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Module
Module 4 of 5Lesson 1 of 4~12 min

General-purpose assistants

ChatGPT, Claude, Gemini, Perplexity or Mistral Le Chat: general-purpose assistants look alike, but not on every point. This lesson helps you choose between them based on your need, from writing to sourced research, and spot the terms that rule some of them out for your data.

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

Lesson objective

By the end of this lesson, you will be able to choose a general-purpose assistant based on your needs (writing, sourced research, ecosystem, privacy) and spot the terms that rule it out for certain data.

Topics covered

  • ChatGPT
  • Claude
  • Gemini
  • Mistral Le Chat
  • AI assistant comparison

Where it fits

Choosing the right tool and way of working

Which tool, and which way of using it, for which need?

Lessons in this module

  1. General-purpose assistants (this lesson)
  2. Conversation, project, research, agent: choosing the mode
  3. Specialized tools
  4. The tool selection grid

What you will learn in the course

This lesson is part of the course Choosing and using AI tools at work

  • Explain how a generative AI assistant works and what it does well or badly, so you know what to ask of it.
  • Identify a tool's limits (fabrications, sources, freshness, data privacy) and the precautions to take before using it.
  • Write a clear request (task, context, data, format, criteria) that produces a usable first result.
  • Diagnose why a response falls short and fix it with a targeted clarification.
  • Select the right tool for a deliverable using a grid of criteria (deliverable, data, sources, cost, language, integration) and justify the choice.
  • Choose the right way of working for a task (conversation, project, deep research, agent) and the level of control that goes with it.
  • Build your toolkit by comparing at least two tools on a real task with criteria written in advance.

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