Prompt Library

ChatGPT Prompts for Project Managers

30 copy-paste prompts

Thirty copy-paste prompts that help you plan schedules, lock scope, surface risks, write status reports, align stakeholders, and run sharp retrospectives — without the blank-page slog.

In short: This page contains 30 copy-paste ready prompts, organized into 6 categories with a description and pro tip for each. The first 5 prompts are free instantly, no signup needed. Drafted with AI writing assistance and checked against our editorial policy.

Louis Corneloup
By Louis Corneloup · Founder, Techpresso
Last updated ·Drafted with AI assistance (how we make prompts)

Planning & Scheduling

5 prompts

Build a Work Breakdown Structure

1/30

✨ What it does

ChatGPT decomposes [PROJECT] into a work breakdown with 4-6 workstreams, role assignments from [LIST ROLES], effort estimates, and dependencies before [TIMELINE]. You check the estimates against [NUMBER] people, then drop the structure into your plan.

<context> You are a senior project manager planning [PROJECT]. The project must deliver by [TIMELINE]. The core deliverables are: [LIST DELIVERABLES]. The team has [NUMBER] people across these roles: [LIST ROLES]. </context> <task> 1. Decompose [PROJECT] into a work breakdown structure with 4-6 top-level workstreams. 2. Under each workstream, list the concrete tasks needed to complete it. 3. For every task, estimate effort in person-days and name the role responsible. 4. Flag any task that depends on another task finishing first. 5. Present the WBS as a nested numbered outline, then summarize total effort per workstream. </task>

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Pro tip: Paste your existing task list into the prompt first and ask ChatGPT to find gaps and missing tasks before it estimates effort.

Draft a Project Schedule with Milestones

2/30

✨ What it does

ChatGPT sequences [PASTE TASKS WITH DURATIONS] into a milestone schedule for [PROJECT] by [TIMELINE], with a critical path and buffers around [BLACKOUT DATES]. You lock the dates you trust, then share the timeline with the team.

<context> You are scheduling [PROJECT] for delivery by [TIMELINE]. Here are the tasks and their estimated durations: [PASTE TASKS WITH DURATIONS]. Known dependencies: [LIST DEPENDENCIES]. The team is unavailable on: [BLACKOUT DATES]. </context> <task> 1. Sequence the tasks into a logical timeline working backward from [TIMELINE]. 2. Group the work into 4-6 milestones with target dates. 3. Identify the critical path and label which tasks sit on it. 4. Add a 15% schedule buffer and show where you placed it and why. 5. Output a week-by-week schedule table: week, tasks, owner, milestone. </task>

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Pro tip: Ask ChatGPT to regenerate the schedule under an aggressive scenario (timeline cut 20%) so you can see what breaks first.

Estimate Effort with Three-Point Estimation

3/30

✨ What it does

ChatGPT gives a three-point estimate for each task on [PROJECT] from [PASTE TASK LIST] and flags the riskiest ranges. You compare those numbers with [PAST EXAMPLES OR 'none'], then put the totals in the plan.

<context> You are estimating effort for [PROJECT]. Here are the tasks: [PASTE TASK LIST]. The team has delivered similar work before, with these reference points: [PAST EXAMPLES OR 'none']. </context> <task> 1. For each task, give a three-point estimate: optimistic, most likely, and pessimistic (in person-days). 2. Compute the PERT expected value for each task using (O + 4M + P) / 6. 3. Sum the expected values and the standard deviation across all tasks. 4. State the confidence range (expected value plus or minus one standard deviation). 5. Call out the three tasks with the widest spread and ask me clarifying questions to tighten them. </task>

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Pro tip: When ChatGPT asks its clarifying questions, answer them and have it recompute — the second pass is far more accurate.

Allocate Resources Across Workstreams

4/30

✨ What it does

ChatGPT assigns people from [LIST PEOPLE AND HOURS] across [LIST WORKSTREAMS] on [PROJECT] and flags who is over- or under-loaded before [TIMELINE]. You adjust for [NOTE CONSTRAINTS], then tell people their assignments.

