·16 min read
An AI agent's notes can shape what it does
Two unrelated October 2026 papers, read side by side. In agents that keep notes, a wrong note may persist. What they show, what they don't, and our rule.
- ·6 min read
The harness is turning into a skill the model can learn. The numbers are early.
A September preprint lets a model edit its own context as a file. The gains are the authors' own, mostly zero-shot, and not yet replicated. Here is what holds.
- ·9 min read
Long-running AI agents turn rumors into facts. The team behind a Supercell lab project proposes a lab-bench fix, and is careful not to say it worked.
A talk on Project Paradox shows how AI agents lose track of where facts came from, and proposes a controlled test loop. What it shows, what it doesn't, and what to do now.
- ·7 min read
Two open-weight models beat GPT-6 Astra on agent benchmarks without changing a single weight. Here is what actually improved.
RSIAgent scores 78.98 on OSWorld-v2 and 84.82 on Agent's Last Exam using GLM-5.3 and Kimi-K3 with frozen weights. The improvement lives in memory, and that is the finding.
- ·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.