In the early days, Synthesia and peers decided "Generative AI" sounded too geeky and collectively chose to brand the space as "Synthetic Media." They later regretted this as "Generative AI" became the dominant term, costing them significant SEO advantages and brand association built over four years.

Related Insights

Fal strategically chose not to compete in LLM inference against giants like OpenAI and Google. Instead, they focused on the "net new market" of generative media (images, video), allowing them to become a leader in a fast-growing, less contested space.

Synthesia initially targeted Hollywood with AI dubbing—a "vitamin" for experts. They found a much larger, "house-on-fire" problem by building a platform for the billions of people who couldn't create video at all, democratizing the medium instead of just improving it for existing professionals.

Earned media is a primary source for generative AI, appearing in over 60% of brand reputation-related responses according to research. This positions PR at the center of the new "Generative Engine Optimization" (GEO) landscape, creating the most significant strategic opportunity for the industry in over a decade.

OpenAI, the initial leader in generative AI, is now on the defensive as competitors like Google and Anthropic copy and improve upon its core features. This race demonstrates that being first offers no lasting moat; in fact, it provides a roadmap for followers to surpass the leader, creating a first-mover disadvantage.

Fal strategically focused on generative media over LLMs, identifying it as a "net new" market. They reasoned that LLM inference directly competed with Google's core search business—a fight an incumbent would win at all costs. The emergent media market lacked a dominant player, creating a perfect greenfield opportunity for a startup to lead and define.

In 2015-2016, major tech companies actively avoided the term "AI," fearing it was tainted from previous "AI winters." It wasn't until around 2017 that branding as an "AI company" became a positive signal, highlighting the incredible speed of the recent AI revolution and shift in public perception.

Unlike traditional SEO, which focuses on keywords and links, GEO aims to make your brand visible in AI-generated answers. This is achieved by becoming a citable, trusted authority, which requires a blend of public relations, high-quality owned content, and technical site readiness.

The founders, not being PhD AI researchers, knew they couldn't rely on being acqui-hired by a tech giant. This perceived weakness became a strength, forcing them to relentlessly focus on finding customers and building a sustainable business from day one, unlike many research-led AI startups of that era.

Marketers must evolve from SEO to GEO, optimizing content for how brands appear in LLM results. This requires a new content strategy that treats the LLM as a distinct persona or channel, creating content specifically for it to crawl and ensuring accurate brand representation.

As users increasingly get answers from AI assistants, marketing strategy must evolve from Search Engine Optimization (SEO) to Generative Engine Optimization (GEO). This means creating diverse, authoritative content across multiple platforms (podcasts, PR, articles) with the goal of being cited as a trusted source by AI models themselves.