Get the AI Edge

Get up to speed — build a foundation — obtain professional credentials

Whether you're a student trying to leverage AI in your studies, a marketing specialist looking to use AI to analyze marketing trends or an engineer preparing for the CCA exam, the approach is the same — watch/listen , read and then MAKE something.

"Nothing is a mistake. There's no win and no fail. There's only MAKE."
— Sister Corita Kent, Rule 6 (popularized by John Cage)

Nothing is a mistake. There is no win and no fail. There is only MAKE !
Sister Corita Kent, Rule 6 (popularized by John Cage)

Watch Read MAKE

Watch. Read. MAKE. A field guide for anyone — student, professional, engineer — getting real with AI.

The pattern that actually works:

  • Watch the right podcasts and channels. Karpathy, 3Blue1Brown, The Cognitive Revolution.

  • Read what shapes real thinking. Medium curators, newsletters, key arXiv papers run through Claude for translation.

  • MAKE something every week. Even something small. Ugly v1s on GitHub beat polished plans.

See the Field Guide

Seven Steps

Every major skill area has foundations. Pianists drill Hannon and Czerny. Basketball players learn to go left and go right. AI coding has its own foundations — and most people skip them and wonder why nothing works.

The seven foundations, in order:

  1. CLI basics — cls, ls, cd, mkdir, glob, grep

  2. Python on the command line — versions matter

  3. Virtual environments — uv is taking over from venv and pip

  4. One IDE done well — Codex, VS Code with Jupyter, JetBrains

  5. API key management — .env and .gitignore

  6. GitHub — the repo is the new résumé

  7. Local LLMs with Ollama — compare with the frontier models

See the Seven Steps Guide

Build to Certify

Eight weeks of structured work that maps directly to the five domains of the Claude Certified Architect exam. Anthropic's professional credential. Cohort launches June 15, 2026.

What you'll build:

  • Agentic architectures with multi-step reasoning loops

  • Tool design following the MCP specification

  • Production prompt engineering with structured output validation

  • Context management strategies — RAG, caching, summarization

  • Claude Code workflows for real CI/CD pipelines

Exits with a GitHub portfolio that qualifies you for exam registration.

See the Curriculum

About drC

Frank Coyle (drC) received a PhD in CS from SMU, an MS in CS from Georgia Tech, and an MS from Emory where he did graduate work in neuroscience. He teaches generative AI at UC Berkeley and retired from a 32-year career at SMU, where he was recipient of numerous teaching awards. He's also taught district attorneys, formerly incarcerated students through Columbia's Justice Thru Code program, and is a visiting Professor at the University of Bologna.

The AI Edge applies what he has learned after more than 30 years of teaching — an approach to give individuals an AI edge in whatever field they are in. Mastery does not require genius. It requires devoting time and realizing that “Nothing is a mistake” — only MAKE.