Vibe-coding Professional Developer (Agentic Development)
Direct AI coding agents, then test their work.
Use AI coding agents to build real software, and stay the person who decides what ships.
WhatsApp ACADEMY to +234 817 188 5917
Is this course for you?
- Newcomers who want to build working software with AI agents from day one
- Working developers adopting agentic workflows who want a review-and-test discipline, not just speed
- Product managers, founders and analysts who want to build internal tools themselves
- You are already in the role and want AI agents in your workflow without shipping bugs or leaks
What you need
- A laptop with at least 8GB of RAM and a modern browser
- Reliable internet and data. Agents need a connection
- No prior coding needed, but you must be willing to read code line by line
- A paid plan for one AI coding tool helps from week 3. Tool plans are optional and not included
Week by week
- Week 1
Set up your agent workspace
- Install an agentic coding tool, Git and a code editor, and connect them to GitHub
- Ship a first small change end to end: branch, agent edit, review, commit, pull request
- Read a codebase with the agent’s help and explain its structure back in plain words
- Week 2
Scope a task for an agent
- Scope a feature into agent-sized tasks, each with written acceptance criteria
- Write a project context file (for example AGENTS.md or CLAUDE.md) with the rules the agent must follow
- Decide which tasks to hand to an agent and which to do yourself
- Week 3
Prompt and manage context
- Write prompts that name the files, examples and constraints the agent needs
- Manage the agent’s context: start fresh sessions, summarise, and keep plans in files
- Compare two agents on the same task and record which one you would trust with it
- Week 4
Review every diff
- Review each diff line by line before accepting it, and reject changes you cannot explain
- Spot the common agent mistakes: invented packages, deleted tests, silent scope creep
- Request changes from the agent with a precise review comment, as you would with a colleague
- Week 5
Write tests the agent must pass
- Write failing tests first, then direct the agent to make them pass without editing the tests
- Add browser tests with Playwright for the user journeys that matter
- Run the tests automatically on every pull request with GitHub Actions
- Week 6
Debug agent output
- Debug a broken feature: reproduce it, read the error and stack trace, and find the cause
- Use Git history to find which agent change introduced a bug, then roll it back
- Direct the agent to explain its own code, and check the explanation against what runs
- Week 7
Keep secrets and users safe
- Keep API keys and secrets in environment variables, never in code, prompts or screenshots
- Scan your repository for leaked secrets and rotate any key that has been exposed
- Check login, access control and payment verification by hand, because agents often get them wrong
- Audit dependencies and remove packages the app does not need
- Week 8
Ship to production
- Deploy to Vercel with preview builds for every pull request
- Set production environment variables, a custom domain and error monitoring
- Roll back a bad release on purpose, to prove you can
- Present your capstone app and its test suite for a practitioner review
What you walk away with
A live web app built with an AI agent, e.g. a stock and orders tracker for a small retailer, with login, a database and tests that run on every pull request
An internal tool that replaces a spreadsheet, e.g. an approvals tracker for a finance team, deployed with preview builds and a rollback history
A public repository showing your agent workflow: context file, task briefs, reviewed pull requests and the tests the agent had to pass
The tools you’ll use
- Claude Code, OpenAI Codex, Cursor and GitHub Copilot agent mode (you practise with more than one)
- Git, GitHub and pull requests
- Next.js with TypeScript
- Supabase (auth and database)
- Vitest and Playwright
- GitHub Actions
- Vercel (preview and production deployments)
- Secret scanning (GitHub secret scanning or Gitleaks)
How AI fits your workflow
AI is the core of this course. You work the way modern teams now work with coding agents: you scope the task, give the agent the right context, let it write the code, then review the diff, run the tests and decide what ships. The agent types; you stay accountable. You leave with a repeatable loop you can use on any codebase: brief, build, review, test, secure, ship.
Career routes
- Junior developer on a team that already uses AI coding agents
- Freelance builder of internal tools and small web apps for SMEs
- Technical product manager or founder who can ship and verify a first version
- Existing developers: a faster, safer workflow in your current role
Live, small and hands-on. Never just videos.
Live reviews
A practitioner reviews your actual work, on screen.
Practice sandboxes
Safe environments where mistakes cost nothing.
Private Discord
Help between sessions when you are stuck.
Career pathing
A clear route to a role or paid service.
Portfolio work
Projects employers and clients can inspect.
Not included: laptop, data, optional tool plans, exam fees.
Vibe-coding Professional Developer (Agentic Development): your questions answered
Take a place on Vibe-coding Professional Developer (Agentic Development)
WhatsApp ACADEMY with your goal, or use the form. We run a quick readiness check, then send placement and payment details in writing.
WhatsApp ACADEMY to +234 817 188 5917Employers can sponsor any course.
Tell us who you want to sponsor and the outcome you need. To train the whole team, see Corporate IT Training.