2026
- Your Agent's Notes Are the Closest Thing It Has to Training Data
TL;DR: A new paper from Meta Superintelligence Labs, UC Berkeley and others measures how well frontier-model agents improve when their weights stay frozen and everything they learn goes into files: …
- From Prompt to Context to Memory: The Arc, Grounded on AWS
A while back I argued that context engineering had quietly replaced prompt engineering as the skill that decides whether an agent is any good [1]. That piece was the framing. This one is the build. I …
- Weekly Review — July 6-12, 2026
TL;DR: This week was about taking a big idea off the whiteboard and finding the exact AWS building block that turns it on. Two posts continue the “Whiteboard to Cloud” series: compression as the …
- How My Setup Learns While You Sleep
TL;DR: The thing that makes an agent get better over time is a loop, and the loop is the same whether you buy it or build it: capture raw interaction, consolidate it on a schedule, and keep the lesson …
- Weekly Review — June 29-July 5, 2026
TL;DR: This week was about where knowledge lives, who owns it, and where the real work actually is. Three posts climb the agent-memory ladder: naming the spectrum, then the retrieval mechanism (vector …
- Your Obsidian Vault Is a Knowledge Graph
🎬 Also available as a blog walkthrough video: a narrated screencast of this post. TL;DR: Tony Seale spent six months working almost entirely inside a markdown wiki wired to an LLM, and argued the most …
- Agent Memory Is a Spectrum, Not a Switch
🎬 Also available as a blog walkthrough video: a narrated screencast of this post. TL;DR: “My agent keeps forgetting things” is usually not a model problem. It’s a memory-architecture problem. Agent …
- Is RAG Still Needed with 1M+ Token Context Windows?
The Kofferklausur, Revisited In September 2024, a colleague asked an audience: “What is RAG?” I answered: Kofferklausur [1]. For non-German speakers: a Kofferklausur is an open-book exam. You bring …