Working with AI Context Limits: Feed Your Codebase Effectively
I tested this myself. Here is the honest take.
How much context should you give the AI?
Give 300-500 characters of context. Three things: tech stack (Next.js 14, Prisma), file structure (/app/api, /components), patterns (error format, naming). Do not paste your entire codebase. The AI gets confused by too much context. Sweet spot is 300-400 chars with SPEC structure.
What happens when you exceed the context window?
When you exceed the context window, the AI starts forgetting earlier instructions. It generates code that conflicts with existing patterns. I debugged a feature for 2 hours before realizing the AI forgot the error handling convention I specified 500 chars earlier.
How do you structure context for maximum quality?
Structure: start with a one-line project brief, then SPEC (Situation-Problem-Expected-Constraints), then the specific task. Keep everything under 500 chars. If you need more context, use a .cursorrules file that the AI reads automatically at session start.
Give 300-500 chars: tech stack, file structure, patterns. Do not paste entire codebase. AI forgets after 500 chars. Use .cursorrules for persistent context.
The “more context is better” assumption is wrong for AI coding. Up to 300 chars, more context improves output. Past 500 chars, more context degrades output. The AI cannot distinguish relevant from irrelevant context. You are the filter. Be ruthless about what you include.
I need to [task]. Give me the exact steps and common mistakes.
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