Context Guide: How to Give AI Full Memory
What is Code Context?
Code context is the information that helps models understand your existing codebase and generate code that fits—placement, naming, dependencies, and architecture.
Concrete Example
Asking an AI to 'add a user authentication function' works best when the model sees your auth patterns, naming conventions, and error handling approach.
How to Provide Full Code Context
- Expose file/folder structure and where new modules belong.
- Show naming styles, comments, and testing patterns.
- Include dependency graph and common utility helpers.
- Reference API styles (e.g., JSON schemas, error envelopes).
Why Increasing Context Is Essential
- Inconsistent Style: Without conventions, outputs default to an average style.
- Wrong Placement: Files land in the wrong feature area or module.
- Duplicate or Missing Functionality: Helpers get re-implemented or omitted.
- Broken Dependencies: Import paths and library choices drift.
- Misaligned Architecture: High-level patterns aren’t respected.
- Higher Error Rate & Hallucinations: Missing types/tests increases guesswork.