For AI-native products where the primary interface is just a prompt box, the traditional role of a growth team in optimizing activation diminishes. The entire activation experience happens via conversation with an AI agent, making it an inseparable part of the core product's responsibility, not a separate optimization layer.

Unlike traditional software development, AI-native founders avoid long-term, deterministic roadmaps. They recognize that AI capabilities change so rapidly that the most effective strategy is to maximize what's possible *now* with fast iteration cycles, rather than planning for a speculative future.

Most companies use AI for optimization—making existing processes faster and cheaper. The greater opportunity is innovation: using AI to create entirely new forms of value. This "10x thinking" is critical for growth, especially as pure efficiency gains will ultimately lead to a reduced need for human workers.

At Lovable, the growth team barely focuses on activation, a typical growth lever. Instead, the core product and AI agent teams own this obsessively. Because the initial AI-generated output *is* the activation moment, its quality is a fundamental product challenge, not a surface-level optimization problem for growth.

Fal treats every new model launch on its platform as a full-fledged marketing event. Rather than just a technical update, each release becomes an opportunity to co-market with research labs, create social buzz, and provide sales with a fresh reason to engage prospects. This strategy turns the rapid pace of AI innovation into a predictable and repeatable growth engine.

While traditionally creating cultural friction, separate innovation teams are now more viable thanks to AI. The ability to go from idea to prototype extremely fast and leanly allows a small team to explore the "next frontier" without derailing the core product org, provided clear handoff rules exist.

The rapid pace of AI makes traditional, static marketing playbooks obsolete. Leaders should instead foster a culture of agile testing and iteration. This requires shifting budget from a 70-20-10 model (core-emerging-experimental) to something like 60-20-20 to fund a higher velocity of experimentation.

Lovable's growth is fueled by maintaining constant "noise in the market" through a high velocity of feature shipments announced daily by the entire team, including engineers. This strategy makes the product feel alive, creates a powerful re-engagement loop, and gives the community a steady stream of things to discuss.

The most durable growth comes from seeing your job as connecting users to the product's value. This reframes the work away from short-term, transactional metric hacking toward holistically improving the user journey, which builds a healthier business.