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AI Automation and Agentic Operations Articles
Operator-focused essays on AI agents, automation systems, workflow proof, operating layers, and the control surface between prompts and business results.
Start here when the question is how to move AI agents beyond demos: define the work packet, preserve state, require proof, assign ownership, and track automation value.
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About Steve Franey
Background on Steve's operator-focused publishing, automation, and education work.
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AI Agent Testing Is the New Operating Discipline
AI agent testing is now an operator problem: define tasks, evidence, approval gates, regression checks, and production stop rules before agents touch customers.
AI Agents Need an Operating Layer, Not Another Demo
A practical operator-grade essay on why AI agents need ownership, state, approvals, validation, and audit trails before they can become reliable business infrastructure.
The AI Automation Ledger: The Missing System Between Prompts and Profit
A practical framework for tracking AI automations by owner, workflow, evidence, approval state, validation, business impact, and next action.
AI Agents Won't Save Broken Operations. They'll Expose Them.
A practical operator-grade essay on why AI agents expose weak workflows, brittle approvals, missing audit trails, and fuzzy ownership before they create leverage.