AI Agents
AI Agent Source Provenance: Keeping Evidence Attached to the Work
How to keep source evidence, tool results, uncertainty, and version context attached to AI agent outputs so reviewers …
Human Review
AI Agents
AI Agent Feedback Loops: Turning Corrections Into Better Delegation
How to turn human corrections, rejected outputs, review notes, traces, and production surprises into better AI agent …
AI Agents
AI Agent Review Queues: Moving Human Judgment Without Bottlenecks
How to design AI agent review queues that route delegated outputs through triage, evidence review, approval, revision, …
AI Agents
AI Agent Acceptance Criteria: Defining Done Before Delegation
How to define acceptance criteria for AI agent work so delegated tasks finish with evidence, boundaries, validation, and …
AI Agents
AI Agent Status Updates: How Delegates Should Report Progress
How AI agents should communicate progress, blockers, evidence, changes, and next actions during delegated work without …
AI Agents
AI Agent Escalation Paths: Knowing When to Ask for Help
How to design escalation paths for AI agents so uncertainty, missing access, risk, and blocked work reach the right …
AI Agents
AI Agent Artifact Design: Turning Runs Into Reviewable Work
How to design AI agent outputs as durable artifacts with evidence, provenance, versioning, validation, and handoff …
AI Agents
AI Agent Output Verification: Checking Work Before It Becomes Trusted
How to verify AI agent outputs against the original task, source evidence, tool results, permissions, tests, and handoff …
AI Agents
AI Agent Control Surfaces: Designing Interfaces for Delegated Work
How to design the human-facing interface around AI agents: state, approvals, evidence, interruptions, permissions, and …
AI Agents
Human Review for AI Agents: The Handoff That Makes Delegation Work
A narrative guide to human review in AI agent workflows: handoffs, approval gates, audit trails, risk levels, evidence, …