Ix

Let us know if you have any feedback. We welcome contributors and are working every day to improve based on what our users want. GitHub = https://github.com/ix-infrastructure/Ix Open source & free to use

Stop playing 20 questions with your AI every session. Every time you start a new session your agent has no idea what system it's working in. Not just losing conversation history, losing the entire architecture. We tried throwing more context at it. Didn't help. The problem wasn't retrieval. There was no map. So we built one. Ix builds a structured architectural map of your codebase deterministically from the actual code. No LLM inferring structure, no guessed relationships, nothing to drift as your code changes. ix map . runs in under 90 seconds. We've been using it ourselves and the difference in how AI agents reason about our system is pretty significant. Context that actually persists. Fewer redundant questions. Better answers. Two weeks in, 190 stars, plugins live for Claude Code, Codex, OpenCode, and Gemini CLI. Homebrew submission i

https://github.com/ix-infrastructure/Ix sorry heres the link.

2 approaches are emerging for giving ai agents structural understanding of a codebase. 1. LLM inferred. fast to build. but edges are labeled INFERRED because the model is just guessing. confidence scores include bc it knows it could be wrong 2. deterministic. built straight from the actual code. same input same output every time. no guessing so my question is: why on earth is the inferred approach winning on github right now?? it seems clear to me which one wins. Does deterministic structure matter to you or is inference good enough. Need to know based on what im building here https://github.com/ix-infrastructure/Ix

We give spearheads to caveman Call it Ix Help caveman save even more tokens https://github.com/ix-infrastructure/Ix