Stop prompting. Start engineering.
The initial awe of generative AI has faded, replaced by a gnawing practical reality: Large Language Models (LLMs) are brilliant storytellers, but terrible employees. We ask them to analyze financial reports, diagnose system failures, and automate customer support. In return, they offer us "hallucinations"—confident, grammatically perfect assertions that are factually wrong.
For a creative writer, a hallucination is a spark of inspiration. For a supply chain manager or a financial auditor, it is a catastrophic liability.
This volume is not about training a bigger, better model; it is about building a better architecture. For the first time in technical literature, we introduce the paradigm of Computational Symbiosis by fusing three distinct pillars of modern intelligence:
- The Reasoning Core (Google Gemini/LLMs): The probabilistic brain that understands human intent, nuance, and creativity.
- The Logic Engine (Wolfram Alpha): The deterministic calculator that enforces mathematical rigor and scientific truth, ensuring that 2 + 2 always equals 4, regardless of the LLM's opinion.
- The Enterprise Librarian (IBM Watson): The grounded memory that anchors the agent in your private, unstructured enterprise data, ensuring it knows your business, not just the internet.
FROM CLOUD API TO LOCAL SOVEREIGNTY (Chapters 21-26)
But we do not stop there. We understand that data sovereignty, privacy, and cost are critical constraints. Therefore, the final chapters of this book teach you how to replicate this entire architecture using purely Open Source, local-first tools. You will learn to replace the cloud giants with Llama 3 (via Ollama), SymPy, and ChromaDB to build "Air-Gapped" agents that run entirely on your own infrastructure.
After Reading This Book, What Will You Be Able to Build?
You will possess the architectural blueprints to solve problems that defeat standard LLM wrappers. Here are four concrete examples of what you will be able to realize:
- The "Zero-Liability" Financial Auditor.
- The Self-Healing Software Engineer.
- The Global Supply Chain Commander.
- The "Air-Gapped" Intelligence Analyst (Open Source Capstone).
In this book, you will stop treating AI as a magic black box. You will learn to treat it as a component in a larger system—a reasoning engine that must be audited, fact-checked, and grounded before it is allowed to act.
We are entering the era of the Neuro-Symbolic Agent.
Prerequisites
Intermediate Python Proficiency: Please note: This is not a syntax tutorial or a beginner's guide. It is a rigorous engineering manual that requires active dedication to master complex architectural patterns.
Full source code on GitHub.
Stop prompting. Start engineering.
The initial awe of generative AI has faded, replaced by a gnawing practical reality: Large Language Models (LLMs) are brilliant storytellers, but terrible employees. We ask them to analyze financial reports, diagnose system failures, and automate customer support. In return, they offer us "hallucinations"—confident, grammatically perfect assertions that are factually wrong.
For a creative writer, a hallucination is a spark of inspiration. For a supply chain manager or a financial auditor, it is a catastrophic liability.
This volume is not about training a bigger, better model; it is about building a better architecture. For the first time in technical literature, we introduce the paradigm of Computational Symbiosis by fusing three distinct pillars of modern intelligence:
- The Reasoning Core (Google Gemini/LLMs): The probabilistic brain that understands human intent, nuance, and creativity.
- The Logic Engine (Wolfram Alpha): The deterministic calculator that enforces mathematical rigor and scientific truth, ensuring that 2 + 2 always equals 4, regardless of the LLM's opinion.
- The Enterprise Librarian (IBM Watson): The grounded memory that anchors the agent in your private, unstructured enterprise data, ensuring it knows your business, not just the internet.
FROM CLOUD API TO LOCAL SOVEREIGNTY (Chapters 21-26)
But we do not stop there. We understand that data sovereignty, privacy, and cost are critical constraints. Therefore, the final chapters of this book teach you how to replicate this entire architecture using purely Open Source, local-first tools. You will learn to replace the cloud giants with Llama 3 (via Ollama), SymPy, and ChromaDB to build "Air-Gapped" agents that run entirely on your own infrastructure.
After Reading This Book, What Will You Be Able to Build?
You will possess the architectural blueprints to solve problems that defeat standard LLM wrappers. Here are four concrete examples of what you will be able to realize:
- The "Zero-Liability" Financial Auditor.
- The Self-Healing Software Engineer.
- The Global Supply Chain Commander.
- The "Air-Gapped" Intelligence Analyst (Open Source Capstone).
In this book, you will stop treating AI as a magic black box. You will learn to treat it as a component in a larger system—a reasoning engine that must be audited, fact-checked, and grounded before it is allowed to act.
We are entering the era of the Neuro-Symbolic Agent.
Prerequisites
Intermediate Python Proficiency: Please note: This is not a syntax tutorial or a beginner's guide. It is a rigorous engineering manual that requires active dedication to master complex architectural patterns.
Full source code on GitHub.
Architecting Neuro-Symbolic Agents with Python Programming. Integrating LLMs, Wolfram Alpha, IBM Watson and Open Source Stacks for Near-Zero Hallucination Systems
Architecting Neuro-Symbolic Agents with Python Programming. Integrating LLMs, Wolfram Alpha, IBM Watson and Open Source Stacks for Near-Zero Hallucination Systems
Product Details
| BN ID: | 2940183248982 |
|---|---|
| Publisher: | Edgar Milvus |
| Publication date: | 12/29/2025 |
| Sold by: | Draft2Digital |
| Format: | eBook |
| File size: | 9 MB |