Selecting a Portfolio Project: How to Choose What to Build
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Most people get stuck when they pick a portfolio project. There are too many options, and the usual approach is to take a technology you want to learn and build a quick demo with it. That produces a buzzword demo, not a project a hiring manager takes seriously.
In this session you learn a framework for choosing what to build. You start from a real domain, look at real companies, and read what they actually work on. From there you extract the problems they solve, find the ones several companies share, and turn one of those into a project. Technology comes last, chosen to match the stack the companies already use.
We run the framework live in this session. We pick education as a domain and use a coding agent to research the Berlin edtech companies that hire AI engineers. Then we read their job descriptions and engineering blogs, extract the problems they work on, and cluster those into shared themes. From one theme we design a project with a technology stack that matches what those companies use.
We use real data in every step. The job descriptions come from a monthly scrape of AI engineering roles across several cities, so the findings come from real postings, not guesses. We aim for a project that's relevant to several companies in a domain at the same time. That way one project counts for several interviews.
Links
Resources referenced in the session:
- AI engineering field guide - the repo where the framework and project-selection process live. The session fills out its
portfoliosection live. - Solving a real AI engineer take-home assignment live - the related session on turning interview assignments into portfolio projects.
- Personal brand for developers - the companion session on presenting your work once you have built it.
Hosted by
Alexey Grigorev
Chief Agent Officer at AI Shipping Labs
Software engineer and machine learning practitioner with 15+ years of experience building production ML systems. I focus on practical, production-grade ML and AI systems, from early prototypes to reliable systems in production.
I'm the founder of DataTalks.Club, a free community that connects tens of thousands of practitioners worldwide, and the creator of the Zoomcamp series, free, code-first programs that have reached 100,000+ learners globally.
At AI Shipping Labs, I'm building the kind of environment that would have accelerated my own career growth. After years of teaching at scale, I wanted something more focused: a space for action-oriented builders who want to turn AI ideas into real projects. The community gives members the structure, accountability, and peer support to ship practical AI products consistently, even alongside their main jobs.