Free sample
One full lesson, and the prompts to go with it
A real sample of The AI Agents Course: the complete research-agent lesson, printed below with nothing held back, plus a starter prompt pack you can copy straight into whatever assistant you already use.
Track B — No-code · Module 01
The research agent, built end to end
This is one complete lesson from the course, printed in full. You build a research agent that takes an open question, searches, and hands back a short brief with sources — and, more importantly, one that stops instead of running forever. No account, no download, nothing withheld halfway through.
- A working agent that answers questions with cited sources.
- A stopping rule, so it finishes instead of looping.
- A refusal rule, so it returns nothing rather than inventing an answer.
01. Write the job down before you touch a builder
An agent is four things: a goal, the tools it may use, a loop, and a done-condition. Skip any one of them and you get a chatbot that costs money.
Write yours out in plain language first. For this build it is: answer one research question with sourced findings, using web search, in at most eight search steps, stopping when the brief is written or the step cap is hit.
02. Create the assistant and paste the instruction block
In whichever assistant builder you use, create a new assistant and put this in the persistent instructions field. It is deliberately blunt — instructions that read like a personality description produce agents that behave like one.
You are a research agent. You answer one question per run. Process: 1. Break the question into at most 3 sub-questions. 2. Search for each. Maximum 8 searches total across the whole run. 3. Stop searching as soon as you can support a recommendation, even if that is after 2 searches. Rules: - Every factual claim carries a source link. No link, no claim. - Never answer from memory. If search is unavailable, say so and stop. - If sources disagree, report the disagreement. Do not resolve it yourself. - If you cannot support an answer, return "No reliable answer found" plus the list of what you checked. This is a correct outcome, not a failure. Output format, exactly: RECOMMENDATION — one sentence WHY — 3 bullets, each with a source link TRADE-OFFS — 2 bullets NOT VERIFIED — list, or "nothing"
03. Give it exactly one tool
Turn on web search. Turn everything else off. The most common cause of an agent behaving unpredictably is that it has five tools and no rule about which to reach for.
One tool per agent until it works. Add the second only when you can describe, in a sentence, the condition under which it should be chosen over the first.
04. Test it on a question you already know the answer to
This is the step that separates a demo from something you trust. Ask it something where you can personally verify the answer — a price you already know, a specification you have checked.
You are not testing whether it sounds good. You are testing three things: are the links real, does the recommendation match the evidence beneath it, and did it stop.
05. Break it on purpose
Now ask it something unanswerable — a fact that does not exist, or a question about a private company's internals.
A correct agent returns "No reliable answer found". If instead it produces a confident paragraph with plausible-looking sources, the refusal rule is not landing: move it higher in the instructions and state it twice. Agents weight the beginning and the end of an instruction block most heavily.
06. Give the output somewhere to land
Send the brief to a document, a note, or an email draft — anywhere a human reads it before it goes anywhere else.
That is the whole lesson in one line: the first version of any agent writes a draft. Automatic sending comes later, if ever. The six builds in the full course are this same shape with more moving parts.
Starter prompt pack
8 prompt blocks, free
The blocks I paste when I start an agent: the job spec that comes before the build, four of the six agent builds, the guardrail block that stops it running away, and the post-mortem for when it gets something wrong.