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AI agent for change managers

Lessons Learned Capture and Reuse Agent

Make past lessons show up in new project plans and prove they worked.

Document handlingAutomationManagement
See how it worksGet access
Lessons Learned Capture and Reuse Agent: what goes in, what the agent does and what you get

What it does

At the end of a project the team holds a lessons meeting, writes a document, and files it where no one looks. The next project repeats the same mistakes. This agent gathers lessons at project close from the retrospective notes, risk log and issue log. It tags each by type, such as vendor, testing or change adoption. When a new project starts, it matches its traits to past lessons and drafts specific checks for the plan, such as a pilot before rollout. It then tracks whether each lesson was applied and whether the problem happened again. The manager approves what is added to the plans. Edge case: a lesson that was applied but the same issue occurred anyway is marked as ineffective and sent for review.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
ApprovedYes, continueYes, continueNoNo 1 STARTS WHEN Project closes with retrospective notes 2 USES A TOOL Read notes, risk log and issue log 3 DOES Extract lessons and tag them by type and projecttrait 4 USES A TOOL Store lessons in the library 5 USES A TOOL At a new project, read its traits and plan 6 DOES Match lessons to the plan by trait 7 DOES Draft specific checks and tasks for the plan 8 YOU APPROVE Manager approves what is added to the plan 9 CHECKS THE RESULT Was each added check applied by its due date? If not: Remind the owner and mark it overdue. Back tostep 8. 10 CHECKS THE RESULT Did the issue stay away? If not: Mark the lesson ineffective and ask the team torevise it. Back to step 6. 11 RESULT Lesson application report
Read the steps as a list
  1. Project closes with retrospective notes
  2. Read notes, risk log and issue log
  3. Extract lessons and tag them by type and project trait
  4. Store lessons in the library
  5. At a new project, read its traits and plan
  6. Match lessons to the plan by trait
  7. Draft specific checks and tasks for the plan
  8. Manager approves what is added to the planThe agent waits here for your OK.
  9. Was each added check applied by its due date?If not: Remind the owner and mark it overdue. Back to step 8.
  10. Did the issue stay away?If not: Mark the lesson ineffective and ask the team to revise it. Back to step 6.
  11. Lesson application report

How it decides

Matches lessons to a new project by shared traits and adds a check only if at least two traits match; a lesson is effective only if the issue does not recur.

  • Match needs at least 2 shared traits
  • A lesson older than 3 years is flagged for review
  • Overdue check goes to the owner after 5 days
  • Recurred issue means the lesson needs rewriting

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Traits used for matching
  • Number of matching traits (default 2)
  • Reminder delay (default 5 days)
  • Lesson age limit (default 3 years)
  • Library location

What keeps you in control

It always asks you first

  • Additions to project plans
  • Changes to the lesson library
  • Any lesson marked ineffective

Hard limits

  • Never edit a plan without approval
  • Never delete a lesson

It stops when

  • Done: lessons applied and results recorded
  • Stop: project cancelled
  • Stop: no matching lessons

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensA new ERP rollout shares three traits with a past project that failed because no pilot was run. The agent drafts a pilot check and a data cleansing task. The manager approves both. At go-live prep the pilot check is overdue. The check fails, so it reminds the owner. The pilot runs two weeks late. After launch, the same data issue does not appear, and the lesson is marked effective.

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