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Most "AI agent" tutorials build something that works in the demo and dies the second it touches real work. It nails the happy path on stage, then quietly fails on the messy input, the long task, the thing nobody tested.
This is the course for the other kind. The agent that survives real work: long tasks, weird input, running while you're asleep, and still being right when you check it.
No fluff, no 50-prompt chains. 14 steps, grouped into four parts: understand what an agent actually is, build the core, make it reliable, then ship it.
## Part 1 - What an agent actually is
<b> 1. An agent is a goal, tools, and a loop. Not a clever prompt.</b>
Anthropic's own definition is almost boring: an agent is an LLM using tools in a loop to reach a goal. That's it. Not a magic prompt, not a personality.
The prompt is one piece. The agent is the system around it: the job it owns, the tools it can reach, the loop that lets it try, check, and try again. Get the system right and an average prompt works. Get the system wrong and the best prompt in the world still fails on step 12.
If you remember one thing from this whole course: you are not writing a prompt, you are designing a loop.
<b>2. The 3 things that kill agents in production</b>
Before you build, know what you're defending against. Every agent that dies in the real world dies from one of these:
• <b><i>Laziness.</i></b><i> It does 8 of 12 steps, then declares the job done. The demo had 3 steps so you never saw it.</i>
• <b><i>Goal drift.</i></b><i> Over a long run it slowly forgets the original goal. The "don't touch the billing code" rule quietly disappears around turn 40.</i>
• <b><i>No real verification.</i></b><i> It says "done" with no proof. A model grading its own work is always happy with it.</i>
Every step below exists to beat one of these three. If a step doesn't fight laziness, drift, or weak verification, it's decoration.
## Part 2 - Build the core
<b>3. Give it ONE narrow job</b>
The most common mistake is building a "general assistant." That's not an agent, that's chat with extra steps.
A real agent owns one repeatable job: triage incoming bugs, draft release notes, reconcile two spreadsheets, answer support tickets from your docs. One job you could describe to a new hire in a sentence.
Narrow is not a limitation. Narrow is what makes it testable, trustable, and good. Build five agents that each do one thing well before you build one that does five things badly.