<context> You are allocating people on [PROJECT] delivering by [TIMELINE]. Team members and their weekly capacity: [LIST PEOPLE AND HOURS]. Workstreams and their estimated effort: [LIST WORKSTREAMS]. Some people are only skilled for certain workstreams: [NOTE CONSTRAINTS]. </context> <task> 1. Assign people to workstreams respecting skill constraints and weekly capacity. 2. Flag any workstream that is under-resourced for the [TIMELINE]. 3. Identify anyone over-allocated beyond 100% in any week. 4. Propose two reallocation options to fix the worst bottleneck. 5. Output an allocation table: person, workstream, % time, weeks engaged. </task>

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Pro tip: Feed ChatGPT the raw export from your resourcing tool and let it spot conflicts you would miss scanning manually.

Create a Project Kickoff Agenda

5/30

✨ What it does

ChatGPT builds a timeboxed kickoff agenda for [PROJECT] with [STAKEHOLDER] that fits [DURATION], covering goals, roles, and decisions to capture. You add [ONE-LINE GOAL], then run the meeting from that agenda.

<context> You are running the kickoff for [PROJECT] with [STAKEHOLDER] and the delivery team. Target delivery is [TIMELINE]. Project goal: [ONE-LINE GOAL]. Meeting length: [DURATION]. </context> <task> 1. Build a timeboxed kickoff agenda that fits [DURATION]. 2. Include sections for goals, scope boundaries, roles, timeline, risks, and ways of working. 3. For each section, write the one outcome the group must leave with. 4. Add three discussion questions designed to surface hidden assumptions. 5. End with a clear list of decisions to capture and owners to assign. </task>

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Pro tip: Add the personalities or known tensions on the team and ask ChatGPT to suggest how to facilitate the tricky moments.

Scope & Requirements

5 prompts

Write a Project Scope Statement

6/30

✨ What it does

ChatGPT writes a scope statement for [PROJECT] covering [OBJECTIVE], in-scope items from [LIST], out-of-scope lines, and assumptions before [TIMELINE]. You settle [LIST OR 'unclear'] with [STAKEHOLDER], then share the statement so scope stays tight.

<context> You are documenting scope for [PROJECT], a project sponsored by [STAKEHOLDER] for delivery by [TIMELINE]. Business objective: [OBJECTIVE]. Known deliverables: [LIST]. Things explicitly out of scope so far: [LIST OR 'unclear']. </context> <task> 1. Write a scope statement with: objective, in-scope deliverables, out-of-scope items, assumptions, and constraints. 2. Make every in-scope item specific and verifiable (no vague verbs like 'support' or 'improve'). 3. Propose three additional out-of-scope items commonly forgotten on projects like this. 4. List the assumptions that, if wrong, would blow up the scope. 5. Keep it under 400 words and format with clear headers. </task>

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Pro tip: Have ChatGPT rewrite each in-scope line as an acceptance criterion you can test at sign-off.

Turn Stakeholder Requests into Requirements

7/30

✨ What it does

ChatGPT rewrites [PASTE REQUESTS] from [STAKEHOLDER] into testable requirements for [PROJECT], classified and prioritized, with open questions flagged. You answer those questions, then put the cleaned list in the spec.

<context> You are translating raw requests from [STAKEHOLDER] into requirements for [PROJECT]. Here are the requests, verbatim: [PASTE REQUESTS]. </context> <task> 1. Rewrite each request as a clear, testable requirement using 'The system shall...' or a user story format. 2. Classify each as functional or non-functional. 3. Assign a MoSCoW priority (Must, Should, Could, Won't) and justify it in one line. 4. Flag any request that is ambiguous, conflicting, or untestable, and write the clarifying question I should ask. 5. Output a requirements table: ID, requirement, type, priority, open question. </task>

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Pro tip: Paste meeting transcripts directly — ChatGPT extracts requirements from rambling discussion better than from cleaned-up notes.

