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Guides, product updates, and ideas on AI-powered project management.

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 (56)
  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. Project steering tools: what a board does not do, and how to choose
  10. Steering a programme with AI agents: what the agent prepares, what you decide
  11. A project steering dashboard: the widgets that trigger decisions
  12. Turn a client email into clear tasks with AI
  13. Your AI agent says “done”: how to check its work
  14. Will AI change your job? 9 practical uses already at work
  15. Always setting AI to maximum? That is often a mistake
  16. Local, cloud, or hybrid AI: how to choose
  17. Claude Fable 5.1 vs Opus 5: which model should your AI agents use?
  18. GPT-5.6 Sol, Terra, and Luna: which OpenAI model should your AI agents use?
  19. MCP vs REST API: which architecture should you choose for AI agents?
  20. AI agent, AI workflow, or automation: which should you choose in 2026?
  21. AI Model Fusion: Why the Future Is Not One Model, but a Multi-Agent Architecture
  22. The Future of AI Agents Is Orchestration, Not Intelligence
  23. AI Backlog Grooming: Keep the Backlog Clean Continuously
  24. AI Scrum Master: What It Can Do and What It Cannot
  25. AI Sprint Retrospective: Bring Facts to the Retro
  26. AI Standup: A Better Daily Update from Real Work
  27. How to Manage AI Agents in Project Management Without Losing Control
  28. Documentation and AI Memory: Why Your Agents Should Not Start From Zero
  29. Best AI Project Management Software in 2026
  30. Best ClickUp Alternatives in 2026 for Multi-Project Teams
  31. Best Linear Alternatives in 2026 for Product and Engineering Teams
  32. Best Notion Alternatives in 2026 for Product Teams
  33. How to Connect Docs, Delivery, and AI Agents in One Workflow
  34. Project Management with AI Agents in 2026
  35. Stellary Beta Is Open
  36. Notion vs ClickUp vs Linear vs monday: strengths and trade-offs in 2026
  37. GPT-6 Astra vs Claude Fable 5.1 vs Gemini 3.5 Flash vs Cursor
  38. GPT-5.4 vs Claude Opus 4.6 vs Gemini 3.1 Pro vs Composer 2 (archive, April 2026)
  39. Best AI Model for Backend Development in 2026
  40. Best AI Model for Code Review, Audits, and Security in 2026
  41. MCP for AI Coding Tools in 2026: What Actually Changes
  42. Introducing Stellary: Your AI-Powered Command Center
  43. How to Connect AI Agents to Stellary via MCP
  44. What Is AI Project Management? A Practical Guide for 2026
  45. AI-Assisted Project Piloting: From Signals to Controlled Action
  46. Save Hours Every Week with Stellary Automations
  47. Knowledge Management for Dev Teams: Stop Losing Context
  48. MCP Explained: How the Model Context Protocol Works
  49. How AI Improves Remote Team Collaboration in 2026
  50. Project Management vs. Piloting: The Key Difference
  51. How to Run Better Sprint Planning with AI in 2026
  52. Kanban vs. Scrum in the AI Era: How to Choose
  53. API-First Project Management: Why You Need an API
  54. How to Reduce Unnecessary Meetings with AI
  55. Why Context Matters for AI Project Assistants
  56. Stellary Early Access: What the First Phase Validated