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The Agentic AI Book

Name: The Agentic AI Book
Brand: Ryan Rad
Price: 92.75 AUD

From Language Models to Multi-Agent Systems

By: RYAN RAD

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Paperback | 28 February 2026

At a Glance

Paperback
218 Pages

Dimensions(cm)
23.5 x 19.05 x 1.17

Paperback

$92.75

or 4 interest-free payments of $23.19 with

Ships in 10 to 15 business days

The barrier to building autonomous AI systems has completely collapsed, but the chasm in true engineering understanding has never been deeper.

The Agentic AI Book is the definitive engineering guide for practitioners who want to move past fragile "prompt-and-pray" scripts, understand exactly why agents work and fail, and architect autonomous systems that hold up under real-world production conditions. This book takes you from language model foundations to production-ready multi-agent systems, with enough depth to predict failure modes before they surface, design systems that degrade gracefully rather than catastrophically, and diagnose exactly what broke and why, when they do.

Inside the Book

- Build intuition around language modeling. Trace the complete problem-solving arc from bag-of-words to self-attention, understanding why each breakthrough was necessary and what it fixed. Understand scaling laws.

- Diagnose the failures that surface-level AI education never names. Move past "the model hallucinated" to isolate specific, actionable failure modes: the Reversal Curse, Flat Latency, and Underspecification in language systems; the Modality Gap and Perception-Reasoning Dissociation in multimodal ones. Coverage extends to the full VLM stack.

- Adapt models when prompting reaches its limits. Master RAG architectures, the RAG Triad, LoRA and QLoRA, and the alignment frontier - including DPO and GRPO, powering today's leading reasoning models.

- Defeat context rot and design bulletproof tools. Navigate the Six Levels of Agentic Autonomy, apply Poka-Yoke principles to the Agent-Computer Interface, and build three-tier memory systems with Just-In-Time context loading and attention budget management.

- Orchestrate multi-agent systems without paying the complexity tax. Use DAG-based task graphs and the Agent-to-Agent Interface, know when not to scale, and prevent deadlocks and runaway costs with conflict-resolution protocols and semantic compression.

- Take absolute engineering ownership of production deployment. Implement evaluation frameworks, build observability stacks, enforce guardrail architectures, debug agentic race conditions, and deploy with quantization and speculative sampling.

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