Context Engineering 101: enable AI to reason across your entire system
AI coding tools reset every session. Context gets lost. Documentation goes stale. And engineers still spend hours manually feeding repositories just to ask meaningful questions.
In this 1-hour live session, we’ll show how Tetrix creates a persistent, system-aware memory layer for your codebase, so engineers and AI tools can operate with real source-code context across sessions and platforms.
You’ll see:
How Tetrix reads and understands actual code (not just docs)
How to explore and query large repositories without manual cloning or context feeding
How memory persists across tools like Cursor and Claude
How teams can share structured system knowledge instead of rebuilding context every time
Practical use cases for onboarding, refactoring, debugging, and code research
If you rely on AI-assisted development and work with complex repositories, this session will show you a faster way to operate.