Building Your First AI Agent: A Hands-on Guide
Hey there! 👋 If you’re joining us from the first article, welcome back! If you’re new here, no worries — just check out the first article to get up to speed.
Today, we’re rolling up our sleeves and building something cool: a smart agent that can actually learn from its environment. No more “if-this-then-that” stuff — we’re going full autonomous!
What We’re Building
We’re creating a trading agent that can:
- Read market data
- Make decisions based on patterns
- Learn from its successes and failures
- Adapt its strategy over time
Don’t worry if you’ve never done anything with trading — the principles we’ll learn apply to any kind of agent system.
The Sense-Plan-Act Cycle
Remember our digital butler analogy from last time? Let’s upgrade it. Every smart agent follows what we call the Sense-Plan-Act cycle. Think of it like a human making decisions:
1. Sense: Get information (like checking your phone’s weather app)
2. Plan: Process that information (like deciding whether to take an umbrella)
3. Act: Do something based on your plan (like actually grabbing that umbrella)