Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (co-founder and CEO)

Mar 9, 2025 1h 9m 15 insights Episode Page ↗
Anton OCK, co-founder and CEO of Lovable, discusses their AI engineer product, which hit 10M ARR in two months with 15 people. He shares insights on building lovable products, hiring generalists, and leveraging AI for rapid development.
Actionable Insights

1. Become an AI Tool Expert

Dedicate a full week to solving a problem using AI tools to become proficient, as being in the top 1% of users will significantly differentiate you in the coming years.

2. Build Lovable Products

Strive to create products that users genuinely love, starting with a “minimum lovable product” and continuously improving, as this drives organic growth.

3. Practice Clear AI Prompting

When interacting with AI, be extremely specific about expectations and what is or isn’t working, as precise communication is even more critical with AI than with humans.

4. Prioritize by Biggest Bottleneck

Identify the single largest problem or bottleneck, solve it quickly, and then move to the next, avoiding overthinking long-term roadmaps for rapid progress.

5. Start with User Problem, Then Add AI

Begin product development by understanding the end-to-end user experience and core problem, then strategically integrate AI to solve specific aspects, rather than retrofitting AI into existing solutions.

6. Hire for Deep Care/Obsession

Seek candidates who demonstrate profound care or obsession for the product, users, and team, as this commitment is a strong predictor of long-term contribution and success.

7. Conduct Work Trials for Hiring

Implement work simulations, having candidates join the team for at least a day or a full week, to assess their thinking, reasoning, and collaborative abilities in a real-world setting.

8. Create a Clear Hiring Filter

Use job descriptions to explicitly communicate the intense pace and ambitious mission, attracting candidates who thrive in such environments and filtering out those seeking comfortable work.

9. Embrace Generalist Skills

Prioritize hiring individuals with diverse skill sets across architecture, design, product taste, and user interaction, as being a generalist is increasingly valuable in AI-driven product teams.

10. Leverage AI for Post-Launch Growth

Consider how AI can assist founders not just with building, but also with critical post-launch activities like user acquisition, feedback collection, and overall go-to-market strategies.

11. Build in Public for Awareness

Regularly share product updates and achievements on social media to generate awareness and foster organic word-of-mouth growth.

12. Embrace Engineering-Led Product Decisions

For AI-first products, allow engineering to lead product decisions, as optimal solutions often involve technical details and larger initiatives intertwined with problem-solving.

13. Foster In-Office Collaboration

Encourage in-office work and informal interactions, like shared lunches, to facilitate high-bandwidth communication, cross-pollination of ideas, and continuous subconscious problem-solving.

14. Use AI Chat Mode for Learning

Utilize AI tools’ chat modes to ask questions, understand functionality, and get unstuck, which also serves as an effective way to learn about software engineering principles.

15. Use Linear for Talent Tracking

Employ versatile tools like Linear for various company operations, including talent application tracking, due to its effectiveness and simplicity.