Books by Alex Merced
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The wiki gives you a definition. These books give you the full treatment of the same territory across data and AI.
AI-Ready Data
Designing data platforms optimized for LLMs, AI agents, and retrieval-augmented generation (RAG) workflows.
The Book on Agentic Analytics
Explores the foundations of agentic data architecture, where AI agents autonomously discover, query, and analyze data.
The Book on Data, Data Engineering, Data Analytics, and Agentic AI - Volume 1
A complete guide to modern data systems, data engineering, analytics, and AI.
The Book on Data, Data Engineering, Data Analytics, and Agentic AI - Volume 2
A complete guide to SQL analytics, BI, and agentic AI for modern data platforms.
The Book on Using Apache Iceberg with Python
A hands-on guide to working with Apache Iceberg using Python tools like PyIceberg, PySpark, and other Python-based engines.
Using AI Agents for Data Engineering and Data Analysis
A practical guide to leveraging AI agents for automating data engineering pipelines and performing intelligent data analysis.
Apache Iceberg: The Definitive Guide
O'Reilly Media
A comprehensive guide to Apache Iceberg and modern lakehouse architecture, covering table format internals, schema evolution, partitioning, and integration with major query engines.
Apache Polaris: The Definitive Guide
O'Reilly Media
A guide to open catalogs for Apache Iceberg lakehouses, covering Polaris catalog architecture, configuration, and governance.
Architecting an Apache Iceberg Lakehouse
Manning Publications
Architecture patterns and best practices for building production-grade, Iceberg-based data platforms from the ground up.
Apache Iceberg for Agentic AI: Connecting Structured Enterprise
Explores how to connect structured enterprise data in Apache Iceberg lakehouses to agentic AI systems.
Dremio and the Semantic Layer
The journey to providing meaning and context for AI with Dremio's semantic layer.
Enabling Agentic Analytics with Apache Iceberg and Dremio
A practical guide to building AI-ready lakehouse systems using Apache Iceberg and Dremio for agentic analytics workflows.
The 2026 Guide to Lakehouses, Apache Iceberg and Agentic AI
A comprehensive guide covering the convergence of lakehouse architecture, Apache Iceberg, and the rise of agentic AI systems.
The AI Lakehouse: Architecting Data Platforms for AI
Explores how to architect data lakehouse platforms specifically designed to serve AI and machine learning workloads.
The Book on Apache Polaris
Building the open data lakehouse with the industry standard Iceberg REST catalog.
The Lakehouse Built for Everyone
From laptop prototypes to enterprise-scale agentic AI with Apache Iceberg and Dremio.
The No Lock-in Apache Iceberg Lakehouse with Agentic Analytics
A practical guide to building a portable Apache Iceberg lakehouse with open catalogs, agentic analytics, and AI-ready data platforms while avoiding vendor lock-in.
The Open Source Lakehouse: Architecting the Decoupled Analytical Foundation
Covers building a fully decoupled lakehouse using open source technologies, emphasizing modularity and vendor independence.
Building Knowledge Systems for AI: Graphs, RAG, Memory, and Context
A deep dive into building robust knowledge systems for AI using knowledge graphs, RAG, memory architectures, and context management.
Constructing Context and Semantics for AI Agents
A practical guide to embeddings, knowledge graphs, memory systems, RAG, evaluation, and production agent architectures.
AI and Agents for Normal People
A practical guide to using AI tools for everyday tasks, covering Gemini, NotebookLM, ChatGPT, Claude, and local agent workflows without technical jargon.
AI Application Architecture: Patterns for Building Intelligent Systems
Covers architectural patterns for building intelligent applications, from inference pipelines to multi-agent orchestration.
Being Productive with Open Models
A practical guide to using open models with Opencode, PI, and Hermes for AI-assisted development.
Evaluating AI Systems: Testing LLMs, RAG, and Agents
A guide to properly testing and evaluating AI systems, including benchmarking strategies for LLMs, RAG pipelines, and agents.
Governing AI Systems
A guide to AI governance frameworks, covering risk management, compliance, ethics, and organizational oversight of AI systems.
Hands-On Agentic Engineering: A Practical Guide to Building Multi-Agent Systems
A practical guide to building multi-agent systems with Apache Iceberg.
The Agentic Enterprise: Deploying AI Agents Across the Modern Organization
A guide to deploying AI agents across enterprise functions, covering strategy, governance, and organizational adoption.
Shipping AI: From Prototype to Production Systems
Covers the full lifecycle of taking AI systems from prototype to production, including deployment, scaling, and monitoring.
The 2026 Guide to AI-Assisted Development
Covers prompt engineering, AI coding assistants, and agent-driven development workflows for modern software engineers.
The AI Engineering Handbook
A full-stack reference for building AI systems, covering LLMs, embeddings, agents, RAG, and production deployment patterns.
The Economics of AI: Cost, Latency, and Infrastructure Tradeoffs
Analyzes the cost structures of AI systems and how to optimize spending across compute, latency, and infrastructure.
The Economics of Labor in the AI Era
Examines how the AI era is disrupting the labor market and explores paths for adaptation and the future of work.
