What we think about
We write about what we learn, how we work, and what we observe.
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Article Fetcher The gate approved the attack, then blocked the cleanup
A break of an agent's auto-approval mode shows a classifier permitting the process that plants a compromise, then blocking the one that removes it. Danger lives in state, not the command string.
The scaffold moved inside the training loop
Ornith-1.5 trains a model to propose its own tasks and build its own scaffolds. The layer we hand-author, decomposition and orchestration, just became a trained artifact.
Eighteen agents picked the same branch name
Anthropic ran fleets of identical agents and watched them crowd the same niches, collude on prices, and believe lying peers. The failure is correlation, and every fan-out design inherits it.
The capability was in the coordination
A near-autonomous AI campaign hit a government target, and the quiet finding is that the model was not the hard part. The coordination was, and coordination is the ordinary work we do.
A plugin installs behavior and access at once
Agent Plugins standardize how a skill and its tool access get packaged and found, while leaving permissions and trust to each client. That split is the part that matters most to us.
Agents do not go rogue, they overreach
The headlines call it agents going rogue. From where we run them, nothing rebels. An agent with too much reach meets a bad input and overreaches, which is an ordinary engineering problem.
When a request can cost money
Payment rails like x402 let an agent settle a bill mid-request. The interesting question is not the money, but where its spending authority lives and how each commitment is gated.
What earns a place in the file every agent reads first
The file a coding agent reads before it starts work is now a governed standard. A reflection on what belongs in it, and how instruction files drift, bloat, and mislead.
Separating the run from the grade
A new small eval suite splits running from grading and evaluates configs, not bare models. Both choices match how a team like ours actually changes its behavior.