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Metaprogramming for AI: Building Dynamic, Agentic Systems in Python (Paperback) (ISBN-13: 9798271218194)
Vendor:
Jason Gran
Product type:
Books
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$25.00
Description
xStop Fighting Static Code. Start Building Truly Dynamic AI Agents.
Are you an experienced Python AI engineer hitting a wall? You're building sophisticated agents - systems that reason, plan, and act - but find yourself trapped by the rigid confines of traditional Object-Oriented Programming. Your agent frameworks feel brittle, difficult to extend, and incapable of the true runtime adaptation that intelligent systems demand. You know there has to be a better way.
There is. The techniques you need aren't in a new, complex library - they're hidden in plain sight within Python itself. Metaprogramming for AI unlocks these "lost arts" to fundamentally change how you architect intelligent systems.
This isn't just theory. This is a hands-on, deep dive into the practical application of Python's meta-object protocol specifically for building the next generation of AI:
Master the "Why" and "How" Understand why dynamic approaches are essential for agentic workflows and solidify your grasp of the core Python Object Model (type, __new__, __dict__).
Wield Python's MOP: Learn to intercept class creation with metaclasses to automate tool registration and enforce architectural rules. Harness descriptors to create self-validating attributes and manage stateful connections (like vector databases) efficiently.
Build Evolvable Systems: Go beyond static blueprints. Engineer agents capable of runtime modification - adding new, LLM-generated tools and skills while running.
Compose Complex Behaviors: Leverage mixins and understand the MRO to build sophisticated agents from reusable, modular components (like logging, state management, and memory).
Engineer Real-World Solutions: Apply these techniques through two capstone projects: a Self-Modifying Agent that learns new tools on the fly and a Dynamic RAG Pipeline with swappable, auto-registered components.
Adopt a Dynamic Mindset: Move beyond simple scripting and prompt engineering to architect truly reflective, adaptable, and scalable AI platforms.
This book is for:
Senior Python/AI developers frustrated with static framework limitations.
Engineers building complex agentic workflows, RAG pipelines, and LLM orchestration systems.
Architects designing maintainable and extensible AI platforms.
Anyone who wants to move beyond surface-level AI and master the deep system design required for truly intelligent applications.
This book is NOT for Python beginners. It assumes professional experience and a desire to go deep.
If you're ready to stop patching brittle systems and start engineering AI that can truly learn and evolve, this book is your guide.
Scroll up and grab your copy today!
Author: Jason Gran
ISBN-13: 9798271218194
Publisher: Independently Published
Language: English
Published: 10/23/2025
Pages: 394
Format: Paperback
Weight: 1.50lbs
Size: 10.00h x 7.00w x 0.81d
Are you an experienced Python AI engineer hitting a wall? You're building sophisticated agents - systems that reason, plan, and act - but find yourself trapped by the rigid confines of traditional Object-Oriented Programming. Your agent frameworks feel brittle, difficult to extend, and incapable of the true runtime adaptation that intelligent systems demand. You know there has to be a better way.
There is. The techniques you need aren't in a new, complex library - they're hidden in plain sight within Python itself. Metaprogramming for AI unlocks these "lost arts" to fundamentally change how you architect intelligent systems.
This isn't just theory. This is a hands-on, deep dive into the practical application of Python's meta-object protocol specifically for building the next generation of AI:
Master the "Why" and "How" Understand why dynamic approaches are essential for agentic workflows and solidify your grasp of the core Python Object Model (type, __new__, __dict__).
Wield Python's MOP: Learn to intercept class creation with metaclasses to automate tool registration and enforce architectural rules. Harness descriptors to create self-validating attributes and manage stateful connections (like vector databases) efficiently.
Build Evolvable Systems: Go beyond static blueprints. Engineer agents capable of runtime modification - adding new, LLM-generated tools and skills while running.
Compose Complex Behaviors: Leverage mixins and understand the MRO to build sophisticated agents from reusable, modular components (like logging, state management, and memory).
Engineer Real-World Solutions: Apply these techniques through two capstone projects: a Self-Modifying Agent that learns new tools on the fly and a Dynamic RAG Pipeline with swappable, auto-registered components.
Adopt a Dynamic Mindset: Move beyond simple scripting and prompt engineering to architect truly reflective, adaptable, and scalable AI platforms.
This book is for:
Senior Python/AI developers frustrated with static framework limitations.
Engineers building complex agentic workflows, RAG pipelines, and LLM orchestration systems.
Architects designing maintainable and extensible AI platforms.
Anyone who wants to move beyond surface-level AI and master the deep system design required for truly intelligent applications.
This book is NOT for Python beginners. It assumes professional experience and a desire to go deep.
If you're ready to stop patching brittle systems and start engineering AI that can truly learn and evolve, this book is your guide.
Scroll up and grab your copy today!
Author: Jason Gran
ISBN-13: 9798271218194
Publisher: Independently Published
Language: English
Published: 10/23/2025
Pages: 394
Format: Paperback
Weight: 1.50lbs
Size: 10.00h x 7.00w x 0.81d
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