Builder Methods library
The video library.
Short videos, ride-alongs, and tutorials on building with AI.
AI costs
How AI pricing is structured, tokens versus subscriptions, how I mix models and plans, and the progression I recommend as your usage grows.
GitHub repos, explained
What a repo is, why syncing to GitHub is worth it, the three words you need (commit, push, pull), and the one thing that must never go in a repo.
Agentic apps & harnesses
How to make sense of the AI apps out there: chat apps vs file-based apps, UIs vs terminals, agent bots, and the three ways an agent reaches your other tools.
File types for AI
Markdown, JSON, HTML, YAML, and scripts: what each file type you saw in the course is for, and why none of them belongs to a company.
Agent employee patterns
The third pattern lesson names the course's biggest idea, the agent employee, assembles the whole AI-native operating model, and hands the loop over to you.
Async interactive agents
Turn the daily report into a two-way command surface: the agent recommends and leaves you checkboxes, you tick or scribble, and the next run carries it out.
Automate agent tasks
The same three skills, run by a scheduler instead of by you: hourly intake, a daily report, a weekly report, and a week that runs while you do nothing.
HTML sales dashboard
A visual board that reads the repo: one HTML page, no app, no database, no server, kept fresh by a skill that other skills call.
Daily report skill
The fix for sifting: two report skills that surface what needs you, plus the first skill that calls another skill, then the rest of the week's inbound.
Leads intake skill
Build the intake skill that files every inbound item, then run it on two days of forms, emails, voicemails, and a call transcript.
Sales Pipeline Repo
A CRM with no app, no database, and no server, from one prompt: six numbered stage folders, eight prospects filed into their stages from a seed doc, and an AGENTS.md that tells any agent how the pipeline works.
Training AI with taste
The second pattern lesson makes the course-wide voice thread explicit: two mechanisms, a self-check, where the training lives, and the kit for doing it on your own work.
AI Sales Pipeline
A quick tour of the third example, a managed IT provider with founder-led sales, and the biggest build in the course: a sales assistant with a real job.
MCP & Agent Skills
The last mile: add a push step so the finished issue lands in your email platform as a draft, then swap platforms and watch nothing in the skill change.
Voice training for AI
Point the agent at nine finished issues to build a voice doc, seed a slop list by hand, wire both into the skill with a self-check, and run it again.
Content drafting skill
We build a newsletter drafting skill that interviews you before it writes, run it on a raw voice memo, and read a draft that has the right shape and none of the voice.
Content development repo
An empty folder becomes the working home for the newsletter: nine finished issues, raw idea captures, brand docs, and an AGENTS.md that explains it all.
Agent Skills Patterns
The first pattern lesson names what you just watched: the loop, where skills live, the anatomy of a skill, the interview convention, and the three improvement moves.
Grow your skills library
Kill the modules nobody used, promote the sections you kept asking for, and run the skill clean: real usage rewrote the design in one pass.
Friction-driven iterations
We run the modular skill on two new prospects and let it hit the limits of the library on camera, patching each run by hand and noticing what keeps coming up.