Working primer
Working notes from the practice.
Concepts, not case studies. A primer on how production AI is actually built — agent architecture, multi-model orchestration, sovereign deployment, and the evaluation and governance layer that decides whether the system survives.
- № 01What Is an AI Agent? A Technical PrimerThe word agent has been overloaded by a year of marketing. A precise definition, and the architectural decisions that decide whether an agent survives contact with a real workflow.30 Apr 20267 min ↗
- № 02Multi-Model Orchestration — How Production AI Stacks Actually WorkAlmost no serious production AI system today uses a single model. This is why, what the orchestration layer does, and the engineering pieces that turn a hybrid stack from a slide into something that runs.30 Apr 20268 min ↗
- № 03Sovereign and Hybrid Deployment — Building AI Inside the PerimeterFor regulated industries, the constraint that decides everything else is where the data sits. What changes when 'send it to the API' stops being an option, and what a serious in-perimeter or sovereign deployment actually involves.30 Apr 20268 min ↗
- № 04Evaluation, Quality and Governance — The Layer That Decides Whether Your AI Survives ProductionHallucination control, deterministic fallback, structured outputs, audit trails, and continuous evaluation are no longer features attached at the end of an AI project. They are the project.30 Apr 20268 min ↗