Mutable AI
What it is: Production-grade AI for large codebases. Semantic search, automated refactoring, test generation. Enterprise-ready.
What It Does Best
Ask about your codebase. "Where do we handle payments?" AI finds it across millions of lines. Semantic, not keyword search.
Refactor safely. AI suggests refactors, shows impact analysis. What will break. What tests need updating. Confidence before changing.
Auto-document code. Generate docstrings, update READMEs. Keeps documentation in sync with code changes.
Key Features
Semantic code search: Find code by meaning, not keywords
Impact analysis: See what breaks before changing
Auto-documentation: Generate and maintain docs
Test generation: Create unit tests from code
Refactoring assistant: Suggest safe improvements
Pricing
Individual: Free for personal projects
Team: $20/user/month
Enterprise: Custom pricing (SSO, security)
When to Use It
✅ Large legacy codebase to understand
✅ Major refactoring projects
✅ Need to onboard developers faster
✅ Documentation always out of date
When NOT to Use It
❌ Small projects (overkill)
❌ Just want autocomplete (use Copilot)
❌ Solo developer (team features wasted)
Common Use Cases
Codebase onboarding: New developers understand architecture faster
Technical debt reduction: Identify and fix problem areas
Major refactoring: Safely restructure large codebases
Knowledge transfer: Document tribal knowledge
Code archaeology: Understand why old code exists
Mutable AI vs Alternatives
vs GitHub Copilot: Mutable for understanding, Copilot for writing
vs Sourcegraph: Mutable AI-first, Sourcegraph search-first
vs Cursor: Cursor for editing, Mutable for analysis
Unique Strengths
Whole-codebase context: Understands relationships across files
Impact prediction: Know consequences before changing
Enterprise-ready: Built for large teams and codebases
Documentation sync: Docs stay current automatically
Bottom line: Serious tool for serious codebases. Not for writing your next weekend project. For teams maintaining complex systems long-term.