TLDR:
1. create a session_map.mdfile where your model(s) log work during each session, serving as a centralized, minimal record.
2. add comments at the end of every file created/edited referencing session_map.mdfile.
3. create ainstruction_history.mdfile that serves as a high-level overview of the instructions that have shaped the codebase, helping developers assess its health, consistency, and progress.
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In the evolving landscape of AI-driven coding, managing context effectively is critical to maintaining model performance and avoiding issues like context poisoning — where excessive or irrelevant context overwhelms the model, leading to degraded outputs or unexpected behavior. To address this, I propose a novel approach called Session Mapping, a lightweight method to track and reference key details of coding sessions without bloating the context window. This post outlines the concept, its implementation, and its benefits for AI-assisted development workflows, including a complementary file to track instruction history for enhanced codebase oversight.
The Problem: Context Overload
Large language models like Claude or Grok thrive on context, but too much context can backfire. When every detail of a coding session —…