@dabit3: Now that agents can act, we ask: when should they run, what can they touch, how is their work checked, and what context…
Summary
The author proposes Automation Engineering as a discipline for designing triggers, guardrails, and success checks to make AI agents safe and reliable without constant human oversight.
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Now that agents can act, we ask: when should they run, what can they touch, how is their work checked, and what context do they get? It’s Automation Engineering, but for AI agents instead of factory floors.
Software Engineering: translating requirements into reliable systems.
Automation Engineering: designing the triggers, guardrails, and success checks that let cloud agents do useful work safely, without someone having to start them, steer them, or watch them.
Automation Engineering belongs in the agent toolchain, alongside the models, tools, integrations, evals, and deployment systems we already use.
This is a big focus and area of growth for us at @cognition https://docs.devin.ai/product-guides/automations…
example - dead code automation (h/t @lukerramsden for the prompt direction)
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