Product Owner
Helps shape priorities, clarify requirements, and define what needs to be delivered.
Engineering Experience
Programme Guide
The 12-Week Engineering Experience
This is a supervised engineering experience where students, software developers, AI engineers, Generative AI engineers, and developers seeking real open-source experience are onboarded into the rhythms used in real software teams: understanding requirements, breaking down problems, planning, development, code review, testing, pull requests, CI/CD awareness, documentation, and delivery.
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01
How the Programme Actually Works
The first week is focused on onboarding. Participants set up their environment, understand the project, read requirements, learn the contribution process, meet the working rhythm, and understand expectations.
From week 2 onward, the programme works like a real engineering project. Participants do not follow isolated weekly lessons. They work through real issues, investigate context, think through possible solutions, develop features or fixes, raise pull requests, receive code review, test changes, improve their work, and contribute to open-source projects under the supervision of senior software and AI-aware engineers where possible.
02
The Working Rhythm
These activities repeat across the 12 weeks, just like in a real software team. Problem analysis, planning, development, review, testing, documentation, and delivery happen continuously rather than as separate classroom topics.
Project onboarding
Sprint planning and ticket selection
Problem analysis and solution design
Daily progress updates
Development work
Git branches and commits
Pull requests
Code review and feedback
Testing and quality checks
CI/CD awareness
Documentation
Review, refinement, and next steps
Sprint review and reflection
Sprint review and reflection help participants understand what was completed, what improved,
and what still needs work. This is where the team reviews progress, discusses lessons learned,
and identifies how to improve the next cycle of work.
03
Working Under Senior Supervision
Participants are not left alone to figure everything out. They work under the supervision of senior developers, AI-aware engineers, and, where possible, software architects who help them understand the problem, the code, and the engineering judgment behind a responsible solution.
- Understanding the codebase
- Breaking down issues
- Thinking through solution options
- Reviewing technical approach
- Giving code review feedback
- Explaining engineering trade-offs
- Improving code quality
- Supporting professional communication
- Helping participants think like engineers, not just write code
04
The Engineering Team Environment
Scrum Master
Supports the working rhythm, helps remove blockers, and keeps the team aligned.
Software Architect
Guides technical direction, system design, maintainability, and long-term thinking where possible.
Senior Developer
Reviews code, mentors participants, explains trade-offs, and supports software and AI-aware engineering quality.
Participant / Junior Developer
Works on real issues, asks questions, reasons through solutions, contributes code, responds to feedback, and builds confidence through practice.
QA / Testing
Supports quality by checking functionality, reliability, edge cases, and expected behaviour.
05
What Participants Learn Through Real Project Work
How to understand existing codebases and how different parts of a system work together
How to analyse real project problems and turn them into responsible technical solutions
How to break down a problem before writing code
How to contribute to open-source projects using professional workflows
How to create, explain, and improve pull requests
How to use code review feedback to improve the quality of the solution
How to test and validate changes before they are submitted
How to communicate progress, blockers, and technical decisions clearly
How engineering teams collaborate, plan, and deliver work
How architectural decisions affect everyday development
How to build credible evidence of real open-source contribution
How to build the confidence to face unfamiliar problems and think through solutions independently
06
What This Is Not
This is not a lecture-based course.
This is not a set of weekly classroom topics.
This is not tutorial watching.
This is not toy project work.
This is not syntax practice without real engineering context.
This is not about memorising code without understanding the problem.
This is not a shortcut to experience without real contribution.
This is not passive learning without feedback, review, and improvement.
It is a supervised engineering environment designed to give participants real-world exposure to problem solving, software engineering, AI engineering, and open-source workflows through guided contribution.
07
Why This Model Works
Students, software developers, AI engineers, and Generative AI engineers grow faster when they work inside real systems, receive feedback, and see how professional teams make decisions. Syntax matters, but it is not enough. Participants practise the behaviours and habits of real engineers: understanding problems, breaking them down, making technical decisions, contributing to existing codebases, and improving work through review.
08
Building a Real Contribution Trail
The goal is not to complete isolated exercises. Participants build visible evidence of real engineering activity: problems investigated, issues clarified, pull requests opened, code reviews received, and contributions improved through feedback.
Apply for the next cohort
The next cohort starts on 06 July 2026. The programme fee is £1,500 and each cohort is limited to 8 participants to keep the experience focused, practical, and personal.
Apply Now