LUNARTECH Fellows Blog
Context: LunarTech Fellows Research
Last Updated: February 2026
Walk into any tech conference today. Listen to the keynotes. Watch the CEOs speak. What do they talk about? They talk about AI models getting larger, automation replacing jobs, robotics taking over manufacturing, the future of work. What do they never talk about? Talent. Specifically: Where does great talent come from? Why are our universities producing fewer and fewer people who can actually build the things these leaders dream about? And what happens to a country when the pipeline breaks? These are uncomfortable questions. But they're the most important ones of our time.
Universities were built for a different era. They offer theoretical knowledge, research methodologies, academic credentials, four or more years of structured learning, and degrees that say you completed this program. Tech companies need something completely different. They need practical engineering skills, the ability to ship real products, experience with production systems, problem-solving under real constraints, and skills that generate revenue from day one. These are not the same thing.
Here's the uncomfortable truth: tech companies invest over $100K into training a single employee. They run internal bootcamps, mentorship programs, and continuous education. A junior engineer at Google or Meta might cost the company $200K–$500K in their first two years, between salary, benefits, training, and mentorship. Meanwhile, students go into debt to pay for their education. The average US student graduates with $30K in debt. In some countries, public universities are underfunded, and the quality shows. The tech employee gets paid to learn. The student pays to learn. No wonder the best talent flows toward tech.
As this gap widens, something predictable happens. Universities output a certain quality of graduate. Tech companies require a different quality of employee. The gap between these two grows wider every year. This is not about degrees being worthless. It is about a structural mismatch. Universities optimize for academic research output, publication counts, peer review, and theoretical advancement. Tech companies optimize for shipping products, user growth, revenue, and engineering excellence. These are opposite optimization targets.
When universities and industry diverge, graduates cannot find jobs. Not because there are not jobs, but because they do not have the skills that matter. In Spain, youth unemployment sits around 27% with underemployment over 40%. Italy sees 24% youth unemployment and 35% underemployment. Greece faces 35% youth unemployment and 45% underemployment. France has 17% youth unemployment and 25% underemployment. The global average sits around 13% youth unemployment and 20% underemployment. Many of these are not idle by choice. They are qualified on paper but cannot contribute to actual work.
And who pays for this mismatch? Governments do. France spends 25% of its government budget on social spending. Germany spends 22%. Sweden spends 28%. The United Kingdom spends 20%. The average across the European Union runs between 20–25%. A significant portion of this goes to unemployment benefits, housing assistance, and retraining programs, all symptoms of a talent pipeline that is not working.
When companies cannot find the talent they need, they do the rational thing. They automate. The shift from 2015 to 2025 shows a clear pattern: traditional hiring gives way to AI and ML engineering, 10 engineers per project becomes 2 engineers plus AI tools, growing headcount becomes growing efficiency, hiring more juniors becomes hiring fewer but paying more, and building teams becomes building systems. This is why you see headlines like AI will replace 300M jobs. It is not because AI is magical. It is because companies could not hire enough qualified people anyway, so they found another way.
This creates a vicious cycle. Universities produce graduates with quality mismatches. Graduates cannot find employment. Government pays for social welfare. Tax revenue goes to welfare instead of education. Universities get less funding. Quality declines further. And then the cycle repeats. Each year, the gap widens. Each year, more talent is wasted. Each year, countries become more dependent on importing talent or outsourcing work.
When talented people cannot find meaningful work at home, they leave. They go where the opportunities are. Romania has a diaspora of 4.2M people, with 18% of the population living abroad. Poland has 20M people in the diaspora, 12% of the population. Greece has 3.5M people abroad, 25%. Armenia has between 7–10M people in the diaspora, an astonishing 70%+. Albania has 1.8M abroad, 40%. These are not people who do not love their countries. They are people who could not find a place to use their skills. The brain drain is not a mystery. It is the logical result of a broken talent pipeline.
When domestic talent is not available, companies outsource. When outsourcing becomes normalized, something strange happens. The country stops building. You can outsource customer support, manufacturing, data entry, even software development. But you cannot outsource core engineering innovation, defense technology, strategic AI research, or national infrastructure. Every country that outsources its brain work eventually finds itself dependent on others for the things that actually matter. You can buy software from anywhere. But you cannot buy national security. You cannot buy economic sovereignty. You cannot buy the ability to shape your own future.
This is where most articles would give you tips. Learn to code. Get certifications. Network more. But that puts the burden on individuals, and individuals cannot solve systemic problems. What we need is a new model.
We did not set out to write a blog post about the problem. We set out to build a solution. The LUNARTECH Fellowship is designed to bridge the gap between talent that needs direction, mentorship, and real experience, industry that needs skilled engineers who can contribute from day one, and countries that need to stop losing their best people.
In traditional education, you pay to learn. At LUNARTECH, you get paid to learn. Traditional education is theory-focused. We are project-driven. In traditional education you learn in isolation. With us, you get mentorship from engineers. Traditional education gives you a degree at the end. We give you skills, a network, and potential funding. Traditional education takes 4+ years. We take 6–12 months. Traditional education leaves you in debt. We invest in your future.
