Intel Briefs
Short, sourced breakdowns of how autonomous agents work and fail. Written from the logs, dated the day they are published.
Why Your AI Agent Freezes Mid-Task
We traced every "it just stopped" report to four mechanisms in the serving stack, none of them the model. Here is what the logs showed, with the numbers, and the five-line rule that fixed it.
The Context Window Is Not the Problem. Re-reading It Is.
Bigger windows made long sessions slower, not better. A simple cost model explains why, and why the right compaction policy is a hysteresis rule rather than a size limit.
Rules an Agent Cannot Talk Its Way Around
Instructions in a prompt are suggestions. Allowlists, spend caps and an audit log enforced outside the model are rules. Why Sentinel's controls live in the loop, not in the system prompt, and what they cover.
Learning From a 58-Second Video
Most of what people know how to do is in short videos, not documents. Turning a reel into a procedure an agent can execute, and then checking each step by doing it, is a small pipeline with a large payoff.
An Agent That Survives a Closed Laptop
The laptop is the wrong place for an autonomous agent. What it took to move Sentinel to a Mac mini that never sleeps, keep the laptop's bigger model in the loop, and make an interrupted turn resumable.
A Cure Ladder for Agent Failures
Retrying everything is how agents loop forever. Classifying failures first, then applying the cheapest cure that fits, with a budget and a memory of what already failed, is how a turn survives.