Putting it together

You've taken the call apart, forced its shape, given it tools, streamed it, and fed it well. So what actually changes when you sit down to build?

What you've got now

In seven short lessons you've picked up the durable toolkit behind AI apps — not a framework that'll be stale next quarter, but the ideas every framework is built on. Here's the whole thing in one view.

• —The call — send system + messages + parameters; the model is stateless, you own the memory.
• —Structured output — demand a schema so the reply is data your code can trust.
• —Tool calling — let the model request functions your code runs; that's how agents act.
• —Streaming & latency — stream for interactive UIs; right-size the model for the real clock.
• —Context engineering — the window is a budget; curate what earns a slot.

The one habit to keep

If you keep one thing: the model proposes, your code disposes. It generates; you constrain, validate, and decide what happens next — the schema, the tool limits, the fallback, the human check. Build with that stance and you get the model's power without betting your product on it being right.