Building AI Agents with LLMs and Custom ML Models: The Blueprint for Enterprise-Ready Autonomy

Introduction: The Rise of Hybrid AI Agents AI agents are rapidly emerging as the next abstraction layer for enterprise artificial intelligence. Rather than interacting with models directly, organizations are beginning to deploy systems that can perceive inputs, reason over context, and take action with limited human intervention. Large language models have accelerated this shift dramatically,... Continue Reading →

January 21, 2026 0

The Transformer Architecture: Foundations, Engineering Trade-Offs, and Real-World Deployment at Scale

I know that many resources explain this architecture, including the pivotal paper Attention Is All You Need. I wanted to write this to cement the concepts in my mind. This architecture is what is driving the current AI revolution, so it is essential to have a good grasp of the ideas. Since its introduction in... Continue Reading →

January 16, 2026 0

The Classification Task: From Data to Decisions

In the first article, I focused on how a data science repository is structured and why that structure supports MLOps practices like repeatability, traceability, and safe iteration. In this follow-on post, I want to zoom in on the machine learning problem itself: the classification task implemented in the repository. The goal here is not to... Continue Reading →

January 12, 2026 0

AI Governance and AI Observability in the Microsoft Stack: Building AI You Can Trust

Artificial intelligence has entered a phase where models are no longer the center of gravity, behaviors are. We’re deploying systems that reason, retrieve, act, and adapt in real time. They generate content, make decisions, and increasingly operate as semi‑autonomous agents woven into everyday business processes. This shift has opened extraordinary opportunities, but it has also... Continue Reading →

January 9, 2026 0