AI Engineering

Building AI products, the decisions behind them, and the foundations they stand on.

AI Products

From demo to product, UX for non-deterministic systems, where the moat really is, and shipping your first AI feature.

AI Decisions

The business and engineering calls: should this use AI, choosing a model, build vs buy vs fine-tune, and the real cost of an AI feature.

LLMs & AI Engineering

Prompting, RAG, agents, fine-tuning, evaluation, and cost control for AI in production.

Deep Learning

The foundations of modern AI: neural networks, CNNs, RNNs, LSTMs, and Transformers from first principles.

Machine Learning

Core ML concepts and interview prep - the groundwork under everything AI.

AI & GTM Systems

AI for RevOps, AI-personalized landing pages, lead routing, data hygiene, attribution, and buy vs build.

Python

Default dictionaries, lambda functions, map, and the everyday tools behind the work.

Big Data

Jupyter on EC2, Kafka, Hadoop - the data plumbing that feeds AI systems.