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
- Agents & CollaborationManaging an AI Team Instead of Editing the Version MyselfA website redesign becomes a case study in managing AI roles: defining outcomes, inviting disagreement, reviewing results, and preserving context at handoffs.
- Agents & CollaborationWhy I Keep AI Tools Isolated During CollaborationSeparate AI conversations, share files, and keep human judgment at the handoff. A collaboration experiment explains why deliberate context isolation matters.
- Agents & CollaborationFive AI Agent Patterns—and When Not to Use ThemCompare tool use, planning, multi-agent coordination, and metacognition through Microsoft's agent lessons, including failure modes and when to avoid each pattern.
- Knowledge & MemoryFour Context Failures—and the Cost Paradox Behind ThemMicrosoft's context and memory lessons frame four context failures, mitigation choices, and trade-offs among memory tools, information quality, and cost.
- RAGAgentic RAG vs. Traditional RAG: Five Differences That MatterAgentic RAG can rewrite queries, change retrieval methods, and check its own results. Compare that loop with traditional RAG and when the added complexity helps.
- Workflow & AutomationWhy I Turned Seven Workflows into SkillsSeven custom workflows reveal how to choose between a Skill, CLAUDE.md guidance, and shared rules when organizing repeatable work in Claude Code.
- Knowledge & MemoryDesign the Knowledge Base, Not the AI ToolA personal knowledge-system design moves beyond choosing an AI tool. Three reframing questions lead to a four-layer architecture and a more durable foundation.