John Coltrane's A Love Supreme moves through four movements — Acknowledgement, Resolution, Pursuit, and Psalm — each one a phase in a single sustained act of devotion. The AI Edge borrows that structure because learning has the same shape. You begin by watching and listening, acknowledging what others have understood. You move to reading, resolving to engage deeply with the work. You pursue your own making, building things that ship. And eventually you arrive at the Psalm — the moment when the practice has shaped you enough that a credential is the natural next step.
"Nothing is a mistake. There's no win and no fail. There's only MAKE."
— Sister Corita Kent, Rule 6 (popularized by John Cage)
I. Watch
Listen · absorb
Short, curated viewing. Talks and videos that resolved something for drC — a concept, a debate, a way of seeing the field. Not a feed. Not exhaustive. Entry points.
drC's picks
Andrej Karpathy — "How to jumpstart your own learning." Watch this first.
3Blue1Brown — Visual math for transformers, attention, neural nets. Chapters 5–7.
Matthew Berman — AI tech and interviews with the movers and shakers. Dylan Patel on the state of the GPU stack.
Dwarkesh Patel — Long-form interviews with top researchers. Dense. Re-listen with the notebook open.
The Scaling Hypothesis — Gary Marcus vs. Dario Amodei. The defining debate in AI right now.
See the full watch list →II. Read
Deepen · refine
Short, curated reading. Papers, essays, and posts worth the time. Each one earns its place — drC reads it, marks it up, and tells you why it matters. Click any title to go to the source.
drC's picks
The Batch — Andrew Ng's weekly newsletter. Clearest signal in AI.
One Useful Thing — Ethan Mollick. Applied AI for normal humans.
Import AI — Jack Clark. Research and policy. Dense.
Towards Data Science — Medium publication. Quality varies; the best pieces are excellent.
arXiv — Papers feel dense because they are. Search "AI" or specific topics. Use the abstract-to-Claude trick.
See the full read list →III. Make
Build · ship · learn
Pick something you care about, or something you want to learn. Then make it. Watch and read are inputs. Make is where the learning actually happens.
drC's approach
Pick a medium — code, data, research, IoT, or media. Whatever you can ship.
Use AI as a collaborator — Claude drafts, debugs, explains. You steer.
Push it to GitHub — code, design files, writing, all of it. README and screenshot.
↻ Loop when stuck — describe the problem to Claude, let it ask the clarifying questions.
See the full MAKE guide →IV. The AI Edge course covering guardrails for agentic AI and ontologies built around the foundations of the Claude Certified Architect (CCA) exam will be launched in September 2026. At completion you’ll exit with a portfolio that proves you can build production AI systems — and a clear pathway to CCA certification. To get notifications about the course, click the link below.