Mastering GenAI Series
Our Mastering GenAI series shares 0+ pages of tactical, engineering-focused playbooks on how to evaluate, guard, and monitor AI agents and LLM systems.
Learn how to detect hallucinations, build reliable RAG pipelines, implement safety guardrails, and evaluate AI agents - all with practical, production-ready techniques.
Read these in-depth eBooks to learn how to:
- Go beyond basic vector search - Catch the answers vector search misses by layering keyword matching, knowledge graphs, and smart query routing into one pipeline
- Fix retrieval at the source - What you retrieve depends on how you chunk. Learn chunking, parent-child structures that keep meaning intact as your knowledge base scales
- Build Production-Ready Systems - Go from RAG basics to enterprise deployment with proven frameworks that work at scale
- Eliminate Costly Failures - Master hallucination reduction and robust evaluation to ensure reliability before launch
- Understand agent failure modes - Learn how planning, memory, and tool use make agents fail differently from traditional ML (and how to catch it)
- Set up a complete eval stack - Instrument agents with span/trace signals and metrics to make behavior transparent and debuggable
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Advanced RAG Patterns
Standard RAG breaks in predictable ways. At enterprise scale, those failures compound - missed answers, rising costs, and compliance risks. This handbook gives you the architecture patterns to close the gap and build retrieval systems your organization can rely on.
The Agentic RAG Playbook
Transform RAG theory into product-ready enterprise solutions that deliver measurable business impact.
Mastering AI Agent Evaluation
AI agents are easy to spin up and dangerously hard to trust in production. This ebook gives you a concrete evaluation playbook to turn messy, non-deterministic agents into controlled systems you can rely on in high-stakes environments.