From the grāmatr brain.
Real problems. Real code. Real decisions. Building an AI that actually gets smarter — and sharing what we learn along the way.
Why I Killed My 40,000-Token System Prompt
My CLAUDE.md file was 40,000 tokens. Claude was getting worse, not better. So I replaced it with 1,200 tokens of intelligence — and everything changed.
The AI Memory Market Is a Retrieval Market
Every AI memory tool stores facts and retrieves them. That's a solved problem. The unsolved problem is intelligence — and nobody in the market is working on it.
422 Commits, One Brain: A Week Powered by grāmatr
422 commits across 5 projects in one week. Two websites built. A CRM stood up. New Kubernetes services deployed. One person, with one intelligence pipeline running across every tool.
From Digital Agency to AI Brain: The 19-Year Journey of gramatr.com
In 2007 I founded a digital agency on gramatr.com. In 2026, the same domain powers a context engineering platform. The thread connecting them: data lives in silos, context gets lost, and the people doing the work spend too much time re-explaining what should already be known.
How grāmatr Mirrors the Human Brain
I didn't set out to build a brain. But the architecture I converged on — fast classification, selective retrieval, modular processing, feedback consolidation — is the same architecture the human brain uses. Here's the neuroscience.
Context Engineering: What Anthropic, Karpathy, and Shopify's CEO Agree On
The biggest names in AI are converging on a single idea: the models are good enough. The problem is context. Here's what context engineering means, why it matters, and how grāmatr automates it.
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