I help organizations improve performance through consulting, coaching, and training, powered by experiential learning and deep expertise in ITSM, DevOps, Generative AI, and PMO.
Gonzague Patinier
I help organizations improve performance through consulting, coaching, and training, powered by experiential learning and deep expertise in ITSM, DevOps, Generative AI, and PMO.
Gonzague Patinier
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Large Language Models are systems trained on massive datasets to understand context and generate human-like text.
Condensing lengthy documents, meeting notes, and emails.
Generating reports, communications, and project plans.
Analyzing historical data to flag potential project risks.
Automating scripts, formulas, and technical tasks.
Act as...
Set the
persona & context
Do what...
Define the
specific action
Show as...
Specify the
output style
"Act as a Senior PM (Role). Draft a risk mitigation plan for a delayed migration (Task). Present it as a Markdown table (Format)."
Use placeholders like [PROJECT_NAME] to make prompts reusable.
Ask AI to explain its reasoning step by step.
Break complex tasks into multiple prompt steps.
Key players in the AI space.
The versatile pioneer.
Focused on safety and large context.
Deep integration with workspace tools.
High efficiency for specific tasks.
Confidently presenting false or made-up information as fact.
Reflecting stereotypes and skewing results based on training data.
Limited context window leads to forgetting earlier details in long chats.
Predicting the next word based on patterns, not logic or reasoning.
Smart automation and content generation for boards.
Instant insights from your project documents.
Rapid visual creation for presentations and assets.
Automated meeting transcription and summaries.
Microsoft workflow automation.
Open-source workflow automation.
Automation and integration tool.
AI automation framework.
AI collaboration workspace.
AI-powered coding assistant.
Forecasting delays before they happen.
Turning messy notes into clean action items.
Q&A across your entire project documentation.
Auto-assigning tasks based on team load.
Identify and document risks with basic details (description, likelihood, impact, mitigation).
Assign ownership and save in a shared tool/document.
AI analyzes the registry and provides feedback.
Suggests additional risks, updates scores, and improves mitigation plans.
PM reviews and validates the registry.
Prioritizes risks based on likelihood, impact, and AI/team insights. Finalizes and shares with stakeholders for monitoring.
"Efficiency boost: 80%. Strategic accuracy: 100%."
Critical Security Rules:
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Step 0: Start a new chat
Step 1: Select Model
Step 2: Type Prompt
Step 3: Send to AI
We will be using this environment for our interactive exercises.
Practical Application of GenAI for PMs
Applying GenAI tools & workflows
GenAI Overview for PMs
GenAI concepts, tools & use-cases
Prompt Engineering for PMs
Interacting with LLMs effectively
PMI-CPMAI™ Introduction
AI PM & CPMAI™ methodology
Data Landscape of GenAI for PMs
Data, governance, ethics & compliance
AI in Agile Delivery
Using AI to enhance agile teams