For people who need to get it right.
AI can write code fast.
That's not the problem.
The problem is knowing what was actually built, whether it matches what you asked for, and how to stay in control as complexity grows.
Staying on Track is a hands-on course that teaches a simple, repeatable way to work with AI coding agents—without drifting scope, silent regressions, or blind trust.
You don't need to know how to program.
You do need to know how to think clearly about what you want built—and how to hold an AI accountable to it.
This course is for people who use AI to build real things—and care about correctness, clarity, and accountability.
It's for founders, product builders, operators, and engineers who:
need changes to do exactly what was intended
want to understand what an AI coding agent actually did
care about regressions, edge cases, and auditability
are comfortable taking responsibility for decisions, even when AI is involved
You don't need a computer science background.
You do need a willingness to think clearly, state intent explicitly, and review results instead of trusting them blindly.
If your work has consequences—technical, financial, or reputational—this course was designed for you.
This course is not for people looking for shortcuts or magic prompts.
It's not a fit if you:
want AI to code without review or structure
are primarily interested in speed over correctness
don't want to read review output or make judgment calls
expect AI to replace responsibility rather than support it
If you're looking for hype, novelty, or a way to avoid thinking about what you're building, you'll likely find this process frustrating.
That's intentional.
No exceptions. No shortcuts.
Instead of “prompt and pray,” you work in four explicit steps that create clarity before code is written and certainty after it runs.
DEFINE
You state what must change before any code is touched.
You write a short declaration that includes the change request, how you'll know it's done, and which files are expected to change. This becomes the contract.
IMPLEMENT
You give Claude Code a precise, scoped instruction.
Claude Code implements the change. You run it. You confirm it works. No interpretation yet. Just execution.
REVIEW
The Chief Engineer runs independently.
It checks whether the implementation actually matches what was declared—first mechanically, then analytically across six dimensions: scope alignment, regressions, edge cases, contracts, tests, and rollback safety. This step does not negotiate. It reports.
DECIDE
You read the review and decide what happens next.
Open the CE review artifact and read what the process observed. Verify the program runs. Then decide: issue a new DEFINE to open the next cycle, or stop. The loop closes when you choose—APPROVED or BLOCKED, the cycle is complete.
Write a clear DEFINE document that prevents drift
Direct Claude Code with precise, bounded prompts
Run the Chief Engineer review and interpret its verdict
Understand what a BLOCKED result means—and how to resolve it
Commit code and review artifacts as a single, auditable unit
Distinguish human judgment from automated gates—and use both intentionally
A proven, repeatable approach for producing production-ready code with an AI assistant as the implementer—while you remain in control of intent, scope, and quality.
You'll build and iterate on a real command-line contact manager through two complete guided cycles. Then the scaffolding comes off—an optional third cycle for running the loop on your own terms.
01
The First Build
Build a CLI contact manager from scratch.
Three fields. Three operations. One complete pass through DEFINE, IMPLEMENT, REVIEW, DECIDE. The loop runs end to end for the first time.
02
The Iteration
Improve the menu and user-facing prompts.
The contact manager works. This cycle runs the same governance loop around a bounded improvement—better prompts, cleaner output, more predictable flow. Same process, different change.
03
Independent Practice
Run the loop on your own terms. (Bonus — optional.)
No guidance, no evaluation. The review records from Cycles 1 and 2 are in your workspace. Choose a direction—extend the project, change something, or start something new—and run the process yourself.
You only need one thing to get started:
A GitHub account (required)
A GitHub username is required because the course materials are delivered as a private repository that is pushed directly to your account. This repo becomes your working environment for the entire course—code, commit history, and Chief Engineer review artifacts included.
If you don't already have a GitHub account, you can create one for free in a few minutes.
Full course · Immediate access · Private GitHub repository
$99
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