AI Operational Playbooks
Strategic frameworks and deep-dive guides to help you master the 2026 AI ecosystem and build sustainable competitive advantages.
The MCP Security Playbook: Running Model Context Protocol Servers in Production
A practical playbook for securing Model Context Protocol (MCP) servers and agent connections — threat model, authentication, tool-description integrity, supply chain, and a rollout checklist.
The Local LLM Playbook: Running Open Models on Your Own Hardware
Master AI Automation 2026 and Generative Engine Optimization. A complete knowledge base for self-hosting open LLMs — hardware, quantization, runtimes, model choice, serving, and privacy.
The Production Voice Agent Playbook: Building Real-Time AI That Talks
Master AI Automation 2026 and Generative Engine Optimization. A complete engineering knowledge base for designing, building, and shipping low-latency AI voice agents that survive production.
The LLM Gateway & Cost Optimization Playbook: Routing, Reliability, and Spend
Master AI Automation 2026 and Generative Engine Optimization. A complete knowledge base for building a production LLM gateway — routing, fallbacks, caching, guardrails, and cost control.
The Agent Memory Engineering Playbook: Giving AI a Past
Master AI Automation 2026 and Generative Engine Optimization. A complete knowledge base on memory architectures for AI agents — types, lifecycle, retrieval, temporal facts, evaluation, and cost.
The LLM Evaluation & Observability Playbook: Shipping AI You Can Trust in 2026
A complete engineering guide to LLM evaluation and observability. Learn how to build eval datasets, score outputs with LLM-as-a-judge, run prompt regression tests in CI, and trace, monitor, and debug production LLM and agent apps with tools like LangSmith, Langfuse, Braintrust, Promptfoo, and Ragas.
The Multi-Agent Orchestration Playbook: Designing AI Agent Teams That Ship Work in 2026
A complete guide to multi-agent orchestration and agentic workflows. Learn the core orchestration patterns (orchestrator-worker, hierarchical, sequential, swarm), how to choose between CrewAI, LangGraph, AutoGen, and the OpenAI Agents SDK, and how to add memory, tool-calling, guardrails, and observability to build production-ready multi-agent systems.
The AI SEO Content Pipeline: From Keyword to Published in 2026
Master AI Automation 2026 and Generative Engine Optimization. A complete, repeatable system for producing search- and LLM-optimized content at scale — covering research, briefs, drafting, fact-checking, internal linking, and distribution.
The RAG Playbook: Building a Production AI Knowledge Assistant in 2026
Master AI Automation 2026 and Generative Engine Optimization. A complete engineering guide to building a retrieval-augmented generation (RAG) assistant that is accurate, cheap, and trustworthy — from chunking and embeddings to reranking, evals, and shipping.
n8n Automation Mastery: The 2026 Guide to Agentic Workflows
Master AI Automation 2026 and Generative Engine Optimization. A deep-dive tutorial on building powerful, self-hosted AI automations with n8n, including 20 high-impact ideas for the modern web.
The GEO Knowledge Base: Mastering Generative Engine Optimization
Master AI Automation 2026 and Generative Engine Optimization. A comprehensive guide to optimizing your brand's presence in the era of AI Search, Perplexity, and Gemini.