Blog

Thoughts on Python, Agentic Systems, AI Projects, and Web Development.

• Lesson 1: LLMs Are Not Functions (And Why That Changes Everything)
  2025-12-14

  My first real AI engineering lesson: large language models are not functions. They're probabilistic generators — and unless you constrain them, they will break your system.

• Vector Embeddings: The AI Superpower Every Developer Should Understand
  2025-12-11

  Embeddings are the quiet engine behind RAG, search, similarity, memory, clustering, and half the AI tools you use. Here's how they really work.

• How LLMs Actually Work: The Mental Model Every AI Developer Needs
  2025-12-11

  Forget the mystical hype. Here's a blunt, developer-friendly explanation of how transformers think, plan, and hallucinate.

• How to Architect a Real AI Application in 2025
  2025-12-11

  Everyone builds AI demos. Here's how to build production-grade AI systems with layers, tools, memory, observability, and fault tolerance.

• AI Agents Under the Hood: What They Actually Do (Not the Hype Version)
  2025-12-11

  Everyone talks about AI agents. Few understand how they work. Here's a developer-first breakdown of tools, loops, memory, state, and why most agents explode at 2am.

• Making Virtual Environments Invisible: How I Stopped Fighting Python
  2025-11-29

  Switching venvs is annoying. Here’s how I made it automatic, effortless, and impossible to mess up — even across multiple projects.

• The Birth of Bob + Chad: My Local Agentic Coding Environment
  2025-11-29

  I built a self-improving AI pair-programming system that runs locally, fixes its own code, and evolves over time.

• GhostFrog: Building a Data-Driven eBay Arbitrage Engine
  2025-11-27

  I built a full pipeline that scrapes eBay listings, classifies products, calculates ROI, and sends alerts.