What we’ll learn today

What we’ll learn today

In this tutorial we’ll build a haiku-writing program that starts with four lines of Python and grows into a tool-using, prompt-optimized agent. Along the way we’ll touch each of DSPy’s core components. We’ll learn:

- How to install DSPy, configure a **language model** and write a simple DSPy program.  
- What a **Signature** is, and why DSPy uses signatures instead of hand-written prompt strings.  
- What a **Module** is, how `Predict`, `ChainOfThought`, and `ReAct` differ, and when to reach for each.  
- How to compose a custom `dspy.Module` that decomposes a task into named, independent stages.  
- How to write **metrics** and use **optimizers** to compile better versions of our program.  
- How to save optimized programs and reload them.

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**Next:** [Setting up DSPy →](installation.md)