
Reverse-Engineer a Proprietary Hardware Protocol with AI
Use an advanced AI model to analyze raw packet sniffer logs and research notes to deduce an unknown, proprietary Bluetooth protocol and create a tool to interact with the hardware.
Implement an automated 'fix and commit' loop by configuring an AI stop hook. This hook runs quality checks on AI-generated code and automatically prompts the AI to fix any detected errors.

with Claire Vo

Using the Claude Agent SDK, write a script (e.g., in TypeScript) that will run automatically every time the AI agent finishes a task.
Add logic to the script to check for file changes. If files were modified by the AI, run a quality gate command like a linter or type checker (e.g., bun typecheck).
If the quality check fails, program the script to capture the error report and output a new JSON prompt instructing the AI to fix the specific errors. The script's console.log output is sent back to Claude.
{"prompt": "Please fix the TypeScript errors. Here is the report: ..."}If all checks pass, the script can trigger a subsequent action, such as instructing a background agent to generate a git commit message and commit the successful changes.
Link your script to the AI tool by adding a configuration to its settings file (e.g., settings.local.json for Claude Code), specifying the command to run the hook.
{
"claude.hooks.stop": [
{
"command": "bun run claude-hooks/index.ts"
}
]
}
Use an advanced AI model to analyze raw packet sniffer logs and research notes to deduce an unknown, proprietary Bluetooth protocol and create a tool to interact with the hardware.

Delegate a complex, multi-format data migration to an AI agent. The model will build the migration script, create a scalable testing system to validate its own work, and repair issues in a self-sustaining loop.

Use an advanced AI model like GPT-5.5 Pro in Codex to automatically analyze a CSV list of security vulnerabilities, group them thematically, propose architectural changes, and implement the necessary code fixes.
Join 100,000+ product managers who use ChatPRD to write better docs, align teams faster, and build products users love.