Notes, experiments, and playbooks on building production LLM applications, orchestrating autonomous agents, and optimizing software delivery. Written for developers and practitioners.
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Learn how to architect, build, and deploy production-ready AI agents using the Model Context Protocol (MCP). Covers state management, security, and scalability.
A complete technical reference and implementation guide to observing agentic workflows, tracking LLM token costs, logging reasoning trajectories, tracing nested tool calls, and monitoring system metrics in production.
An architectural guide to designing scalable, asynchronous AI agents using Apache Kafka to handle long-running model inferences, tool executions, and backpressure in production.
Chatbots are dead. Welcome to the era of Agentic AI. Explore how enterprises are deploying autonomous agents for complex workflows, the architectural shift required, and the rise of specialized inference models like Nemotron 3.5 Lightning.
Global AI inference spending hit $23.3 billion in 2026, officially surpassing model training. Explore what this structural shift means for AI platform engineers, IaaS growth, and managing production token costs.
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.