When a Session Forgets What It Knew: Why LLM State Management Breaks Under Load

I needed a mobile workflow. Capture a TikTok screenshot in the field, run it through ChatGPT for analysis, commit the result to GitHub. Two to three minutes total, standing on a sidewalk. What ChatGPT designed for me was an 8-step enterprise workflow with canonical templates, asset management pipelines, QC checkpoints, and multiple fallback procedures — including one that assumed GitHub Copilot mobile could parse YAML-style commands to create files in specific directories. Nobody had tested whether GitHub Copilot mobile could actually do any of this. ChatGPT's own critique of its own design was blunt: "8-step process with multiple fallbacks is complex for 2-3 minute field capture. System assumes desktop-level complexity when field capture needs simplicity." The recommendation that should have come first arrived last: "Test the core mobile Copilot execution capability first, then simplify the system based on actual mobile constraints rather than desktop assumptions." That ordering — des