February 19, 2026
The way Einstein's brain worked is how AI should retrieve information
Genius isn’t storing more. It’s retrieving better. SR-SI turns AI retrieval into short, indexed pathways instead of full-context scavenging.
Retrieval
February 23, 2026
RAG gives AI a library. SR-SI gives it something closer to a memory
RAG is human-curated retrieval. SR-SI is self-curated reconstruction. That shift is subtle in mechanics, but huge in implications for long-running AI work.
February 27, 2026
Computation is killing collaboration
Most teams treat LLM memory as a compute problem. It’s an architecture problem. SR-SI replaces bloated scaffolds with a simple retrieval prosthesis built on indices, markdown, and Git.
February 28, 2026
Why I went the opposite direction from spec-first
Spec-first tools aren’t wrong — they just don’t match how everyone thinks. SR-SI supports an architect’s workflow: sketch, test, refine, repeat, without context loss.
May 12, 2026
The memory problem
The first SR-SI lesson was not that AI needed more intelligence. It needed a better way to orient itself before it worked.
May 13, 2026
Memory is retrieval strategy, not storage
Better AI memory does not come from storing more context. It comes from giving the system a disciplined way to reconstruct the right context at the right time.
June 2, 2026
Context decay in AI isn't a model problem. Here's what it actually is.
Context decay usually comes from the way relevant information gets diluted inside long sessions, not from the model suddenly becoming less capable.