The Thiel Fellowship proved this model works. They invested $200K per fellow in approximately 250 people, and created over $750B in value. Y Combinator proved it too, with $800B–$1.3T in portfolio value from 5,000 companies. Entrepreneur First proved it: you do not find founders, you create them. Put talented people in the right environment with the right support, and company creation is an emergent property.
We invest in promising individuals. We provide real projects with real engineering challenges, mentorship from experienced engineers and founders, pathways to employment or startup funding, and a network of fellow fellows and industry connections. We are not competing with universities. We are filling the gap that universities cannot fill, the gap between having knowledge and being able to use it.
Every fellow who becomes a productive engineer, every founder who builds a company, every person who finds meaningful work instead of drifting through unemployment, that is one fewer person on social welfare, one more taxpayer, one more job creator, one more reason for talented people to stay. This is not charity. It is infrastructure. It is human capital infrastructure. Just as roads connect cities and power grids connect homes, talent pipelines connect people to purpose. When the pipeline breaks, everything downstream suffers.
If you are a student, a graduate, or someone looking to transition into AI and engineering, we are looking for you. If you are a company that needs talent, we are building talent for you. If you are a country that wants to stop the brain drain, we are creating reasons to stay. The old model is broken. We are building a new one.
At LunarTech, we keep meeting incredibly motivated people who feel stuck in the same frustrating loop. Every role asks for experience, but no one seems willing to give them that first real chance to build it. If this sounds familiar, please know — you are not alone, and there is a way forward.
You might be:
It can feel exhausting. It can feel discouraging. And it can feel like a vicious, never-ending loop. We have been there — and that is exactly why we created the LunarTech Apprenticeship Programs, with love, to help break that cycle.
Over 6 months, you will join an international AI startup family, contribute to real products that matter, and develop job-ready skills while being lovingly mentored by experienced professionals who genuinely care about your growth. You will not be just watching from the sidelines. You will be in the arena, working on live AI, data, product, software, UX, and content problems that actually matter — and we will be right there with you every step of the way. Think of it as a warm, structured journey: you start as an aspiring learner and end as a confident contributor with concrete stories, skills, and a portfolio you can be proud of.
Let us share a couple of stories that warm our hearts.
Picture Sarah, a bioinformatics enthusiast who joined us last year. She arrived with lots of theoretical knowledge but no hands-on experience in a dynamic environment. By month three, she was troubleshooting AI pipelines for cutting-edge tools, engaging in code reviews with senior engineers, and pitching ideas during sprints and product discussions. Six months in, she secured a role at a biotech company — with a portfolio full of real, production-related work she could confidently talk about in interviews. We could not be prouder of her.
Now think of Alex, a self-taught coder who felt stuck in endless beginner tutorials. He joined our Software Engineering Track and started working on live SaaS deployments. He shipped features alongside the engineering team, honed DevOps skills using tools like Docker and GitHub, and learned how to navigate real-world trade-offs, bugs, and deadlines. Today, he is thriving at a major tech firm and openly credits the combination of mentorship, structure, and exposure to real systems as the turning point in his journey. Stories like Sarah and Alex are why we do what we do — they remind us that with the right support, everyone can flourish.
We want to share something important with you from the heart: the LunarTech Apprenticeship is our gift to you. We invest over $200K in each fellow throughout the program, because we genuinely believe in your potential and want to see you thrive. Here is what that means for you:
We share this with you openly because we want you to join us with full awareness and complete trust. If you are here for genuine growth, challenge, and transformation — we cannot wait to welcome you with open arms. And if you need a paid role right now, we completely understand, and we wish you all the best on your journey.
Our apprenticeships are designed to align with the U.S. Fair Labor Standards Act and similar guidance around training programs:
There are many internships, bootcamps, and volunteer opportunities out there — and we celebrate them all. But we wanted to create something a little different, something deeper and more caring. At LunarTech, you will be joining a warm, supportive family:
This is not a passive tutorial. It is a warm, structured immersion into how a real AI company operates — with you at the center.
Think of it as your personal journey with four gentle phases:
You are the protagonist. We are the mentors, tools, and world you get to explore.
This is not a "watch and take notes" shadowing experience. From early in the program, you will be contributing under guidance to real work. Depending on your track, you might:
You will participate in the actual rhythm of a real deep tech startup:
All of this happens in a training-first context. You are supervised, coached, and supported, and your contributions are scoped so that they are educational, not mission-critical, keeping the focus firmly on your development.
We invest over $200K in every fellow throughout the program. We want you to understand what that investment really means for you.
Imagine looking back after 6 months and being able to say: "I had senior people reviewing my work every week, I shipped things that mattered, and I finally had a story to tell in interviews that did not start with 'I followed a tutorial…'." That is the kind of value this program is designed to create.
You are not left to figure things out alone. You become part of a small, caring circle of people who are actively guided. Your mentor does not just comment on your code or designs. They share why something works better a certain way, walk you through trade-offs, and help you build judgment. Over time, you will notice you are catching issues before they are pointed out, asking better questions, and starting to think like a professional, not just a learner. This kind of ongoing, practical mentorship is something people often pay serious money for in coaching or premium courses.
