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> An AI agent implementation playbook is the ordered sequence that moves an agent from a chosen use case to trusted, unsupervised production. Its seven stages (scope, score, design, build, evaluate,...
Jun 22, 2026/ recent · long reads
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> An AI agent risk assessment framework scores a single agent workflow on five factors (autonomy, reversibility, data sensitivity, customer impact, and auditability) to decide how much oversight it...
Jun 22, 2026
> AI agent security is the practice of capping what a deployed agent, and anyone who hijacks it, can do to the systems and data it touches. The agent's defining flaw, that it cannot tell data from...
Jun 22, 2026/ selected notes
All dispatches →01 / Workflows
> An AI agent governance framework is the set of runtime controls (scoped permissions, approval gates, exception queues, human review, audit trails, and a kill switch) plus the single accountable...
Jun 22, 2026
02 / AI Agents
> An AI agent ROI measurement framework separates an agent's return into four classes (cost avoidance, capacity creation, risk and quality, and revenue lift) and measures each one on the clock it...
Jun 22, 2026
03 / AI Agents
> AI agent performance metrics are the numbers a business tracks to confirm a deployed AI agent does its job correctly, safely, affordably, and fast enough to matter. Marshal sorts them into five...
Jun 11, 2026
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