Build a Requirements Traceability Matrix

8/30

✨ What it does

ChatGPT maps each item in [PASTE REQUIREMENTS] to deliverables and tests for [PROJECT], and flags orphans or gold-plating. You add [PASTE DELIVERABLES AND TESTS OR 'tests not written yet'], then close the gaps before build starts.

<context> You are setting up traceability for [PROJECT]. Here are the requirements: [PASTE REQUIREMENTS]. Here are the planned deliverables and test cases: [PASTE DELIVERABLES AND TESTS OR 'tests not written yet']. </context> <task> 1. Map each requirement to the deliverable(s) that satisfy it. 2. Map each requirement to the test case(s) that verify it. 3. Flag any requirement with no deliverable (orphaned) or no test (unverified). 4. Flag any deliverable that maps to no requirement (gold-plating). 5. Output the matrix as a table: requirement ID, deliverable, test case, status. </task>

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Pro tip: Re-run this monthly with your updated requirement list so ChatGPT catches scope creep as it appears.

Assess a Change Request Impact

9/30

✨ What it does

ChatGPT analyzes [DESCRIBE CHANGE] on [PROJECT] against [SUMMARIZE BASELINE] and [STATUS], with options and a recommendation before [TIMELINE]. You choose the option, then send the write-up to the people who must approve.

<context> You are evaluating a change request on [PROJECT] due [TIMELINE]. The change: [DESCRIBE CHANGE]. Current scope baseline: [SUMMARIZE BASELINE]. Current schedule and budget status: [STATUS]. </context> <task> 1. Summarize what the change actually asks for in one paragraph. 2. Assess impact on scope, schedule, budget, and risk, with a magnitude (low / medium / high) for each. 3. List the tasks that would need to be added, changed, or removed. 4. Give two options: accept with adjustments, or defer, each with consequences. 5. Draft a recommendation I can take to [STAKEHOLDER] in 100 words. </task>

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Pro tip: Ask ChatGPT to play the skeptical sponsor and challenge your recommendation before you present it.

Define Acceptance Criteria for a Deliverable

10/30

✨ What it does

ChatGPT writes Given/When/Then acceptance criteria for [DESCRIBE DELIVERABLE] on [PROJECT], including edge cases and sign-off evidence for [STAKEHOLDER]. You fill [PASTE OR 'unknown'], then use the criteria as the done check.

<context> You are defining done for a deliverable on [PROJECT]. Deliverable: [DESCRIBE DELIVERABLE]. Who signs off: [STAKEHOLDER]. What good looks like, in their words: [PASTE OR 'unknown']. </context> <task> 1. Write acceptance criteria in Given/When/Then format covering the main scenarios. 2. Add criteria for edge cases and failure modes, not just the happy path. 3. Note any criterion that cannot be objectively verified and propose how to make it measurable. 4. List what evidence [STAKEHOLDER] will need to see to sign off. 5. Keep each criterion to one sentence and number them. </task>

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Pro tip: Tell ChatGPT the deliverable type (report, feature, design) so it tailors the edge cases to that medium.

Risk Management

5 prompts

Run a Project Risk Identification Workshop

11/30

✨ What it does

ChatGPT brainstorms 12-15 risks for [PROJECT] across scope, schedule, budget, resources, technical, and external, given [CONSTRAINTS] and [DEPENDENCIES]. You drop the ones that do not apply, then take the rest into the register.

<context> You are identifying risks for [PROJECT] delivering by [TIMELINE]. Project summary: [SUMMARY]. Team size: [NUMBER]. Known constraints: [CONSTRAINTS]. Key dependencies: [DEPENDENCIES]. </context> <task> 1. Brainstorm 12-15 candidate risks across categories: scope, schedule, budget, resources, technical, external, and stakeholder. 2. Phrase each risk as 'cause leads to event leads to impact', not a vague worry. 3. Group near-duplicate risks and keep the clearest wording. 4. Highlight the three risks most specific to this project rather than generic ones. 5. Output a numbered risk list grouped by category. </task>

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Pro tip: After the list, ask ChatGPT for the risks teams typically forget on projects like yours — it surfaces blind spots.

