Notes, experiments, and playbooks on building production LLM applications, orchestrating autonomous agents, and optimizing software delivery. Written for developers and practitioners.
Learn how to architect, build, and deploy production-ready AI agents using the Model Context Protocol (MCP). Covers state management, security, and scalability.
A definitive technical guide to AI agents: how they differ from standard LLMs, their core architectural components (memory, planning, tools), and how they execute autonomous workflows.
A definitive technical guide to Context Engineering: how it differs from prompt engineering, the architecture of the context window, and how to programmatically structure data for reliable LLM inference.
A definitive technical guide to Retrieval-Augmented Generation (RAG): how it solves LLM hallucinations, the core architecture of vector databases and embeddings, and why it beats fine-tuning for enterprise data.
A practical guide to the four-phase Agent Development Lifecycle. Learn how leading engineering teams ship AI agents reliably and repeatedly.
AI Engineer & Systems Practitioner
Building LLM products, researching multi-agent orchestration, and setting up secure deployment pipelines. Formerly writing DevOps playbooks, now mapping the production AI stack.
Learn more about my experiments arrow_forwardEverything published here is tested locally and run against real applications. We avoid corporate jargon, consultant hand-waving, and empty marketing hype.
Designing, optimizing, and operating reliable AI pipelines in production. Context truncation, pricing model controls, hybrid search architectures.
Orchestrating autonomous decision-making loops and workflows. Complex state machines, multi-agent frameworks, LangGraph orchestration.
Practical implementations, fine-tuning methodologies, model evaluation frameworks, and speech-to-text models on Azure and cloud environments.
Accelerating local development velocity, command-line interfaces, automated CI/CD pipelines, container optimizations, and secret scanners.
We send out weekly breakdowns of RAG implementations, agent logic flows, Docker optimizations, and code checklists. Straight code snippets, zero fluff.