By the end of the apprenticeship, you do not just have screenshots or toy apps. You have concrete stories:
Alongside this, you get a certificate of completion and for those who fully commit and perform well, a letter of recommendation that speaks specifically to your real contributions.
Instead of paying for access, you are given scholarship-style access to:
In many other setups, you would pay for this kind of exposure. Here, it is part of the experience because our goal is to accelerate your learning, not sell you content.
You do not go through this in isolation. You collaborate with other apprentices and with the core team. Over 6 months of stand-ups, reviews, and shared problem-solving, you naturally build relationships. Some of those people will go on to work at other companies. Some will stay in the LunarTech orbit. Either way, you walk away with a network that knows your work because they have seen it in action.
If you tried to piece together the equivalent on your own, you would likely be looking at:
Conservatively, the combination of training, resources, and experience you get here would land in the five-figure range if packaged as a paid program. We are not asking you to pay that — we are investing $200K+ in you. Instead, your investment is your time, energy, and commitment over 6 months. That does not mean this is the right choice for everyone, but it does mean that if you are in a position to take on this high-value learning experience, the return can be substantial.
Training programs where the organization invests significantly in the participant can be controversial, and that is a fair conversation to have. We believe strongly that when we invest this much in someone, it must be training-first, transparent, and structured around the fellow being the primary beneficiary.
Our program is built around principles like the FLSA Primary Beneficiary Test:
In addition, we use standard agreements like NDAs, MoUs, and IP and confidentiality clauses to protect everyone's work and privacy. You will always know what you are signing, and we encourage you to read every document carefully and ask questions.
Nothing in this blog is legal advice. It is a high-level explanation of how we think about fairness and structure.
This program might be a wonderful fit for you if:
This program may not be the best fit if:
Both paths are completely valid. We simply want to find the people who will genuinely thrive in this kind of environment — those who see it as a meaningful investment in their growth.
What is the compensation? While this is not a salaried role (no wages, salary, or employee benefits), we invest $200K+ in every fellow. The real value lies in the skills, portfolio, experience, mentorship, and resources you will gain — things that can transform your career far more than any short-term salary could.
What if I need flexibility? The program is designed to be flexible. It is remote and typically requires 20-25 hours per week. There is structure — regular meetings, gentle deadlines, and meaningful responsibilities — but we genuinely want to work with you to accommodate your personal and academic commitments.
Can I put this on my CV or LinkedIn? Absolutely. This is legitimate, valuable experience in a real AI company. You will have concrete contributions to describe with confidence, and upon successful completion, you will receive a certificate and potentially a letter of recommendation.
What do you expect from fellows? We hope for genuine commitment and willingness to grow. We invest significant time mentoring and guiding you. In return, we simply ask for your best effort, professionalism, and a collaborative spirit.
How are apprentices selected? Our process is warm and thoughtful: we review your CV and any portfolio or project links you want to share; we have two friendly conversations focused on your skills, motivation, and how you might fit into our culture; and we give you a small, relevant assignment for your chosen track. If it feels like a good match, you will sign some simple agreements before beginning.
Is there a chance of a paid role afterward? We cannot guarantee anything, of course. However, strong performers may be considered for paid roles or extended collaboration where it makes sense for both sides. The apprenticeship is designed to make you far more competitive in the broader job market — and perhaps, down the road, with us too.
Duration: The program lasts for 6 months.
Commitment: The typical time commitment is 20-25 hours per week.
Format: This is a remote-first program with structured meetings and asynchronous work.
Compensation: We invest $200K+ in every fellow. This is not a salaried role — there is no salary, no overtime, and no benefits. The real value is in the skills, portfolio, and experience you gain.
Primary Benefit: Your learning, experience, and portfolio are the primary benefits of this program.
What You Get: You receive a $200K+ investment in your training, direct mentorship and feedback, real-world projects and access to codebases and tools where appropriate, a certificate of completion, a letter of recommendation for successful apprentices, and scholarship-style access to LunarTech Academy resources.
Selection Process: The selection process consists of 2 interviews plus 1 assignment, focused on skills, motivation, and culture fit.
Agreements: You will sign an NDA, MoU, IP/Confidentiality, and related documents before you start.
Termination: Participation is at-will. Leaving early without valid reasons or notice may result in losing program benefits. Confidentiality and IP obligations continue even after you leave.
Post-Program: There is no promised job. Strong performers may be considered for paid opportunities, but the core goal is making you more employable everywhere.
If this speaks to something in you, we would love to hear from you. Here is how to take the next step:
Pick your track:
Prepare your materials:
Apply:
At LunarTech, we are not just building AI products. We are helping nurture the next generation of creators, engineers, designers, and strategists who will shape what AI becomes. Your story does not start "someday." It can begin right here, with this 6-month journey. We would be honored to have you join us.
The best time to fix the talent pipeline was 20 years ago.
The second best time is now.
LUNARTECH — Building the next generation of AI engineers and founders.
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