Build a Risk Register with Scoring

12/30

✨ What it does

ChatGPT scores each item in [PASTE RISK LIST] for [PROJECT] on probability and impact, ranks them, and suggests a response and owner. You challenge the scores you disagree with, then assign those owners.

<context> You are scoring risks for [PROJECT]. Here are the identified risks: [PASTE RISK LIST]. Use a 1-5 scale for both probability and impact. </context> <task> 1. For each risk, assign a probability (1-5) and impact (1-5) with a one-line rationale. 2. Compute the risk score (probability x impact) and rank all risks. 3. Assign each risk a response strategy: avoid, mitigate, transfer, or accept. 4. Name a likely owner role for each risk. 5. Output a risk register table: risk, probability, impact, score, strategy, owner, sorted highest score first. </task>

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Pro tip: Keep the register in a doc and paste it back next month asking ChatGPT to re-score based on what has changed.

Write Mitigation and Contingency Plans

13/30

✨ What it does

ChatGPT writes a mitigation plan and a contingency plan for each of [PASTE TOP 5 RISKS WITH SCORES] on [PROJECT], with triggers and cost notes before [TIMELINE]. You assign the actions, then watch those triggers.

<context> You are planning responses for the top risks on [PROJECT] due [TIMELINE]. Top risks: [PASTE TOP 5 RISKS WITH SCORES]. </context> <task> 1. For each risk, write a mitigation plan (actions to reduce probability or impact before it happens). 2. Write a contingency plan (what we do if it happens anyway). 3. Define the trigger or early-warning sign that tells us to activate the contingency. 4. Estimate the cost or effort of each mitigation so I can judge if it is worth it. 5. Output per risk: mitigation, contingency, trigger, cost. </task>

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Pro tip: Ask ChatGPT to phrase each trigger as a measurable threshold so you know exactly when to act, not just 'when things look bad'.

Pre-Mortem a Project Before Launch

14/30

✨ What it does

ChatGPT writes 10 past-tense stories of how [PROJECT] already failed against [GOAL] by [TIMELINE], plus the preventive moves that would have stopped each one. You pick the few you will act on now, then add them to the plan.

<context> You are running a pre-mortem for [PROJECT] before it starts. Goal: [GOAL]. Timeline: [TIMELINE]. Imagine it is delivery day and the project has failed badly. </context> <task> 1. Generate 10 plausible stories for how [PROJECT] failed, written in past tense as if it already happened. 2. For each failure story, trace back to the root cause and the earliest moment it could have been caught. 3. Identify the two or three failure modes that show up across multiple stories. 4. Recommend the single highest-leverage action to prevent each recurring mode. 5. Output as: failure story, root cause, earliest signal, prevention. </task>

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Pro tip: Run the pre-mortem with ChatGPT solo first, then bring its failure stories to your team as discussion starters.

Analyze a Dependency and Blocker Map

15/30

✨ What it does

ChatGPT maps what blocks what on [PROJECT] from [LIST] and [LIST WITH OWNERS], and ranks which dependencies to manage before [TIMELINE]. You update [LIST OR 'none yet'], then chase the ones that can slip the date.

<context> You are mapping dependencies for [PROJECT] due [TIMELINE]. Internal dependencies between tasks: [LIST]. External dependencies on other teams or vendors: [LIST WITH OWNERS]. Current blockers: [LIST OR 'none yet']. </context> <task> 1. Build a dependency map showing what blocks what. 2. Identify the dependencies on the critical path that would delay [TIMELINE] if late. 3. Flag every external dependency where we do not control the timeline. 4. For each high-risk dependency, suggest a fallback or a way to de-risk it now. 5. Output a prioritized list of dependencies to actively manage this week. </task>

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Pro tip: Ask ChatGPT to draft the chase email to each external dependency owner so you can follow up the same day.

