·5 min read
Strategic Intent as Part of the Agent Environment
Persistent operator intent and peer delegation need tests that measure useful work, preserved authority, and the human effort still required.
- ·6 min read
Can a Smaller AI Model With Better Memory Beat a Bigger One?
A new Qwen paper trained a 9-billion-parameter agent to navigate its memory as a set of tools instead of consuming pre-fetched context, and it out-scored the same system built on a 397-billion-parameter model. The result is real and useful. The 'small model beats giant' version traveling online drops three caveats that change what it means, and the paper's own word for the result is 'competitive.'
- ·8 min read
Does Better AI Agent Memory Come From Training or From Structure?
Stanford built a system to learn memory management as a trainable skill. Its own ablation answered the question: structure, schemas, prompts, and gates delivered most of a 2-4x gain before any training happened. Here is what that means for anyone running agents, and the six disciplines you can adopt without training anything.
- ·5 min read
Agent Memory Is Infrastructure, Not a Feature
Most teams build an agent knowledge base and stop. Keeping it from rotting in production is the hard part. Agent memory is infrastructure, and infrastructure needs hygiene.