Mindaugas, founder of Coho, transitioned from recruitment and community-building into product development using Lovable. Without prior coding experience, he built a job search guidance tool that gained paying users within days. Now, he’s scaling Coho by rebuilding it entirely with AI-driven development. His journey proves that the future of education isn’t in courses—it’s in building real things.
TL;DR
- You don’t need to be an engineer to build impactful products – Mindaugas used Lovable to turn his ideas into reality without writing code.
- Rapid validation leads to faster growth – He secured his first paying customers by simply sharing a prototype, proving demand before over-investing.
- AI-driven tools are the future of education – Learning by building, rather than taking courses, is the best way to stay ahead in today’s job market.
- Designers are uniquely positioned to leverage AI – With their expertise in user experience and visual language, designers can push AI tools like Lovable further than ever before.
The Journey Before Lovable
Mindaugas never saw himself as a developer. With a background in sales and hospitality, he discovered his passion for design through recruiting. Over the past decade, he dedicated himself to building design communities, working at companies like InVision (before Figma reshaped the industry) and On Deck. Eventually, he started building Coho, a platform designed to match small, curated peer groups of designers, engineers, and data scientists.
However, building Coho the traditional way—hiring engineers and designers—was slow and expensive. That’s when he stumbled upon no-code and AI-assisted development. His curiosity led him to Lovable, and suddenly, his mindset shifted.
“My brain has been waiting for this moment for 42 years,” he joked.
Discovering Lovable: The Gateway to Building
Mindaugas experimented with various tools, but Lovable felt different. It allowed him to iterate quickly, progressively making his projects more complex. His approach wasn’t about launching a perfect product; it was about testing, learning, and refining.
At first, he simply built small projects to understand the tool’s capabilities. Then came the breakthrough: understanding how to write system prompts, integrate AI APIs, and create user authentication.
“A big unlock for me was when I realized I could write a system prompt and connect an AI API—and it actually worked,” he said. “That’s when my confidence in building started growing.”
Turning an Idea into a Business
While learning to build with AI to eventually build Coho with it, Mindaugas started thinking about some of the other problems he keeps hearing from professionals. One of them - how hard the market is right now and that the traditional ways to apply are becoming impossible.
While he built his own career over the last decade by using a non-traditional approach to stand out, he initially resisted the idea of making a traditional course, finding it uninspiring. Instead, he built a system where job seekers could get step-by-step interactive guidance without needing to pay for expensive coaching.
He built a prototype in Lovable, demonstrating how his product could help job seekers navigate the difficult job market with structured guidance.
The unexpected happened: when he shared a simple Loom video of his MVP, the first person asked to pay for it.
“I didn’t even have a pricing model,” he laughed. “I just generated a quick Stripe link and sent it over.”
“People kept asking if I would do coaching, but I didn’t want to charge $1,000 for something I could scale through AI,” he said.
"Excellent content in step 2. I think it will really intrigue folks and open their eyes to new ways of approaching the job search."
"This is EXCELLENT content !"
"I'm loving the structure and how each section has a few different types of materials (audio, reading materials, and action items). I also like how you spaced out the release of each section. I think being able to message you questions we have would be helpful! I can tell you have put a lot of thought into it"
"This is gold!!!!"
Scaling Up: From MVP to Product
With a few paying users onboard and others eager to test, Mindaugas rapidly improved the product. He shipped new features like a community forum, allowing job seekers to connect and support each other—addressing one of their biggest concerns: isolation.
“One of the first requests I got was, ‘Can we interact with others going through this?’” he shared. “So, I built a community forum overnight.”
He also built an incremental content delivery system, where users gain access to new job search strategies every two days, increasing engagement and retention.
“It’s timeless advice that can help job seekers at any stage,” he explained. “And the way it’s structured means people actually engage with it instead of rushing through.”
Through his journey, Mindaugas also developed an in-depth process for refining AI-generated output. He found that crafting the right prompts and iterating them before feeding them into Lovable was key to ensuring high-quality results.
“People often try AI once, get a bad result, and give up. But the key is in refining how you communicate with it,” he emphasized.
The Future of Coho and AI-Driven Learning
The early traction of Backchannel has given Mindaugas valuable experience with AI tools that he'll apply to his main focus:
"I'm going to attempt rebuilding Coho with Lovable now that I understand what's possible."
Now that he understands Lovable’s potential, he sees an opportunity to bring his main venture to life without the traditional constraints of hiring full-time engineers.
Beyond that, he’s planning workshops to help designers overcome the fear of AI tools and embrace the future of product-building.
“Designers have an incredible advantage,” he explained. “They understand user experience, and they have the language to instruct AI with precision. That’s a superpower.”
Mindaugas also believes that education is shifting away from theoretical knowledge and towards hands-on, practical learning. In a world where AI can generate answers instantly, the real skill is knowing how to use these tools effectively.
“Instead of learning how to calculate financial metrics, why not build an app that automates it?” he challenged. “The barrier to making something is gone. Now, it’s about who dares to build.”
When asked about his roadmap for BackChannel, he emphasized that he doesn't have a formal PRD (Product Requirements Document) yet.
“I quite quickly managed to build a core that’s pretty valuable, so for now, I just need to create the rest of the content for the last few steps and make it available for users. Then I’ll listen to feedback,” he explained.
Mindaugas is already iterating based on user needs, having recently shipped a community forum feature. He’s considering adding video capabilities to complement audio, written content, and action items.
“I might build a video feature so there's a combo of audio + video + written content + action items,” he shared.
Looking ahead, he sees opportunities to expand beyond job search guidance.
“There likely will be opportunities to create other programs in the future—like teaching how to build things with Lovable,” he said. “If there’s demand, I’ll build it, and the core architecture already exists for me to make it.”
Lessons for Aspiring Builders
- Start Small, Learn Fast – Don’t aim for perfection. Experiment, refine, and iterate.
- Use AI to Accelerate Learning – Instead of spending months hiring an engineer, figure out how much you can do yourself.
- Solve Real Problems – The best validation is when someone asks to pay for what you’ve built.
- Embrace the Shift in Work – The job market is changing. MBAs and traditional paths don’t guarantee success anymore. Building real things does.
- Designers have a unique advantage in AI development – Their ability to structure user experiences and interface logic makes them the perfect candidates to leverage tools like Lovable.
A New Era of Innovation
Mindaugas’ story is proof that anyone—designer, recruiter, or entrepreneur—can become a builder with the right tools. Lovable is breaking down barriers, enabling people to turn ideas into reality without traditional technical constraints.
As Mindaugas puts it,
“The future belongs to those who are willing to experiment. AI levels the playing field—the only thing standing in your way is not trying.”
