Scope the task
Define a coding task inside a repository tightly enough that Codex knows what is in and out of bounds.
Partners and press
Overview
Codex can change a lot of code quickly. This course teaches you to check it.
Get Started with Codex is a free, self-paced 80-minute course for software engineers, and it opens OpenAI Academy’s Codex pathway. You scope a coding task in a repository, verify Codex’s changes and give reviewers clear evidence that they work. Finishing all three Codex courses earns a pathway certificate of completion, which OpenAI says is not a certification.
5Modules
10–20Questions
80Minutes
7Roles
What it covers
Learn all the way down.
Learn all the way down.
Perform when it matters.
Verify the changes
Check what Codex changed, rather than trusting the summary it gives you of its own work.
Give reviewers evidence
Show the people reviewing your pull request clear evidence that the change does what it should.
Start the Codex pathway
Earn the first course badge toward the Codex pathway certificate of completion.
Course outline
Give Codex a task it can finish
Give Codex a task it can finish
and proof a reviewer can trust.
We design this course ourselves. OpenAI issues the credential, and LUNARTECH is independent of OpenAI.
Codex reads a codebase, edits files and runs commands to carry out a task you describe. Knowing how it works and where it gets stuck lets you give it jobs it can finish, and spot the ones it cannot.
- How a coding agent works through a task
- What it can see, change and run
- Where it works well and where it stalls
- Your role: owner of the change
- Reading what it reports back
You build A short note on one small task in your repository that suits an agent, and why.
A task with no edges invites a sprawling change. You define the goal, the files and behavior in scope, the ones out of scope, and the checks that will show the work is finished.
- Writing the goal as observable behavior
- Naming the files and areas in scope
- Stating what must not change
- Sizing a task so one change covers it
- Splitting a large job into separate tasks
- Adding acceptance criteria
You build A scoped task description for a real change in your own repository.
An agent does better in a repository it can build and test. You make setup, test and lint commands clear and repeatable, and write down the conventions the agent should follow, for example in an AGENTS.md file.
- Making the build and tests run from a clean checkout
- Documenting the commands the agent should run
- Writing guidance files such as AGENTS.md
- Recording conventions and no-go areas
- Fast checks an agent can run often
You build Repository guidance and one-command checks that Codex can follow.
A summary is the agent’s account of its own work, not proof. You read the diff, run the tests yourself, look for changes beyond the task and confirm the behavior directly before anything moves on.
- Reading the diff line by line
- Running tests and checks yourself
- Finding changes outside the task’s scope
- Testing behavior the existing tests miss
- Spotting invented APIs and quiet deletions
- Sending the work back with a sharper instruction
You build A verification checklist, used on a real Codex change.
Reviewers should not have to take your word for a change. You write a pull request that states what changed and why, shows test output and before-and-after behavior, and says plainly what was not checked.
- Writing a pull request description that reads fast
- Attaching test results and command output
- Showing before-and-after behavior
- Stating what you did not verify
- Disclosing which parts the agent wrote
- Answering review comments with follow-up tasks
You build A pull request for a Codex-made change, with its evidence attached.
Issued by
Certifying body · Independent of LUNARTECH
OpenAI
A certification in early pilot, and free Academy courses across Foundations, Codex and the API. OpenAI says its Academy badges and certificates of completion are not certifications, and don’t guarantee eligibility for one. Availability is still changing, so check OpenAI’s own pages before planning around any of these.
How you get there
Top-tier roles go to people who can do the work.
Top-tier roles go to people who can do the work.
Here’s how you get there.
Know where you start.
Codex pathway level. Check OpenAI’s official page for what it expects before you begin.
Work through the course.
Five modules, designed by LUNARTECH, at your own pace.
Earn it with OpenAI.
OpenAI issues the credential, so you earn it directly with them.
Support
Support at every stage.
Support at every stage.
You won’t be working through this alone.
Before you start
Try it first.
A 3-day free trial opens a selection of the content. Your card is only charged once it ends.
While you learn
Mentors within reach.
Stuck on a concept? Reach out to a mentor whenever you need help.
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One-on-one sessions.
On the yearly plan, one-on-one sessions give you dedicated support.
Any time
A team behind you.
Write to info@lunartech.ai at any point, from your trial onwards. If your employer is funding you, we’ll set it up with them directly.
All the way through
A schedule that fits around your life.
Your own paceFrom anywhereAt any hour
After the last lesson
Stay in the network.
Your alumni network stays with you: ongoing support, opportunities and industry insight.
Career support
Career support, past the last lesson. Coaching, a sharper resume, real interview preparation and the people to know.
Career direction
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Strong portfolio
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Resume and profile
Personalized refinement, so what you send says what you can actually do.
Interview preparation
Preparation for the questions that decide it, so you walk in ready.
Network and search
Connections with industry leaders, and an alumni network that stays with you.
