Chapter 24 Exercises: Project Planning and Task Management

These exercises build practical AI-assisted project planning skills. Complete them in order — each builds on the previous one. All exercises assume access to any capable AI assistant.

Foundation Exercises (Exercises 1-5)

Exercise 1: The Scoping Interrogation

Objective: Practice using AI to surface hidden complexity in a project concept.

Setup: Choose a project you're either planning now or have recently completed. Write a 3-5 sentence description of the project as you'd describe it to a colleague.

Task: 1. Run the hidden complexity identification prompt from Section 24.2 with your project description. 2. Review the output. Which items are genuinely applicable to your project? Mark each as: Relevant / Not relevant / Already addressed. 3. For the relevant items, write one sentence about what action you'd take to address each one before the project starts. 4. Write one paragraph describing what the AI missed — hidden complexity specific to your context that the AI couldn't have known.

Reflection prompt: What does the gap between the AI's output and what you added manually tell you about the value of domain expertise in scoping?

Exercise 2: WBS Generation and Gap Analysis

Objective: Build and refine a work breakdown structure using AI, then identify what the AI missed.

Setup: Use the same project from Exercise 1, or choose a new one.

Task: 1. Run the WBS generation prompt from Section 24.3. Provide as much context as you can about the project. 2. Read the entire output carefully. Identify: - At least 3 tasks that are too vague and need further breakdown - At least 3 tasks that are missing entirely from the WBS - At least 2 tasks that probably aren't needed for your specific situation 3. Edit the WBS manually to address items 2a, 2b, and 2c. 4. Run the "What am I missing?" prompt on your edited WBS. 5. Add any new items the second prompt surfaces that you agree with.

Deliverable: A fully edited WBS with at least 3 levels of detail, annotated with your changes and reasoning.

Exercise 3: Pre-Mortem Workshop

Objective: Conduct a full pre-mortem analysis on a real project.

Setup: Use a current or upcoming project with at least 4 weeks of remaining duration.

Task: 1. Run the pre-mortem prompt from Section 24.4. Be specific about your project context. 2. Review the 8-10 failure stories generated. Select the 3 you think are most plausible for your specific situation. 3. For each selected failure story, write: - Why you find this scenario plausible (what in your project makes this likely) - The specific early warning sign you'd watch for - One concrete action you'll take in the next two weeks to reduce this risk 4. Identify one failure mode that is specific to your organization or context that the AI's pre-mortem missed.

Reflection prompt: Would you be comfortable sharing this pre-mortem output with your project sponsors? Why or why not? What does your answer reveal about stakeholder communication norms?

Exercise 4: Risk Register Build

Objective: Create a complete risk register using AI, then validate it with human judgment.

Task: 1. Run the risk brainstorming prompt from Section 24.4 for a project of your choice. 2. Review the output risk register. For each risk, make one of three decisions: - Accept as-is - Modify (refine the description, adjust likelihood/impact) - Reject (not applicable to your project) 3. Add at least 5 risks that the AI didn't generate but you know are relevant based on your organizational context. 4. Run the risk-impact matrix prompt to prioritize the resulting risk register. 5. Select the top 3 risks and write a full mitigation plan for each (not just a brief note — a real plan with actions, owner, timeline, and early warning indicators).

Deliverable: A completed risk register with at least 15 items, including your manual additions, prioritized, with full mitigation plans for the top 3.

Exercise 5: Stakeholder Communication Set

Objective: Practice adapting project communication for different audiences.

Setup: Take a project status (real or hypothetical) with mixed news — some things going well, one thing behind schedule, one decision needed.

Task: 1. Write the "raw" status update as you'd naturally write it for your team — unfiltered, with all the detail you'd include internally. 2. Run the audience adaptation prompt from Section 24.6 to generate versions for: executive sponsor, external client (if applicable), and dependent team. 3. Review all three adapted versions. For each one, answer: - Does this accurately represent the situation? - Is anything misleading or over-optimistic? - What would you change to make it more authentic? 4. Finalize and polish all three versions.