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Status Reporting

5 prompts

Write an Executive Status Summary

16/30

✨ What it does

ChatGPT turns [PASTE NOTES ON PROGRESS, BLOCKERS, DECISIONS] into a short status for [STAKEHOLDER] on [PROJECT], opening with on track, at risk, or off track. You check the facts, then send it before their five minutes are gone.

<context> You are writing a weekly status update on [PROJECT] for [STAKEHOLDER], who has five minutes. Delivery target: [TIMELINE]. This week's raw notes: [PASTE NOTES ON PROGRESS, BLOCKERS, DECISIONS]. </context> <task> 1. Open with an overall status: on track, at risk, or off track, and one sentence of why. 2. Summarize progress this week in three bullets focused on outcomes, not activity. 3. List blockers and exactly what you need from [STAKEHOLDER] to clear them. 4. State what happens next week. 5. Keep the whole update under 150 words and lead with the status color. </task>

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Pro tip: Save your raw notes in the same chat all week, then ask for the summary on Friday — ChatGPT already has the context.

Generate a RAG Status Dashboard

17/30

✨ What it does

ChatGPT colors each workstream on [PROJECT] red, amber, or green from [PASTE WORKSTREAMS WITH NOTES], plus an honest overall call and recovery actions before [TIMELINE]. You correct any color that feels too kind, then put the table in the weekly update.

<context> You are building a status dashboard for [PROJECT] due [TIMELINE]. Workstreams and their current state: [PASTE WORKSTREAMS WITH NOTES]. Budget status: [STATUS]. Schedule status: [STATUS]. </context> <task> 1. Assign a RAG status (red / amber / green) to each workstream with a one-line reason. 2. Assign an overall project RAG that honestly reflects the worst material issue. 3. For every amber or red item, state the action and owner to move it toward green. 4. Show schedule and budget as separate RAG indicators. 5. Output a dashboard table: workstream, RAG, reason, action, owner. </task>

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Pro tip: Tell ChatGPT not to let the overall status be greener than the worst red item unless you explicitly justify it — it prevents watermelon reporting.

Explain a Schedule Slip to Leadership

18/30

✨ What it does

ChatGPT drafts a clear, non-defensive explanation of the slip on [PROJECT] from [TIMELINE] to [NEW DATE], covering [CAUSES] and [RECOVERY ACTIONS]. You edit the tone, then send it to leadership.

<context> You are reporting a delay on [PROJECT]. Original target: [TIMELINE]. New realistic target: [NEW DATE]. What caused the slip: [CAUSES]. What you are doing about it: [RECOVERY ACTIONS]. </context> <task> 1. Write a clear, non-defensive explanation of the slip and its root cause. 2. State the revised timeline and the confidence level behind it. 3. Describe the recovery plan and what it will and will not fix. 4. Be explicit about any decision or trade-off you need leadership to make. 5. Keep the tone accountable, not apologetic, and under 200 words. </task>

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Pro tip: Ask ChatGPT to anticipate the three hardest questions leadership will ask and draft your answers to each.

Summarize a Long Status Thread

19/30

✨ What it does

ChatGPT distills [PASTE THREAD] on [PROJECT] into current state, decisions with owners, and open actions. You assign missing due dates, then chase the follow-ups that still matter.

<context> You are catching up on [PROJECT]. Below is a long thread of updates, messages, and notes from the past two weeks: [PASTE THREAD]. </context> <task> 1. Summarize the current state of the project in one paragraph. 2. Extract all decisions that were made, with who made them. 3. Extract all open action items, with owner and due date if stated. 4. Flag any contradiction or unresolved disagreement in the thread. 5. List the three things I should follow up on first and why. </task>

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Pro tip: Works on Slack exports and email chains — paste the raw mess; ChatGPT is good at untangling who said what.

Draft a Monthly Steering Committee Report

20/30

✨ What it does

ChatGPT writes a monthly steering report for [PROJECT] sponsored by [STAKEHOLDER], covering milestones, budget, risks, and decisions from your [DATA] and [LIST]. You fill the real numbers against [TIMELINE], then tee up the asks in the meeting.

