Lawrence Rowland

AI-Driven Project Management Methodologies

• GPTs as low-code tools for project teams
• Custom GPTs with domain-specific project knowledge
• AI-augmented communication and documentation
• Retrieval-Augmented Generation (RAG) for document use
• AI agents with defined project roles (e.g., risk analyst)
• Flywheel of AI learning through early adoption

Experiments in AI for Projects

• GPT-to-GPT collaboration on project strategy and literature
• Role-based AI agents simulating project team interactions
• "Thinking" agents that operate asynchronously
• Ontology-driven app-building using AI coders

Frameworks & Predictions

• Project GPT Framework: AI-augmented team models
• Thinker vs Builder agents: classification for delegation
• AI Flywheel: compounding benefits of early AI use
• Democratisation: making PM tools accessible via AI
• Ethical governance: transparency and validation

Manifesto for Running Projects with AI

1. AI as collaborator, not replacement
2. Embrace experimentation
3. Democratize project management
4. Prioritize knowledge flow
5. Maintain human judgment
6. Ensure transparency
7. Focus on value creation

Publications & Media

• Substack: Experiment in AI
• LinkedIn Series: Daily AI Project Tips
• Interviews: Project Chatter Podcast, MPA Podcast

Contact

To discuss AI implementation in your project environment, reach out via LinkedIn or Substack.