Basic prompting can take you surprisingly far. Clear instructions, a well-defined task, and a specified output format are often enough to get good results from modern language models.

But some problems require more control.

Tasks like complex reasoning, structured data extraction, long-form generation, or multi-step workflows often benefit from more advanced prompting strategies. These techniques help guide how the model processes information, reduce ambiguity, and improve reliability across a wider range of inputs.

In this chapter, we will explore several advanced prompting techniques that go beyond simple instructions.