<context> You are preparing the monthly steering committee report for [PROJECT] sponsored by [STAKEHOLDER], due [TIMELINE]. Inputs: progress against milestones [DATA], budget vs plan [DATA], top risks [DATA], key decisions needed [LIST]. </context> <task> 1. Structure the report: executive summary, milestone progress, budget, risks, decisions needed, next month. 2. In the executive summary, lead with the one thing the committee must know. 3. Frame each 'decision needed' so the committee can decide in the meeting, with a recommended option. 4. Keep risk to the top three with current trend (improving / stable / worsening). 5. Output a polished, headed report under 600 words. </task>

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Pro tip: Reuse the same prompt monthly and paste last month's report so ChatGPT carries forward trends and open decisions.

Stakeholder Communication

5 prompts

Build a Stakeholder Map and Engagement Plan

21/30

✨ What it does

ChatGPT plots each person in [LIST NAMES, ROLES, INTERESTS, ATTITUDE] on a power/interest grid for [PROJECT] and recommends how often to engage them before [TIMELINE]. You adjust the placements, then set the cadence per person.

<context> You are mapping stakeholders for [PROJECT] due [TIMELINE]. Stakeholders and what you know about each: [LIST NAMES, ROLES, INTERESTS, ATTITUDE]. </context> <task> 1. Plot each stakeholder on a power/interest grid (high or low for each). 2. Recommend an engagement approach per quadrant: manage closely, keep satisfied, keep informed, monitor. 3. For each high-power stakeholder, note their likely concern and what would make them an advocate. 4. Flag any stakeholder whose attitude is unknown or hostile and propose a first move. 5. Output an engagement plan table: stakeholder, quadrant, approach, cadence, key message. </task>

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Pro tip: Keep stakeholder names anonymized as roles if pasting into ChatGPT, then map names back yourself.

Draft a Difficult Stakeholder Message

22/30

✨ What it does

ChatGPT drafts a hard-news message to [STAKEHOLDER] about [PROJECT] that states [DESCRIBE] plainly, with a second tone and likely [REACTION] already handled. You pick the tone that fits [CONTEXT], then send it toward [OUTCOME].

<context> You need to deliver hard news to [STAKEHOLDER] about [PROJECT]. The situation: [DESCRIBE]. Their likely reaction: [REACTION]. Relationship history: [CONTEXT]. Desired outcome of the message: [OUTCOME]. </context> <task> 1. Draft a message that states the news plainly in the first two sentences. 2. Give the context they need to understand it without burying the point. 3. Address their most likely objection before they raise it. 4. End with a clear, specific ask or next step toward [OUTCOME]. 5. Provide two tone variants: direct and more diplomatic. </task>

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Pro tip: Tell ChatGPT the channel (email, Slack, in-person script) — the right length and tone differ a lot by medium.

Tailor One Update for Three Audiences

23/30

✨ What it does

ChatGPT rewrites [PASTE FACTS] about [PROJECT] into three updates for executives, the delivery team, and [STAKEHOLDER] or clients, without changing the truth. You send each version to the right group, then keep one source of facts.

<context> You are communicating a [PROJECT] update. The core facts: [PASTE FACTS]. Audiences: executives, the delivery team, and [STAKEHOLDER] / clients. </context> <task> 1. Write three versions of the same update, one per audience. 2. For executives: outcomes, risks, and decisions only, under 100 words. 3. For the delivery team: specifics, dependencies, and what to do next. 4. For [STAKEHOLDER] / clients: benefits and reassurance, minimal jargon. 5. Keep the underlying facts identical across all three; only framing changes. </task>

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Pro tip: Ask ChatGPT to flag any place where the framing risks crossing into spin so you keep all three honest.

Prepare for a Stakeholder Negotiation

24/30

✨ What it does

ChatGPT preps your negotiation with [STAKEHOLDER] on [ISSUE] for [PROJECT], mapping interests behind [YOUR POSITION] and [THEIR POSITION], plus options and a fallback. You hold [CONSTRAINTS], then walk in with the options you can actually offer.

