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New MEAP! Crack Any Codebase with AI
Code is free, understanding is not
Author and Microsoft AI researcher Zachary Huang argues that in an AI-first environment, the developers who thrive will be those who build architectural thinking rather than passively accepting AI’s output. This book transforms this thesis into a hands-on training program, reframing AI code’s flaws as workout opportunities for your skills as a developer.
The ten mental models you’ll master in this book are timeless, and the book’s transferable methodology works on any codebase, in any language, at any scale. Every chapter teaches you to ask sharper questions and demand
concrete outputs. You’ll build the muscle to interrogate AI, catch its confident nonsense, and ship real changes in hours. [Read more]
5 chapters of this new MEAP are available now with more to follow soon!
Replacing manual prompts with systematic optimization
Traditional prompts often become brittle as models and data evolve. Building LLM Applications with DSPy by Serj Smorodinsky and Brett Kennedy introduces the DSPy framework, which replaces static text prompts with flexible Python-based contracts that adapt automatically over time. The book shows how DSPy optimizes context, evaluates prompt performance, and adjusts applications as models drift, helping developers maintain reliable results as AI systems grow more complex.
Focused on practical implementation, the book teaches DSPy best practices for building