Reviews
Real stories from the community.
LUNARTECH Academy has been the most empowering learning experience of my life, giving me a clear, structured path from the absolute basics to building real-world AI systems with confidence.
Your page is fantastic. As a bachelor’s student in Data Science now accepted for a master’s at UConn, your work has been a real source of motivation.
The programme’s clear, bite-sized content and practical projects dramatically improved my speed from fuzzy idea to MVP and my ability to communicate AI value. I followed the system, and it works.
I really appreciate your teaching style and the way you break down complex topics. It has been incredibly helpful.
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As a Data Science graduate, I want to thank you for the effort you put into making videos to support growing data scientists.
I’ve been following your work since taking your machine learning course, and I’m impressed by your practical approach to applying AI.
Why choose us
Built around how you actually learn.
One standard behind every course, from the first lesson to long after the last.
Hands-on practice
Apply every idea to real problems, so it becomes something you have used, not only seen.
Industry-aligned curriculum
We keep courses current with the tools, techniques and skills the field asks for.
Flexible learning
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Certificate of completion
Finish the course and earn a certificate that shows what you have learned.
Focus on your success
Personalized learning plans and support structures carry you through the hard parts.
Lifetime alumni network
Stay connected after you finish, with ongoing support, opportunities and industry insight.
Your certificate
It doesn’t raise its voice. Neither will you.
Finish a LUNARTECH course and its certificate is issued in your name, under our signature. OpenAI’s credential comes from OpenAI.
Certificate of completion
Your Name
Get Started with Codex course
LUNARTECH RISE Academy
Pricing
This course comes with the membership.
This course comes with the membership.
So does everything else.
One membership opens every course, certification, workshop and masterclass in the Academy. Every plan starts with a 3-day free trial. OpenAI issues the credential.
3 days free, then $29.97 a month. Your card is only charged once the trial ends.
Included in every plan
- Every course in the Academy
- Every certification course
- Workshops and masterclasses
- A certificate of completion
- A 3-day free trial
- Learning at your own pace
- The lifetime alumni network
- Upgrades at any time
In practice
Seven roles.
Seven roles.
One credential across them all.
No single job owns it. Here’s where each role leans hardest, and where its work ends up.
- 01Scoping
- 02Verifying
- 03Evidence
-
A tight task gets a tight diff. Evidence makes a reviewer’s job faster.
Scoping, Verifying, Evidence
Software teams, Startups
-
Review habits matter more with AI-written code. Make evidence part of every change.
Verifying, Evidence
Software teams, Open source
-
A well-scoped task stays inside one service. Run the tests before you trust the change.
Scoping, Verifying
Software teams
-
Evidence is a test result, not a claim of success. Verification is where Codex output earns trust.
Verifying, Evidence
Software teams
-
A pull request needs proof it works, whoever wrote it. Codex changes should arrive with that proof.
Verifying, Evidence
Open source
-
Codex can take well-defined tickets off a small team. Scope them tightly so the diffs stay readable.
Scoping, Evidence
Startups
-
A fix for a live system needs evidence before it ships. Verification covers what the change might break.
Verifying, Evidence
Software teams
- Software teams
- Open source
- Startups
Software Engineer
A tight task gets a tight diff. Evidence makes a reviewer’s job faster.
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The field
Anyone can use AI.
Anyone can use AI.
Few can engineer it. This is where that starts.
+340%growth in open roles requiring AI skills
Roles and pay
~35,000 open roles right now
Open roles: Built In, Greenhouse, LinkedIn.
Typical salaries: Glassdoor, Levels.fyi, Payscale, Indeed, Ravio, JobRise, U.S. BLS. Military: 2026 U.S. basic pay, drone officers with aviation incentive pay.
Updated November 2026.
FAQ
Frequently asked questions.
Need help? These answers cover most of what people ask before they start.
No. OpenAI issues it. LUNARTECH is independent of OpenAI, and its names and marks belong to it. When you finish a course of ours, you earn a LUNARTECH certificate of completion for that course.
No. We design this course ourselves, around what the credential covers. OpenAI has no part in it, and you still earn the credential directly with OpenAI.
10–20 questions, 80 minutes, online, self-paced. The passing score is 80% on the assessment.
We last reviewed it on 5 November 2026, from excerpts of OpenAI’s official pages, because its site doesn’t accept automated readers. Details change, so check the official page before you book.
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The course
Build the skills behind Get Started with Codex.
Learn to scope coding tasks for Codex and prove the result. Start with a free trial, or enroll in a plan and work through the course at your own pace. OpenAI issues the credential.
LUNARTECH is independent of the vendors and certifying bodies listed here. Their names, exam titles and marks belong to them, exams are run by them, and credentials are issued by them. Reviewed 5 November 2026. Catalogues change often, so confirm the details on the official page before you book.
