AI Workflows & Teams
Organize processes, materials and responsibilities so work can be repeated and shared.
Make a one-off method repeatable and transferable
Recommended reading
Should AI Work Live in a Project, Folder, or Conversation?
Give projects, files and conversations distinct roles, with an established place for important results.
All articles
- Knowledge & MemoryWhich Instructions Belong in AGENTS.md?Save durable, scoped, testable project rules in AGENTS.md. Keep one-off deliverables, temporary preferences, and stale facts in the current task.
- Knowledge & MemoryWhy Does AI Forget, and How Should You Manage Versions?Separate temporary context, retrievable memory, and authoritative files so AI work can survive long conversations without silently using stale versions.
- Workflow & AutomationWhat Is a Skill, and Which Work Is Worth Turning Into One?Use four checks—repetition, stable steps, defined inputs and outputs, and reviewable failure—to decide whether a workflow deserves a reusable Skill.
- Agents & CollaborationHow to Design Agent Permissions, Approvals, Stops, and RecoveryLimit access first, require approval before consequential actions, define stop conditions, and verify a recovery path before the agent runs.
- Workflow & AutomationHow to Prove an AI Workflow Is Repeatable Before AutomationTest standard input, variations, missing data, errors, and same-input reruns. Record intervention and decide go or not yet before scheduling.
- Team Adoption & SOPsHow to Build a Team SOP From a Personal AI WorkflowDocument purpose, roles, inputs, steps, checks, exceptions, and version ownership, then test the SOP with someone who did not design it.
- Workflow & AutomationHow to Test Whether a Skill, Plugin, or Workflow Is ReliableWrite the expected behavior first, then test normal, boundary, failure, rerun, and permission cases with saved evidence and a clear decision.