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AI project management

AI project management is the practice of running planning, execution, and delivery with AI systems as active participants — agents that prepare sprints, triage backlogs, draft documentation, and execute missions — rather than as assistants that only summarize what humans did.

The articles in this hub cover the full spectrum: what AI project management actually means, how to plan sprints with AI, how to manage agents like team members, and which models hold up when the cost of being wrong becomes real.

See how Stellary applies this in practice
Can AI agents run a sprint? Six project management tools compared
Featuredresearchaiagentsproject-managementcomparison

Can AI agents run a sprint? Six project management tools compared

Compare the documented agent capabilities of Linear, ClickUp, Notion, Asana, monday, and Stellary across one reproducible sprint benchmark.

11 min read
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An AI-ready project brief: the template that stops endless prompting
aiguideproject-managementagents

An AI-ready project brief: the template that stops endless prompting

An AI project brief connects outcomes, scope, sources, constraints, and validation. Use this template before assigning work to an agent.

6 min read
How to coordinate multiple AI coding agents without collisions
aiagentsdevelopmentguide

How to coordinate multiple AI coding agents without collisions

Task boundaries, context, worktrees, contracts, and integration: a method for running multiple AI coding agents in parallel without multiplying conflicts.

6 min read
GPT-6 Astra vs Claude Fable 5.1: which model should you use for coding?
aiagentsopenaianthropiccomparison

GPT-6 Astra vs Claude Fable 5.1: which model should you use for coding?

Astra or Fable 5.1? Compare capabilities, pricing, context, safeguards, and agentic workflows to choose the right coding model.

11 min read
Vibe coding: move from prototype to product without rewriting everything
aiguidedevelopmentproject-management

Vibe coding: move from prototype to product without rewriting everything

Vibe coding accelerates prototyping. Use this practical method to secure architecture, data, testing, and deployment before going to production.

7 min read
The MCP servers worth connecting to Claude Code (and the order to add them)
mcpguideai

The MCP servers worth connecting to Claude Code (and the order to add them)

Ten MCP servers that earn their place in a Claude Code setup — repository, docs, browser, database, project tool — what to allow, and the order to add them.

6 min read
Building a video game with AI is easy. Finishing one isn’t.
aiguideproject-management

Building a video game with AI is easy. Finishing one isn’t.

Building a video game with AI takes more than code. Follow a practical method to organize mechanics, assets, tests, decisions, and agents in one project.

7 min read
All articles (39)
  1. Can AI agents run a sprint? Six project management tools compared
  2. An AI-ready project brief: the template that stops endless prompting
  3. How to coordinate multiple AI coding agents without collisions
  4. GPT-6 Astra vs Claude Fable 5.1: which model should you use for coding?
  5. Vibe coding: move from prototype to product without rewriting everything
  6. The MCP servers worth connecting to Claude Code (and the order to add them)
  7. Building a video game with AI is easy. Finishing one isn’t.
  8. The steering committee of an AI project: who, how often, what agenda
  9. Steering a programme with AI agents: what the agent prepares, what you decide
  10. Turn a client email into clear tasks with AI
  11. Your AI agent says “done”: how to check its work
  12. Will AI change your job? 9 practical uses already at work
  13. Always setting AI to maximum? That is often a mistake
  14. Local, cloud, or hybrid AI: how to choose
  15. Claude Fable 5.1 vs Opus 5: which model should your AI agents use?
  16. GPT-5.6 Sol, Terra, and Luna: which OpenAI model should your AI agents use?
  17. MCP vs REST API: which architecture should you choose for AI agents?
  18. AI agent, AI workflow, or automation: which should you choose in 2026?
  19. AI Model Fusion: Why the Future Is Not One Model, but a Multi-Agent Architecture
  20. The Future of AI Agents Is Orchestration, Not Intelligence
  21. AI Backlog Grooming: Keep the Backlog Clean Continuously
  22. AI Scrum Master: What It Can Do and What It Cannot
  23. AI Sprint Retrospective: Bring Facts to the Retro
  24. AI Standup: A Better Daily Update from Real Work
  25. Documentation and AI Memory: Why Your Agents Should Not Start From Zero
  26. Best AI Project Management Software in 2026
  27. GPT-6 Astra vs Claude Fable 5.1 vs Gemini 3.5 Flash vs Cursor
  28. GPT-5.4 vs Claude Opus 4.6 vs Gemini 3.1 Pro vs Composer 2 (archive, April 2026)
  29. Best AI Model for Backend Development in 2026
  30. Best AI Model for Code Review, Audits, and Security in 2026
  31. MCP for AI Coding Tools in 2026: What Actually Changes
  32. How to Connect AI Agents to Stellary via MCP
  33. What Is AI Project Management? A Practical Guide for 2026
  34. AI-Assisted Project Piloting: From Signals to Controlled Action
  35. MCP Explained: How the Model Context Protocol Works
  36. How AI Improves Remote Team Collaboration in 2026
  37. How to Run Better Sprint Planning with AI in 2026
  38. How to Reduce Unnecessary Meetings with AI
  39. Why Context Matters for AI Project Assistants