Author(s): Gaurav Shrivastav

Originally published on Towards AI.

Let’s learn context engineering in this course!!

So, Large Language Models (LLMs) are everywhere. We all know it. But actually building something useful and reliable with them? That’s a whole different story. It often feels like you’re wrestling with a brilliant but unpredictable intern.

This article explores the concept of “context engineering,” which involves effectively providing Large Language Models (LLMs) with the necessary information to generate desired outputs. It highlights the importance of building effective prompts, using examples and constraints to improve responses, and introduces DSPy as a framework for managing prompt workflows, aiming to make LLM applications more efficient and less error-prone. The author emphasizes the significance of structured prompting and offers insights into how DSPy can streamline the development process.

Read the full blog for free on Medium.

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Published via Towards AI