Lovable's Tiered Release Strategy

The AI Growth Playbook: Lessons from Lovable's Hypergrowth

In the rapidly evolving AI product landscape, traditional growth strategies are being rewritten. Elena Verna, Head of Growth at Lovable, shares how the company reached $200M ARR in just one year with only 100 employees, requiring a fundamentally different approach to growth.

The New AI Growth Paradigm

• Only 30-40% of traditional growth playbooks transfer to AI companies
• The focus shifts dramatically from optimization to innovation:
  • Traditional companies: 95% optimization, 5% innovation
  • AI companies: 5% optimization, 95% innovation
• Growth teams must go deeper into core product functionality rather than just "smoothing the outer layers"
• The pace of change requires constant reinvention rather than incremental improvement

Key Growth Levers for AI Products

1. Build a Minimum Lovable Product (MLP)

• Replace "minimum viable product" with "minimum lovable product"
• Focus on creating emotional connections and moments of delight
• Prioritize experiences that "blow people's socks off" to drive word-of-mouth
• Embed brand values into every product interaction
• Design for humanity over pure utility

2. Ship Constantly and Build in Public

• Maintain continuous "noise in the market" through frequent shipping
  • Ship marketable features daily or multiple times per day
  • Empower engineers to announce their own features (product engineers)
  • Use a tiered release approach:
    • Tier 1: Major launches that step-function change product-market fit
    • Tier 2-3: Smaller, continuous improvements that maintain momentum
  • Build in public through founder and employee social sharing
  • Create a sense that "the product is alive" and constantly evolving

3. Give Your Product Away Strategically

• Treat free product usage as a marketing expense, not a margin drain
• Remove barriers to entry, especially for those who will evangelize your product
• Support hackathons, events, and user initiatives with free credits
• Recognize that AI costs are marketing costs, not just COGS
• Shift spending from traditional marketing to product-led growth

4. Leverage Social Over Search

• The organic marketing strategy has shifted from SEO to social media
• Focus on founder-led socials, employee sharing, and customer stories
• Prioritize platforms where your audience congregates (X/Twitter, LinkedIn for B2B)
• Show authentic personality rather than corporate messaging
• Influencer marketing often outperforms paid social for AI products

5. Build and Nurture Community

• Create spaces for users to share what they're building
• Enable users to help each other and amplify word-of-mouth
• Use community to drive both acquisition and retention
• Develop ambassador programs to extend reach

The Product-Market Fit Treadmill

• Product-market fit is no longer a one-time achievement but requires constant recapture
• The recapture cycle has compressed from years to just 3 months due to:
  • Rapidly evolving AI capabilities with each new model release
  • Quickly shifting consumer expectations
• Companies must simultaneously:
  • Build for capabilities that don't exist yet
  • Adapt to changing user expectations
  • Maintain growth momentum
• This creates a tension between scaling existing product-market fit and finding the next one

Team Structure and Hiring

• Hire for passion, high agency, and autonomy over traditional credentials
• Look for people who can create clarity from chaos
• Consider new graduates who are "AI native" as they bring fresh perspectives
• Value failed founders who understand how to operate with high autonomy
• Use work trials and probation periods to ensure cultural fit
• Empower teams to make decisions without excessive supervision

Operational Approaches

• Use AI tools extensively within the company (eat your own dog food)
• Prototype everything on your own platform before building
• Question what AI can do first, then determine where humans add value
• Use AI for brainstorming, meeting summaries, and customer support
• Maintain work-life boundaries by prioritizing rather than balancing

The AI growth playbook requires embracing constant change, focusing on emotional connections with users, and building in ways that generate organic enthusiasm. Success comes not from optimization but from continuous reinvention and creating experiences worth talking about.