Building AI Agents in Python
Transform static AI prompts into autonomous Python programs that reason, call functions, and solve multi-step problems on their own.
Like Duolingo, but for Building AI Agents in Python. Tomo turns the whole topic into a game you play five minutes a day, until it actually sticks.
A short one: 8 levels across 2 sections, about 16 minutes end to end, roughly 3 days at five minutes a day. It moves through Making AI Take Action and Steering and Guardrails. It starts from scratch.
Free forever · No credit card · iPhone & Android
Key ideas in Building AI Agents in Python
- An agent runs inside a loop where Python queries the model and acts on its response
- Python must execute the action the model decided on before gathering the result
- The loop repeats by feeding that new result back to the model for the next decision
- Python needs predictable keys and values to safely call functions based on model output
- Free-form conversational text is difficult and brittle for Python code to parse into specific arguments
- Structured text like JSON bridges the gap between text generation and code execution
- A standard Python while loop requires an explicit break condition or return statement to terminate
- The agent loop cannot guess if a problem is solved unless the model signals it is finished or reaches a step limit
- Without an explicit completion check in Python, the loop risks running continuously and wasting API calls
- LLMs are stateless: each API call has no memory of previous calls unless the history is passed in
- The agent loop relies on appending each step's action and tool output to an ongoing list of messages
- Omitting tool results from the conversation list leaves the model unaware of what it already discovered
- An AI model does not run or inspect the internal Python code directly; it reads a tool definition
- The model decides whether and how to call a function based on its signature (name and arguments) and text description
- Your Python environment executes the function only after the model generates a request matching the signature
- LLMs use docstrings as instructions to judge which tool matches the user's prompt
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 Building AI Agents in Python 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.
When the AI model decides to look up a file or run a search, who actually performs that action?
Get it right to open this lesson and 7 more in the app.
How to learn Building AI Agents in Python, step by step
Go in order. 8 short levels across 2 sections, about 16 minutes in all, five minutes a day.
- 1
Making AI Take Action
- The Core Agent Loop
- Turning Python Functions into AI Tools
- 2
Steering and Guardrails
- Steering Decisions and Setting Guardrails
2 sections · 3 units · 8 levels. Built to play, not to enroll.
Questions about Building AI Agents in Python
How do I learn Building AI Agents in Python?
Go in order: start with Making AI Take Action, then Steering and Guardrails. On Tomo that's 8 short levels, about 16 minutes in all, played five minutes a day. Start free and play the first level in under a minute.
Is there a Duolingo-style app for Building AI Agents in Python?
Yes. Tomo works like Duolingo: short daily lessons, streaks and quick quizzes. Building AI Agents in Python is one of its free courses, and you can type any other topic to get a course of your own.
Is the Building AI Agents in Python course free?
Yes. Building AI Agents in Python is playable on Tomo's free plan, which doesn't expire. No credit card, no waitlist. Download the app and start your first lesson.
How long does it take to learn Building AI Agents in Python?
8 levels across 2 sections, about 16 minutes of play in total. It's built for five minutes a day, so you finish it a little at a time instead of all at once.
Do I need any background to start Building AI Agents in Python?
No. It's pitched at a beginner level, so it starts where you are and builds up. If you can tap a phone, you can start.
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
Building AI Agents in Python is taught in the Bestie style: your friend who just gets it. 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.
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Start Building AI Agents in Python today.
Download Tomo, search Building AI Agents in Python, and play your first lesson in under a minute.