AI Agents at Work
Learn how AI agents move beyond simple conversation to solve problems, use external tools, and automate complex multi-step tasks on your behalf.
Like Duolingo, but for AI Agents at Work. Tomo turns the whole topic into a game you play five minutes a day, until it actually sticks.
23 levels across 4 sections, about 46 minutes end to end, roughly 9 days at five minutes a day. It moves through Putting Agents to Work, Keeping Agents on Track, Designing Multi-Step Automations, and Under the Hood of Autonomous AI. It starts from scratch.
Free forever · No credit card · iPhone & Android
Key ideas in AI Agents at Work
- A chatbot is limited to producing conversational text in a single turn
- An AI agent can trigger real-world tools and carry out a chain of actions in the environment
- Agents work toward an objective rather than just answering a prompt
- The agent first searches for candidates matching the basic location and budget constraints
- It then compares and filters the candidates against the review rating criteria
- Finally, it executes the action of reserving the selected room
- AI agents run in continuous feedback loops (acting, observing the result, and deciding what to do next)
- If a tool call or action encounters an error, the agent uses that feedback to adjust its next move
- Agents lack human common sense and need measurable criteria to judge if an outcome is met
- Vague goals make it impossible for an agent to evaluate whether it has succeeded or should keep working
- Language models only know what was in their training data
- An AI cannot reach out to the live internet unless an external tool explicitly fetches the data for it
- Tools are shown to the AI with plain text descriptions explaining what they do
- The model matches the user's intent to the tool whose written description best solves the problem
- The AI generates the text command or arguments rather than running the code itself
- The host application intercepts the AI's request, runs the tool, and feeds the output back into the conversation
You've tried the other tabs
Thirty open tabs. Four facts you actually kept.
You watched. You nodded. By Sunday it was gone.
One answer, then back to scrolling.
Eight weeks. You meant to finish. You didn't.
Tomo gives AI Agents at Work the Duolingo treatment: levels, streaks, and quick quizzes that test what you just learned. That game loop is what the tabs above never had, so it's the one you actually finish.
Here's what playing it feels like
A real question from this course. Take your best guess.
You want an AI to tidy your email by deleting spam and filing receipts. Why use an AI agent instead of a chatbot?
Get it right to open this lesson and 22 more in the app.
Where AI Agents at Work takes you
- 1
Putting Agents to Work
- Giving an AI a Goal Instead of a Chat
- Equipping Agents with Tools
- 2
Keeping Agents on Track
- Setting Boundaries and Stop Conditions
- The Human-in-the-Loop Pattern
- 3
Designing Multi-Step Automations
- Managing Agent Memory Across Tasks
- Coordinating Multi-Agent Workflows
- 4
Under the Hood of Autonomous AI
- The Think-Act-Observe Engine
- Choosing the Right Automation Architecture
4 sections · 8 units · 23 levels. Built to play, not to enroll.
Tomo is in ChatGPT
Tomo is also a ChatGPT plugin: the same playable courses, built and played inside your chat.
Add Tomo to ChatGPT- What to ask
- “Make me a Tomo course on black holes.” “Turn this chat into a Tomo course.”
- What you get
- Quick questions with instant feedback, hearts and stars, ready to play in about a minute.
- Where it goes
- No sign-up to start. Connect your Tomo account and your streak carries on in the app.
You pick the voice
AI Agents at Work is taught in the Professor style: clear, structured, thorough. Want a different feel? In the app you can spin up the same topic in any of Tomo's teaching styles. Same facts, totally different vibe.
More Technology on Tomo
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Move beyond basic chat prompts to build AI that takes action. Learn how agents use tools, plan multi-step tasks, and operate safely under human oversight.
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Move beyond simple chat and learn how to build AI systems that can use tools, plan complex tasks, and work autonomously to solve real-world problems.
Building with Agentic Platforms
Move beyond basic prompting into full autonomous agent architectures. Learn how to bind tools, manage stateful graphs, orchestrate multi-agent swarms, and implement robust production guardrails.
Building Autonomous AI Agents
Bridge the gap between basic prompting and production-grade agentic systems. Learn how to architect autonomous loops, manage memory, coordinate multi-agent topologies, and deploy reliable self-healing workflows.
How Artificial Intelligence Works
Go beyond the hype to understand how AI actually processes information, how to get the best results from it, and where its limits truly lie.
Working with Modern AI
Understand how contemporary artificial intelligence models actually process, reason, and generate information. Learn to steer models via structured outputs, ground them with retrieval systems, and navigate the architectural trade-offs powering modern AI applications.
Start AI Agents at Work today.
Download Tomo, search AI Agents at Work, and play your first lesson in under a minute.