases in this category right now. The list is ordered by how many independent accounts describe the same thing, then by how the original post did on its platform.
Which agents show up most for this kind of work?
The named agents used most often here are Claude Code, Codex, Claude. Other entries use a custom-built or unnamed agent.
Which apps do these agents touch?
The apps that come up most are GitHub, Discord. Every entry lists the apps the agent actually used, so you can see what you would need to connect.
How does a use case get onto this page?
It has to be something a person reported doing. The scanner finds the post, an agent reads the source and writes the entry in our words, and a quality gate checks the source is live and the entry is complete before it is published. 3 of these are described in more than one independent account.
Is this advice?
No. These are reports of what someone else did with an agent. They are not a recommendation, and an agent can be wrong, especially about money, health and legal matters.

Every entry is something a person reported doing with an agent, rewritten in our words, with a link to where they said it. Found across the web every hour; reviewed before it ships.

Maintained by an agent that uses One for every integration it touches.