What's the Best Way to
Learn AI for a Job?
Build production projects, not just take courses. Focus on implementation over theory.
The learning that leads to jobs looks different from the learning most people do.
You've Taken Courses. Watched Tutorials.
Why Aren't You Getting Hired?
You've completed Coursera, Udemy, YouTube tutorials. Your certificates don't seem to impress anyone.
You can follow along with tutorials, but when you try to build something original, you get stuck.
Job postings ask for 'production experience' and 'deployed projects.' Your learning doesn't translate.
The Learning That Gets You Hired Looks Different
The World-Class AI Engineer Cohort
I've helped dozens of people land AI roles. The ones who succeed learn differently than the ones who struggle. Here's what actually works.
Build From Week One
Start a real project immediately, not after 'finishing' courses
Focus on Production
Deployed apps, not Jupyter notebooks. End-to-end, not tutorials.
Get Feedback
Learn from practitioners, not just content. Iteration beats consumption.
Meet Your Mentor
My aim has been the same for years: become a world-class AI engineer. Every career move I've made has been measured against that.
I started as a software tester on a $500/month internship in the Netherlands. Taught myself to code, learned to ship real systems, and worked my way to Senior Engineer at GitHub.
Then I left GitHub. I joined an AI research lab as Member of Technical Staff, where I currently build products for secure AI monitoring.
The cohort draws directly from my real experience so you can make progress fast.
I run this special cohort with only a few people because hands-on work with me is what it takes to bring you to become a world-class AI engineer.
Real Results
Vittor
AI Engineer
Built and deployed his portfolio piece, then landed the AI role
"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
8 Weekly Tuesday Sessions
3 hours each for 24 live hours total.
Project Scoping at Kickoff
We set the scope of what you'll ship and the milestones to get there before the live sessions start.
Code Reviews
Reviews of your code from Zen during the cohort.
Lifetime Demo Access
Every architecture demo is recorded and yours to keep.
Demo Day
You present what you built and get feedback from Zen, with a recording you can use in your portfolio.
12 Months Community Access
Included with the cohort.
Every Month of Tutorial Hell Is a Month You're Not Getting Paid
Frequently Asked Questions
Why do projects matter more than courses for AI jobs?
Hiring managers don't care what courses you completed. They care what you can build. Courses prove you can follow along; projects prove you can solve problems. A deployed AI application demonstrates: you can handle real data, integrate APIs, deploy to production, and solve actual problems. That's what gets you hired.
What AI projects should I build to get hired?
Build projects that demonstrate end-to-end skills: (1) A PDF Q&A system that shows RAG, embeddings, API integration. (2) A custom chatbot with specific domain knowledge that shows prompt engineering and deployment. (3) An AI-powered tool that solves a real problem and shows product thinking. Avoid: Kaggle competitions (hiring managers don't care), tutorial follow-alongs (everyone has these), toy demos that aren't deployed.
Should I skip courses entirely?
No. Courses have a role, but it's limited. Use courses to understand concepts you'll apply immediately. Watch a video on embeddings, then build something with embeddings the same day. The trap is treating course completion as the goal. Courses are inputs; projects are outputs. Hiring managers evaluate outputs.
How much time will this take?
You'll spend 3 hours every Tuesday in the live session and roughly 3 hours of async work in between, for 8 weeks. The Tuesday session time is fixed.
Can I do this while working full-time?
Yes, most attendees do. The live session is one Tuesday a week and the async work fits around your existing schedule, as long as you can carve out roughly 6 hours a week.
I've signed up for cohorts before and dropped out. How is this different?
It probably isn't, and you should hold the money. Most cohort dropouts are people who couldn't articulate what they were shipping when they signed up. That's why the consult exists, and why I turn down most applications. If we get on the call and you can't tell me what you'll have shipped at the end of week 8, I'll point you to the AI Native Engineer community until you can.
I'm not pivoting careers. I want to build a product. Does this still work?
Yes, the cohort works for people shipping their first serious AI system whether the goal is to land a senior role or to launch a product. The shipped system serves both equally well.
Do I need prior AI experience?
You need to be able to code in Python or TypeScript. Complete beginners can follow the classroom they get access to before the cohort sessions to come in well-prepared.
What does it cost?
It's a four-figure investment that we discuss during the 30-minute consult, alongside whether the cohort is the right fit for your project.
What's the fastest way to learn AI for employment?
The fastest path: (1) Learn enough Python to be functional (2-4 weeks if new). (2) Build your first AI project immediately, like a simple RAG system. (3) Get feedback from someone in the industry. (4) Iterate and build 2 more projects. (5) Position yourself strategically. With guidance, this takes 3-6 months. Without guidance, people often spend 6-12 months in tutorial hell.
Can I learn AI on my own, or do I need help?
You can learn on your own, but most people waste significant time. Self-taught challenges: choosing what to learn, identifying gaps you don't know you have, building the wrong kinds of projects, positioning yourself poorly. Guidance from a practitioner typically saves 2-4 months of wasted effort and increases your probability of actually landing a role.
I accept those who have the highest chance of success.
In the 30-minute call we discuss your goals and whether you are ready for the program.