November 17, 2025
The LLM structural crisis: solving context decay with the AI Memory Prosthesis
Introducing Simulated Recall via Shallow Indexing (SR-SI), an architectural pattern for reducing context drift in long-running AI workflows.
Introducing Simulated Recall via Shallow Indexing (SR-SI), an architectural pattern for reducing context drift in long-running AI workflows.
Why long-running AI projects collapse around 200 prompts — and the architectural solution that breaks the limit.
The 200-prompt wall isn’t a model limitation — it’s a memory architecture problem. SR-SI adds an external memory layer to prevent context collapse.
PRDs decay on contact with reality. This post outlines an AI-native operating model that turns documentation from writing into evidence-based extraction.