What Projects Should I Build
for My AI Portfolio?
Most AI portfolio projects get ignored by hiring managers.
Learn which projects actually demonstrate the skills employers want to see.
AI Native Engineer Community Access
You Have Projects.
But They're Not Getting You Interviews.
Your Kaggle competitions and tutorial projects look like everyone else's. Hiring managers scroll past them.
You spend weeks on projects that showcase the wrong skills. Theory over production-ready work.
You don't know what employers actually want. So you guess and hope something sticks.
Build Projects That Prove You Can Ship.
The AI Career Accelerator
Employers don't want to see that you can follow tutorials. They want proof you can build production-ready AI systems that solve real problems. Here's how to create a portfolio that actually opens doors.
Choose High-Impact Projects
RAG systems, AI agents, deployed applications
Build Production-Ready
APIs, error handling, documentation, deployment
Present Strategically
Show business impact, technical decisions, results
Meet Your Mentor
When I started in tech, I was based in the Netherlands with no connections and only thousands of video game hours under my belt. Not exactly the ideal starting point.
My first tech job was software tester. One of the most junior roles you can start with. I was just happy someone took a chance on me.
I kept learning. Kept pivoting. But what actually accelerated my career wasn't more certifications or more code. It was learning to solve problems that matter and proving beyond a doubt that what I built solved real problems. That's the skill that stays future-proof, even with AI.
I've since worked remotely for international software companies throughout my career. Proof that the high-paid remote path is possible for anyone with the right skills and motivation. In the end, I went from a $500/month internship to 6 figures as a Senior AI Engineer at GitHub.
Now I teach over 22,000 engineers on YouTube. Becoming an AI-Native Engineer is a system I lived through and offer to you today.
Real Results
Vittor
AI Engineer
Landed his first AI Engineering role in 3 months
"The coaching played a huge part in my success. I focused on AI fundamentals, the certification path, and soft skills like professional writing. Having access to expert guidance gave me confidence during interviews and helped me feel I was on the right path.
I built my own platform (simple but functional) and deployed it on AWS. I used it in my portfolio and showcased it during interviews. The way complex topics were explained, especially the restaurant analogy for AI systems, really stuck with me. Focusing on doing the basics well was absolutely essential."
What You Will Get
Personalized Roadmap & Career Strategy
A custom plan tailored to your background, goals, and timeline. No generic advice.
Weekly 1:1 Coaching Calls
Direct access to Zen for guidance, project feedback, and answers to your questions.
Portfolio-Ready AI Projects
Build production-grade AI applications to showcase to employers. Work that gets you hired.
Interview Prep & Mock Interviews
Practice technical and behavioral interviews. Learn what hiring managers look for.
Resume & LinkedIn Optimization
Transform your online presence to attract recruiters. Stand out from other applicants.
Community Career Support
Join the AI Native Engineer community. Not seeing results yet? You stay and keep going. We're with you through the ups and downs.
Every Generic Project You Build Is Time You Could Spend on Projects That Actually Get You Hired
Every month you delay can cost you thousands in lost earning potential. While you're watching tutorials, others are landing $120K+ AI Engineering roles.
I can only work with a limited number of 1:1 clients at a time to ensure you get the personalized attention you deserve.
Frequently Asked Questions
What are the best AI portfolio projects in 2026?
Projects that demonstrate production skills: (1) RAG-based document Q&A systems with real deployment, (2) AI agents that complete multi-step tasks, (3) Full-stack apps integrating LLM APIs with proper error handling. Avoid: Jupyter notebooks, Kaggle competition code, tutorial recreations. The key differentiator is deployment. A simple project that's live beats a complex project in a notebook.
Are Kaggle projects enough for an AI portfolio?
No. Kaggle shows you can optimize models in isolation. Companies need engineers who can build complete systems. Hiring managers told me directly: 'We ignore Kaggle. Show me something deployed.' Use Kaggle to learn, but your portfolio needs production projects with APIs, front-ends, and real users.
How many portfolio projects do I need?
Quality over quantity: 2-3 excellent projects beat 10 mediocre ones. Each project should demonstrate different skills: one showing API integration and deployment, one showing AI agent capabilities, one showing full-stack implementation. Make sure at least one is deployed and accessible.
How much time do I need to commit?
Most clients invest 10-15 hours per week, but this can be flexible based on your schedule. We'll have weekly 1:1 calls plus time for you to work on projects and learning. The key is consistency. Regular, focused effort beats occasional marathons.
Do I need prior AI experience?
Not necessarily. While some programming experience is helpful, many of my clients have successfully transitioned from web development, data science, or other technical backgrounds. We'll assess your current skills during our strategy call and create a personalized plan that meets you where you are.
How is this different from online courses?
Online courses give you content. 1:1 coaching gives you a personalized roadmap, direct feedback on your work, career strategy, interview prep, and accountability. You get answers to your specific questions and guidance tailored to your unique situation instead of generic advice meant for everyone.
What if I don't land interviews in 90 days?
You become a member of the AI Native Engineer community, and you stay and keep going. Career transitions take different amounts of time for everyone, and I'm not going to abandon you if things take longer. You get ongoing support through good times and bad.
What's the investment for 1:1 coaching?
Investment details are discussed during the 30-minute strategy call, where we'll assess your goals and create a custom plan. The program is designed to pay for itself quickly through your increased salary. Most AI engineers see a 20-50% pay increase.
Can I do this while working full-time?
Absolutely. Most of my clients work full-time and make steady progress. We'll schedule calls at times that work for you and create a realistic plan that fits your schedule. Consistency matters more than intensity.
How do I make my AI portfolio stand out?
Three things: (1) Solve real problems, not toy examples. Build something you or others actually use. (2) Deploy everything. Live demos are 10x more impressive than GitHub repos. (3) Document your decisions. Explain why you chose certain tools, how you handled edge cases, what you'd improve. This shows senior-level thinking.
Ready to Land Your AI Role?
Stop watching others succeed. Start building your AI career today.
30-minute strategy call • Limited spots available