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Module
Module 5 of 5Lesson 2 of 2~24 min

Workshop: your grid on ten tasks, the exit kit and the application plan

The final workshop applies the grid to ten real tasks from your job, several of them tested directly in your tool. You assess how solid your choices are and leave with a reusable kit and a plan to anchor these decisions firmly in your day-to-day work.

Take this lesson: your first course is freeSee the full syllabus

Lesson objective

By the end of this lesson, you will have produced your "delegate / verify / keep" grid on ten real tasks from your job, tested at least three of them in your tool, and planned how to apply it over 7 and 30 days.

Topics covered

  • AI workshop
  • delegate verify keep grid
  • AI adoption plan
  • AI at work

Where it fits

Deciding what to delegate

For each of my tasks, what do I hand to AI, what do I verify and what do I keep?

Lessons in this module

  1. The "delegate / verify / keep" grid
  2. Workshop: your grid on ten tasks, the exit kit and the application plan (this lesson)

What you will learn in this module

This lesson is part of the course Understand what LLMs do well, and where they fail

  • Anticipate hallucinations, sycophancy, poorly calibrated confidence and run-to-run variability, and choose the right check for each case.
  • Locate what the model knows (training data, knowledge cutoff, uneven coverage) and what web search, provided documents and connectors change.
  • Explain the context window as working memory (limit, degradation over long contexts, no memory across conversations without a dedicated feature) and derive working rules from it.
  • Sort the tasks of your job into "delegate / verify / keep" based on the cost of an error, how easy it is to verify, the model property involved and the value of doing it yourself.

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