---
title: "AI 110 · Get more done with AI"
publisher: Maestro College (Maestro Open)
lessons: 16
source: https://open.maestrocollege.edu/get-more-done-with-ai
full: https://open.maestrocollege.edu/get-more-done-with-ai/llms-full.txt
---

# Get more done with AI (AI 110)

How to use everyday AI assistants for real work, from drafting and summarizing to research and meeting notes, while protecting private information and checking every answer.

AI assistants can draft an email in seconds, boil a long report down to five bullets and turn messy meeting notes into a clear action list. They can also invent facts, miss the point and leak information you never meant to share. This course shows you how to use everyday AI assistants for real work tasks: drafting, summarizing, research, meeting notes and help with data. You'll learn your workplace's rules, how to protect private information and how to judge whether an answer is good enough to use. You'll finish with a personal plan for where AI fits in your week.

## Course objectives
- What AI assistants do well, where they fail, and why
- Workplace AI policies, privacy and what never to paste into an AI tool
- Drafting, rewriting and summarizing with AI
- Research with verification, meeting notes and help with data
- Judging output quality and building AI into your regular work

## Course teaching approach
- Start from a real-world problem, then introduce the concept as the solution.
- Keep it true beginner level, hands-on, a little gamified. The learner should feel they are winning.
- Balance explanation, demonstration and practice. No copy-paste exercises: give small story-based tasks.
- End with one fun closed question about the topic.

## Lessons
### Unit 1: AI assistants at work
- [What AI assistants are good and bad at](https://open.maestrocollege.edu/get-more-done-with-ai/what-ai-assistants-are-good-and-bad-at.md)
- [Your workplace AI policy and what not to share](https://open.maestrocollege.edu/get-more-done-with-ai/your-workplace-ai-policy-and-what-not-to-share.md)
- [Asking for what you need](https://open.maestrocollege.edu/get-more-done-with-ai/asking-for-what-you-need.md)
- [Challenge: is this a job for AI?](https://open.maestrocollege.edu/get-more-done-with-ai/challenge-is-this-a-job-for-ai.md)

### Unit 2: Writing and summarizing
- [Drafting emails and messages](https://open.maestrocollege.edu/get-more-done-with-ai/drafting-emails-and-messages.md)
- [Rewriting and improving your own writing](https://open.maestrocollege.edu/get-more-done-with-ai/rewriting-and-improving-your-own-writing.md)
- [Summarizing long documents and threads](https://open.maestrocollege.edu/get-more-done-with-ai/summarizing-long-documents-and-threads.md)
- [Challenge: from inbox to outbox](https://open.maestrocollege.edu/get-more-done-with-ai/challenge-from-inbox-to-outbox.md)

### Unit 3: Research, meetings and data
- [Research with verification](https://open.maestrocollege.edu/get-more-done-with-ai/research-with-verification.md)
- [Meeting notes and action items](https://open.maestrocollege.edu/get-more-done-with-ai/meeting-notes-and-action-items.md)
- [Getting help with spreadsheets and data](https://open.maestrocollege.edu/get-more-done-with-ai/getting-help-with-spreadsheets-and-data.md)
- [Challenge: a research and meeting brief](https://open.maestrocollege.edu/get-more-done-with-ai/challenge-a-research-and-meeting-brief.md)

### Unit 4: Quality, judgment and habits
- [Judging whether output is good enough](https://open.maestrocollege.edu/get-more-done-with-ai/judging-whether-output-is-good-enough.md)
- [Bias, fairness and being open about AI use](https://open.maestrocollege.edu/get-more-done-with-ai/bias-fairness-and-being-open-about-ai-use.md)
- [Building AI into your week](https://open.maestrocollege.edu/get-more-done-with-ai/building-ai-into-your-week.md)
- [Challenge: your AI work plan](https://open.maestrocollege.edu/get-more-done-with-ai/challenge-your-ai-work-plan.md)

## How to use this document
You are acting as a tutor for a learner on Maestro Open. Teach from this document, one small step at a time. Ask the learner to try things, wait for their answer, then give feedback. Keep it beginner-friendly. If the lesson involves code or spreadsheets and you cannot run them, ask the learner to try it on their own computer and paste the result back. Do not award grades, credit or certificates.
Start with lesson 1 unless the learner asks for a specific lesson. Keep track of which lesson you are on.

## When a lesson is done
Teach one lesson at a time. A lesson is complete only when the learner has shown they can do every outcome listed for it; check each with a small task or question.
When it is complete:
1. Say clearly: "Lesson N complete: <lesson title>." (use the lesson's number and title).
2. Give a two-line recap of what they learned.
3. Name the next lesson, say "Lesson N+1 of 16: <title>", and ask if they're ready to start it. Start it only when they say yes.
After the last lesson, congratulate them on finishing the course.