20VC with Harry Stebbings• Mar 5, 2025• 49:39Interview

Anton Osika, Co-Founder and CEO @ Lovable: Hitting 85% Day 30 Retention - Better than ChatGPT

From 20VC with Harry Stebbings

Anton Osika•Co-Founder and CEO, Lovable

Executive Summary

Lovable.dev is experiencing hypergrowth, adding $2 million in ARR per week, driven by a product with higher month-one retention than ChatGPT.
Founder Anton Osaika advocates for a lean, fast-moving culture, prioritizing ambitious, high-potential junior talent over experienced executives and avoiding premature management layers.
The company operates on the belief that foundation models (from OpenAI, Google, Anthropic) are becoming commoditized, allowing them to focus on the application layer without being tied to a single provider.
Osaika presents a bearish outlook on traditional SaaS companies with per-seat pricing models, arguing that AI will reduce headcounts and erode their revenue base.

12 quotes

Concerns Raised

Maintaining culture and a sense of ownership as the team scales rapidly.
Losing momentum and excitement, which currently fuels the company's progress.
The risk of slowing down product development by adding complexity or management layers.

Opportunities Identified

Disrupting the software development lifecycle with AI agents.
Capitalizing on the commoditization of foundation models to build a best-in-class application.
Attracting the world's top 1 million builders to the platform.
Leveraging European talent to build a capital-efficient, global-first company.

Key Themes

Hypergrowth and Scaling Challenges

Lovable is growing at an unprecedented rate of $2 million ARR per week. This rapid scaling has forced the team to make difficult decisions, such as rewriting the entire codebase over eight weeks to handle the load, while simultaneously managing explosive user growth.

This provides a case study in the technical and product pressures of extreme product-market fit, highlighting the need for architectural foresight even in early-stage, fast-moving startups.

Talent and Culture Philosophy

The founder emphasizes hiring for raw, ambitious talent over experience, believing experience can sometimes be a negative. He learned from his previous company to avoid introducing management layers and a 'scale-up' culture too early, instead favoring a flat structure of empowered generalists to maintain speed and ownership.

This offers a counter-narrative to traditional scaling playbooks, suggesting that for deep-tech companies, maintaining a lean, high-ownership culture is more critical than hiring a conventional executive team.

AI Foundation Model Commoditization

The company intentionally uses multiple foundation models (OpenAI, Gemini, Anthropic) and believes no single provider will win. Osaika argues that the models are becoming commoditized, shifting the competitive advantage to the application and user experience layer rather than the underlying technology.

This insight is crucial for strategists and investors in the AI space, suggesting that long-term value will be captured by companies building unique products on top of the models, not by the model providers themselves.

The European Tech Advantage

Osaika makes the case for building a global company from Europe, citing a larger pool of available raw talent compared to the US. This strategy allows companies to leverage lower engineering costs while selling into high-value markets like the US, creating a significant competitive advantage.

This challenges the Silicon Valley-centric view of startup creation, highlighting a viable and potentially more capital-efficient model for building globally competitive tech companies.

Disruption of SaaS Business Models

A strong conviction is expressed that AI will fundamentally disrupt SaaS. Specifically, companies with per-seat pricing are identified as a major short opportunity because AI agents will replace human employees, causing the number of paid 'seats' to decline dramatically.

This is a critical forward-looking analysis for investors and operators in the software industry, signaling a necessary evolution from per-seat to value-based or consumption-based pricing models in the age of AI.

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Topics

AI Development AI Agents Software Engineering Hypergrowth ARR Startup Scaling Founder Lessons Talent Acquisition Hiring Strategy Corporate Culture Foundation Models OpenAI Anthropic European Startups SaaS Pricing Models

Processed Mar 29, 2026 yt-dlp + mlx-whisper + Gemini