<context> You are negotiating with [STAKEHOLDER] on [PROJECT]. The point of tension: [ISSUE]. What you want: [YOUR POSITION]. What you think they want: [THEIR POSITION]. Constraints you cannot move: [CONSTRAINTS]. </context> <task> 1. Identify the underlying interests behind each stated position, for both sides. 2. Propose three options that could satisfy both sets of interests. 3. Define your BATNA and the walk-away point. 4. Anticipate their three strongest arguments and prepare a response to each. 5. Suggest an opening framing that lowers defensiveness. </task>

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Pro tip: Have ChatGPT role-play as the stakeholder afterward so you can rehearse the conversation before it happens for real.

Write Meeting Notes with Decisions and Actions

25/30

✨ What it does

ChatGPT turns [PASTE NOTES] from a [PROJECT] meeting with [STAKEHOLDER] into clean minutes with decisions, owners, and due dates. You fill any missing owners, then send the notes the same day.

<context> You are documenting a [PROJECT] meeting with [STAKEHOLDER] and the team. Here are my rough notes from the meeting: [PASTE NOTES]. </context> <task> 1. Write a clean summary of what was discussed, grouped by topic. 2. Extract every decision made into a clearly labeled Decisions section. 3. Extract every action item with owner and due date; mark any missing owner or date as TBD. 4. Note any topic raised but left unresolved, as Parking Lot items. 5. Keep it skimmable: short paragraphs, bold labels, no filler. </task>

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Pro tip: Dictate your notes into ChatGPT voice mode right after the meeting while it is fresh — then ask for the structured version.

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Retrospectives & Closeout

5 prompts

Facilitate a Sprint or Project Retrospective

26/30

✨ What it does

ChatGPT designs a timeboxed retrospective for [PROJECT] that fits [DURATION] and [MOOD], with a format and facilitation moves. You add [PASTE EVENTS], then run the session and capture the actions.

<context> You are designing a retrospective for [PROJECT] with the delivery team. Duration: [DURATION]. The team's mood: [MOOD]. Notable events this period: [PASTE EVENTS]. </context> <task> 1. Recommend a retro format that fits [DURATION] and the team's mood (e.g. Start/Stop/Continue, 4Ls, Sailboat). 2. Build a timeboxed agenda with each activity and its purpose. 3. Write the specific prompting questions for each section, tied to the notable events. 4. Include a technique to keep quieter team members contributing. 5. End with how to turn discussion into 2-3 committed action items. </task>

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Pro tip: Tell ChatGPT if the last retro produced no real change — it will design the session to break that pattern.

Synthesize Retrospective Feedback into Themes

27/30

✨ What it does

ChatGPT clusters [PASTE ALL FEEDBACK] from the [PROJECT] retro into named themes, splits systemic from one-off, and proposes actions. You keep a few actions the team can own, then put them on the board.

<context> You are analyzing raw retrospective input for [PROJECT]. Here is everything the team submitted: [PASTE ALL FEEDBACK]. </context> <task> 1. Cluster the feedback into themes and name each theme. 2. For each theme, count how many people raised it and quote one representative point. 3. Separate systemic issues (recurring, structural) from one-off complaints. 4. Identify the two themes with the highest impact-to-effort ratio to fix. 5. Draft a candidate action item for each high-priority theme. </task>

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Pro tip: Paste feedback anonymously and ask ChatGPT not to attribute quotes so the team stays comfortable being honest next time.

Write a Lessons-Learned Document

28/30

✨ What it does

ChatGPT writes a lessons-learned document for [PROJECT] from [OUTCOME] and your [LIST] of what went well, badly, and surprised you. You keep the transferable ones, then share the doc with the next team.