Reflection prompt: Where did the AI produce content you wouldn't actually send? What does that reveal about the difference between technically accurate and genuinely appropriate communication?

Intermediate Exercises (Exercises 6-10)

Exercise 6: Full Timeline with Dependency Mapping

Objective: Build a complete timeline from a WBS, including critical path identification.

Task: 1. Take the WBS you built in Exercise 2 (or create a new one for a different project). 2. Run the WBS-to-timeline prompt from Section 24.5. Provide your team capacity information. 3. Run the dependency mapping prompt. 4. Run the critical path identification prompt. 5. Manually review the critical path. Do you agree with it? What has the AI missed about your actual project dependencies? 6. Add at least 2 buffer points to the timeline based on the buffer planning prompt. Justify each buffer placement in one sentence.

Deliverable: A complete project timeline (table or outline format) with critical path identified, dependencies documented, and buffer placements explained.

Exercise 7: Sprint Planning Session

Objective: Run a complete AI-assisted sprint planning session.

Task: 1. Create or use an existing backlog of 15-20 items for a real or realistic project. 2. Run the sprint planning prompt from Section 24.7. Provide your team's actual or estimated capacity. 3. Review the recommended sprint plan. Answer: - Does the sprint goal make sense? Refine the language. - Are there items the AI included that you wouldn't? Why? - Are there items the AI excluded that should be in? 4. For the 3 largest or most complex items, run the user story generation prompt. 5. Review the acceptance criteria generated. Add, remove, or modify criteria to match your actual definition of done.

Deliverable: A finalized sprint plan with user stories and acceptance criteria for the 3 key items.

Exercise 8: The Effort Estimation Calibration Exercise

Objective: Understand the gap between AI duration estimates and your team's actual velocity.

Task: 1. Take a completed project from the past 3-6 months. List 10 tasks with their actual durations. 2. Without sharing the actual durations, run the AI timeline prompt for these tasks. 3. Compare AI estimates to actual durations. Calculate: - The average ratio (actual / AI estimate) - The range (what's the most over-estimated task? Most under-estimated?) - Any patterns (does AI consistently underestimate certain types of work?) 4. Write a "calibration note" you could add to future planning prompts based on what you learned.

Reflection prompt: How should the findings of this exercise change how you present AI-generated timelines to stakeholders?

Exercise 9: The Project Brief-to-Plan Pipeline

Objective: Build a complete project plan from a one-paragraph brief using a chained prompt sequence.

Task: Using a project brief of 100-200 words, chain together the following prompts in sequence: 1. Hidden complexity identification 2. Requirements elicitation questions (adapt 5 questions into assumptions you'll make) 3. WBS generation 4. "What am I missing?" WBS review 5. Risk brainstorming 6. Pre-mortem (5 failure stories) 7. Timeline generation 8. Status update template for this project

Deliverable: A complete project planning package (all 8 outputs) for your brief, with a cover page noting what you manually changed at each step and why.

Exercise 10: Agile Retrospective Analysis

Objective: Use AI to get more value from retrospective data.

Setup: Take notes from a real retrospective (or write realistic retrospective notes for a project you know well). The notes should include at least 10 "what could have gone better" items.

Task: 1. Run the retrospective prompt from Section 24.7 with your notes. 2. Review the pattern analysis. Do you agree with the groupings? Revise if needed. 3. For the 3 suggested improvements, assess each one: - Is it specific enough to implement? If not, make it more specific. - Does it address the root cause, or just the symptom? - Who would own this change? 4. Compare the AI-suggested improvements to what your team actually decided in the retrospective (or what you would have decided). Note the differences.

Reflection prompt: What's the risk of using AI to analyze retrospective data rather than having the team discuss it together? When is AI retrospective analysis useful vs. potentially counterproductive?

Advanced Exercises (Exercises 11-15)

Exercise 11: The Red Team Your Plan Challenge

Objective: Experience the full impact of AI adversarial analysis on a real project plan.

