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The Agentic Automation Canvas: a structured framework for agentic AI project design

New framework creates machine-readable contracts for AI agents across six key dimensions before deployment.

Deep Dive

Researcher Sebastian Lobentanzer introduced the Agentic Automation Canvas (AAC), an open-source framework for designing agentic AI systems. It structures projects across six dimensions—including scope, metrics, and governance—and exports as FAIR-compliant RO-Crate packages. The framework is implemented as a client-side web app with real-time validation. This provides developers and users with a versioned, shareable, and machine-interoperable contract to standardize AI agent project planning and communication before building begins.

Why It Matters

It provides a critical missing piece for responsible, scalable deployment of autonomous AI systems across industries.