AI Agents
AI Agent Permissions: The Ladder From Read to Act
How to think about AI agent permissions, approval gates, private data, money movement, reversibility, and audit trails.
Ai Agents
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AI Agents
How to Delegate to AI Agents: A Playbook for Better Tasks
A practical narrative guide to turning vague work into clear AI agent assignments with outcomes, boundaries, …
AI Agents
The Future of AI Agents: Permission, Memory, and the Open Agentic Web
A grounded forecast of AI agents: personal delegates, enterprise fleets, open protocols, safety, identity, robotics, and …
AI Agents
What AI Agents Are: The Moment Software Started Taking Initiative
A clear narrative definition of AI agents, how they differ from chatbots and automation, and why the term matters.
AI Agents
What AI Agents Can Do Now: From Errands to Real Work
A grounded tour of what AI agents can already do in research, coding, operations, customer support, and personal …
AI Agents
AI Agent Workflow Discovery: Finding the Work Worth Delegating
How to find agent-worthy workflows before building them, by studying real work paths, context movement, exception …
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 …
AI Agents
AI Agent Rollback and Recovery: Designing a Way Back
How to design AI agent workflows with reversible changes, stop controls, snapshots, compensating actions, recovery …
AI Agents
AI Agent Capability Inventories: Knowing What the Delegate Can Really Do
How to keep a practical inventory of an AI agent's tools, permissions, model lane, context sources, review needs, and …
AI Agents
AI Agent Trigger Design: Deciding When a Delegate Should Start
How to design safe AI agent triggers from inboxes, schedules, webhooks, queues, and manual requests without creating …
AI Agents
AI Agent Input Normalization: Preparing Messy Requests Before the Run
How to turn messy requests, attachments, records, and source material into stable AI agent inputs without hiding …
AI Agents
AI Agent Environment Parity: Keeping Test Runs Close to Real Work
How to keep AI agent sandboxes, staging lanes, tools, data shapes, clocks, permissions, and validation steps close …
AI Agents
AI Agent Concurrency: Locks, Leases, and Shared Work
How to keep parallel AI agent runs from colliding by using ownership, locks, leases, idempotency, checkpoints, and …
AI Agents
AI Agent Knowledge Freshness: Keeping Sources From Going Stale
How to manage freshness for AI agent knowledge bases, retrieved evidence, memory, checkpoints, and artifacts so old …
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 Decommissioning: Retiring Delegates Without Losing the Work
How to retire AI agent workflows cleanly by stopping new work, preserving evidence, revoking access, redirecting tasks, …
AI Agents
AI Agent Intake Packets: Framing Work Before It Starts
How to prepare AI agent task intake packets with scope, sources, constraints, permissions, acceptance criteria, and …