Task: 1. Take a project plan you're proud of — something you've spent time on and believe is solid. 2. Run the red team prompt from Section 24.4 on this plan. 3. Read the output without defensiveness. For each adversarial point, respond: - "This is a real issue and here's how I'll address it": [specific response] - "This is a real issue but it's acceptable risk because": [reasoning] - "This doesn't apply to my project because": [specific reason] 4. Update your project plan based on the responses in 3a. 5. Run the red team prompt a second time on your updated plan. Note what has changed.

Reflection prompt: How did it feel to have your plan criticized? Did the adversarial framing produce more useful output than a straightforward "identify risks" prompt? Why?

Exercise 12: Multi-Stakeholder Communication Campaign

Objective: Build a complete communication plan with AI assistance.

Task: 1. For a real or realistic project, identify 5 distinct stakeholder groups with different information needs. 2. For each group, define: what they care about, how often they need updates, and what format works best. 3. Use AI to generate a communication template for each stakeholder group. 4. Generate a sample update for each template based on a realistic project status. 5. Review all 5 communications for consistency — does each one present the same facts accurately even while emphasizing different aspects?

Deliverable: A complete stakeholder communication plan with 5 templates and one sample update per template.

Exercise 13: Project Failure Post-Mortem

Objective: Use AI to extract maximum learning from a project that didn't go as planned.

Setup: Identify a past project with significant problems — something that was late, over budget, or that had quality or stakeholder satisfaction issues.

Task: 1. Write a detailed description of the project, its problems, and what you know about the causes. 2. Ask AI to help you build a structured post-mortem analysis: - Root cause analysis for the top 3 failures (use "5 Whys" technique) - Timeline of how each failure developed from first signs to impact - What interventions at each stage could have changed the outcome - Specific process changes for future similar projects 3. Compare the AI's root cause analysis to your own understanding. What did it surface that you hadn't fully articulated? 4. Write 5 specific "lessons learned" statements that will actually influence how you plan the next similar project.

Exercise 14: Building Your Personal Planning System

Objective: Create a reusable AI-assisted planning system customized for your work.

Task: 1. Identify the 3 types of projects you run most frequently (e.g., client engagements, product launches, internal process improvements). 2. For each project type: - Write a customized WBS template that captures the standard work for this type - Write a customized risk brainstorming prompt that includes risk categories specific to this type - Write a stakeholder communication template appropriate for this type's typical audiences 3. Test each template on a real or realistic example. 4. Document your "planning playbook" — a single reference document that captures your templates and guidance for when to use each.

Deliverable: A personal planning playbook with templates for 3 project types.

Exercise 15: The Capacity Planning Challenge

Objective: Confront AI's limitations in effort estimation by building a capacity-aware timeline.

Task: 1. List your team members with their current allocation to other projects, planned time off, and any known constraints for the next 3 months. 2. Take a project plan and ask AI to create a timeline without sharing this capacity information. Note the result. 3. Now provide the full capacity context and ask AI to create a revised timeline. 4. Compare the two timelines. What changed? 5. Now validate the capacity-aware timeline against your team's actual velocity data. What does AI still get wrong? 6. Write a "capacity briefing template" — a structured prompt addition you'll always include when asking AI for timeline estimates.

Reflection prompt: At what point does it become more efficient to use a dedicated resource management tool rather than trying to get AI to handle capacity planning?

Capstone Exercise

Exercise 16: The 90-Minute Plan

Objective: Run a complete AI-assisted project planning session under time pressure.

Constraint: You have exactly 90 minutes.

Task: Use AI to produce a complete project plan for a real project you're planning. The plan must include: - Project scope statement - Work breakdown structure (3 levels) - Risk register (10+ items, prioritized) - Timeline (milestone-level) - Stakeholder communication plan

Rules: - You may use AI for all generation tasks - You must review and edit every output — nothing goes into the final plan unreviewed - Track your time: how much on prompting vs. reviewing vs. editing? - At the end, rate the quality of the plan on a scale of 1-10 compared to plans you'd produce without AI assistance

Reflection: After the 90 minutes, write a half-page reflection on what AI made faster, what required the most human judgment, and what you'd do differently next time.