Selecting a Portfolio Project: How to Choose What to Build

Picking a portfolio project is where most people stall. There are too many options, and the default move is to grab a technology you want to learn and bolt a demo onto 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 mirrors what those companies use.

Real data drives every step. The job descriptions come from a monthly scrape of AI engineering roles across several cities, so the findings are grounded in real postings, not guesses. We aim for a project that speaks to several companies in a domain at the same time. That way one piece of work 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 portfolio section 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.