Explore how real professionals across different industries and roles leverage AI as a tool. Each use case includes practical examples and community stories from around the web.
2 use cases across all industries
Documents LLM usage directly in Git history—sometimes via inline comments, but primarily via per-commit `Co-authored-by` trailers that record the model/provider—so teams can later identify where AI-generated code entered the codebase (useful for review, provenance, and potential legal/indemnity requirements).
Uses LLM chat and agent tools (e.g., CodeCompanion.nvim, Ollama/OpenWebUI, Crush with Copilot backend, Claude Code) to delegate tasks like implementing failing tests, debugging why code doesn’t work, and drafting larger changes that are written into the codebase.