AI-powered "vibe coding" is reversing the design workflow. Instead of starting in Figma, designers now build functional prototypes directly with code-generating tools. Figma has shifted from being the first step (exploration) to the last step (fine-tuning the final 20% of pixel-perfect details).

Initial data suggested the market for design tools was too small to build a large business. Figma's founders bet on the trend that design was becoming a key business differentiator, which would force the market to expand. They focused on building for the trend, not the existing TAM.

Early user research showed designers did not want a collaborative, multiplayer tool. However, Figma's web-based architecture made a single-player experience technically terrible (e.g., tabs constantly reloading). They were forced by the technology to build multiplayer functionality, which ultimately became their key differentiator, proving the platform's needs can override initial user requests.

Early versions of Figma failed to gain traction because designers, its target users, fundamentally didn't trust the tool's own subpar visual design. This meta-problem highlights that for a tool to be credible to its expert users, its own execution must embody the principles it espouses. A redesign was the key to unlocking user trust and adoption.

When FigJam felt soulless a month before launch, the team made a controversial decision to differentiate it by making it fun. This seemed frivolous but was strategically crucial for encouraging participation and creative expression in brainstorming sessions, especially during the remote-work era.

In AI, low prototyping costs and customer uncertainty make the traditional research-first PM model obsolete. The new approach is to build a prototype quickly, show it to customers to discover possibilities, and then iterate based on their reactions, effectively building the solution before the problem is fully defined.

Figma learned that removing issues preventing users from adopting the product was as important as adding new features. They systematically tackled these blockers—often table stakes features—and saw a direct, measurable improvement in retention and activation after fixing each one.

Historically, resource-intensive prototyping (requiring designers and tools like Figma) was reserved for major features. AI tools reduce prototype creation time to minutes, allowing PMs to de-risk even minor features with user testing and solution discovery, improving the entire product's success rate.

Despite Figma's massive success, Dylan Field considers their long pre-monetization period a mistake. The company started in 2012 but didn't earn its first revenue until 2017. He strongly advises founders against this path, emphasizing the need to ship and learn from the market more quickly.