<context> You are capturing lessons learned at the end of [PROJECT]. Outcome vs goal: [OUTCOME]. What went well: [LIST]. What went badly: [LIST]. Key surprises: [LIST]. </context> <task> 1. Organize lessons into: what to repeat, what to change, what to stop. 2. For each lesson, write it as a specific, transferable recommendation, not a vague platitude. 3. Tie each lesson to the evidence or event that produced it. 4. Note which lessons are project-specific vs applicable to all future projects. 5. End with the top three lessons the next project manager must read first. </task>

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Pro tip: Ask ChatGPT to rewrite any lesson that sounds generic ('communicate better') into a concrete, testable change.

Build a Project Closeout Checklist

29/30

✨ What it does

ChatGPT builds a closeout checklist for [PROJECT] covering sign-off, finance, contracts, access, and docs for [STAKEHOLDER]. You tick each row against [LIST] and [LIST OR 'none'], then chase anything still open.

<context> You are closing out [PROJECT] delivered for [STAKEHOLDER]. Deliverables: [LIST]. Contracts or vendors involved: [LIST OR 'none']. Systems and access created: [LIST]. </context> <task> 1. Generate a closeout checklist across: deliverable sign-off, finance, contracts, access/decommissioning, documentation, and team release. 2. For each item, name who must confirm it is done. 3. Flag anything that, if missed, creates legal, security, or financial exposure. 4. Include a formal acceptance step with [STAKEHOLDER]. 5. Output as a checklist grouped by category with owner and a done column. </task>

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Pro tip: Ask ChatGPT for the closeout items teams most often forget — orphaned access and unbilled work top the list.

Draft a Project Closure Report

30/30

✨ What it does

ChatGPT drafts a closure report for [PROJECT] using [RESULTS VS OBJECTIVES], [ACTUAL VS PLAN], and [PASTE] lessons for [STAKEHOLDER]. You fill the last numbers against [TIMELINE], then file the report.

<context> You are writing the final closure report for [PROJECT], sponsored by [STAKEHOLDER], delivered against [TIMELINE]. Final results: [RESULTS VS OBJECTIVES]. Budget outcome: [ACTUAL VS PLAN]. Major lessons: [PASTE]. </context> <task> 1. Structure the report: objectives vs outcomes, schedule performance, budget performance, scope changes, key lessons, and handover status. 2. State plainly whether the project met its objectives, with evidence. 3. Summarize variance in schedule and budget and explain the main drivers. 4. List what has been handed over to operations and what remains open. 5. Output a professional closure report under 700 words with clear headers. </task>

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Pro tip: Give ChatGPT your original project charter so it can measure the closure honestly against what you promised at the start.

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Frequently Asked Questions

Copy a prompt, replace the bracketed placeholders like [PROJECT], [TIMELINE], and [STAKEHOLDER] with your real details, and paste it into ChatGPT. The more specific your inputs — actual task lists, real dates, real constraints — the more useful and accurate the output. Treat the first response as a draft and refine it with follow-up questions.
For planning, scheduling, and analytical tasks like risk scoring or estimation, a reasoning-capable model gives more reliable structured output. For quick status summaries and rewriting notes, a faster general model is fine. Whichever you use, always verify dates, effort estimates, and dependencies yourself — ChatGPT can produce confident but wrong numbers.
No. ChatGPT is excellent for drafting, summarizing, brainstorming risks, and structuring communication, but it has no live view of your project and does not track state between sessions. Use it to generate the content — schedules, registers, reports — then keep the source of truth in your PM tool like Jira, Asana, or MS Project.
Be careful with sensitive data. Avoid pasting personal information, client names, financials, or anything under NDA unless your organization uses an enterprise plan with data controls and a no-training policy. A safe habit is to anonymize names to roles (e.g. 'the sponsor') and map them back yourself after you get the output.
Give ChatGPT real context and constraints. Paste your actual task list, real durations, the names and attitudes of stakeholders, and your hard deadlines. Ask it to flag the items most specific to your project rather than generic ones, and answer any clarifying questions it asks — the second pass is almost always sharper than the first.

Prompts are the starting line. Tutorials are the finish.

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