DSPy: The End of Prompt Engineering - Kevin Madura, AlixPartners
Applications developed for the enterprise need to be rigorous, testable, and robust. The same is true for applications that use AI, but LLMs can make this challenging. In other words, you need to be able to program with LLMs, not just tweak prompts. In this talk we'll cover why DSPy really is all you need in building applications with LLMs. We'll dive into real-world examples where we have successfully automated manual work using an opinionated DSPy-first approach to structuring applications, covering everything from simple modules to using SoTA optimizers to measurably improve performance.
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Chapters (8)
Introduction & The Enterprise AI Challenge
7:12
The 6 Core Concepts of DSPy (Signatures, Modules, Adapters)
13:23
Deep Dive: Class-based vs. Shorthand Signatures
19:57
Adapters: Controlling the Prompt Format (JSON vs. BAML)
24:17
Optimizers: The "Killer Feature" for Transferability
31:08
Code Walkthrough: Setup & Model Mixing
36:24
Handling Documents: "Poor Man's RAG" with Attachments
42:10
Adapter Comparison: Impro
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