I’m excited to share that my latest Pluralsight course, Applying GenAI to Planning and Requirements, is now live!
Generative AI is changing how project managers, business analysts, product owners, developers, and other technology professionals approach project planning and requirements gathering. Teams can now use GenAI to organize scattered information, accelerate documentation, identify missing details, and create stronger project artifacts.
However, generating content is only part of the process. Teams also need to validate the output, maintain traceability, involve the right stakeholders, and apply human judgment before AI-generated artifacts are used to guide development.
In this intermediate-level course, I focus on practical and responsible ways to apply GenAI across project planning, requirements gathering, documentation, validation, and governance. The course is approximately 75 minutes and is part of Pluralsight’s Generative AI Across the Software Development Lifecycle learning path.
What You’ll Learn
Modern project teams are expected to move quickly while still producing clear plans, accurate requirements, and documentation that stakeholders can trust.
This course explores how GenAI can help teams meet those expectations without removing people from the decision-making process.
Throughout the course, you’ll learn how to:
- Generate initial project charters and define project scope
- Identify assumptions, constraints, dependencies, and scope boundaries
- Support Agile planning, backlog refinement, estimation, and release planning
- Create risk registers and develop potential mitigation strategies
- Transform meeting notes, interviews, emails, and informal briefs into structured requirements
- Generate user stories, acceptance criteria, and definitions of done
- Identify missing non-functional requirements related to security, performance, accessibility, and compliance
- Detect gaps, ambiguities, and contradictions in requirements
- Generate clarifying questions for stakeholder review
- Establish human review and stakeholder sign-off workflows
- Maintain traceability between requirements, backlog items, testing, and supporting evidence
- Apply governance practices to AI-generated project artifacts
The course is intentionally tool-agnostic, with an emphasis on concepts and transferable practices that can be applied across different GenAI platforms and tools.
Applying GenAI to Project Planning, Scoping, and Risk Management
The first module explores how GenAI can support early project planning activities.
I demonstrate how to use GenAI to create an initial project charter, establish scope boundaries, document assumptions and constraints, and support Agile planning activities.
The module also covers how GenAI can assist with backlog refinement, effort estimation, release planning, risk identification, and mitigation planning.
For example, GenAI can help a project team identify common risks, organize them into a risk register, and propose possible contingency approaches. This can give the team a stronger starting point for planning and stakeholder discussions.
Just as importantly, I discuss the limitations of AI-generated planning artifacts.
GenAI may not understand internal politics, team dynamics, organizational history, available resources, unstated constraints, or business context that was not included in the prompt. Its output may sound complete while still missing important details.
Human judgment remains essential.
Accelerating Requirements Gathering and Documentation
The second module focuses on using GenAI to improve requirements gathering and documentation.
Requirements are often distributed across stakeholder conversations, meeting transcripts, emails, notes, whiteboards, documents, research findings, and informal requests. Important decisions may also exist only as verbal agreements or undocumented assumptions.
GenAI can help organize these inputs and transform them into structured artifacts that a project team can review and refine.
In this section, I show how GenAI can assist with:
- Requirements workshops
- Stakeholder discussion prompts
- Meeting summaries and action items
- Structured requirements documentation
- User stories and acceptance criteria
- Non-functional requirements
- Definitions of done
- Gap and ambiguity detection
- Clarifying questions
- Audience-adapted requirements documentation
The goal is not to have AI make final product or project decisions.
The goal is to help teams build a stronger starting point, organize information faster, ask better questions, and spend more time validating requirements with stakeholders.
Hands-On Demos with GitHub Copilot App
One of the highlights of the course is the set of practical demos.
I used GitHub Copilot App, OpenAI’s Codex, and GitHub Projects througout the demos so that you have an example with real tools you can start using today. In one of the demos GitHub Copilot App was used to move from unstructured project inputs to usable planning and requirements artifacts in GitHub Project. I show learners how GenAI can move beyond producing isolated text and become part of a real project workflow.
Across the demos, I show how to use GitHub Copilot to:
