In today's hype-driven AI market, founders must ignore 'false signals' like media attention and investor interest. These metrics have zero, or even negative, correlation with building a useful product. The only signal that matters is genuine user love and feedback from actual customers.

Higgsfield's controversial use of copyrighted characters and celebrity deepfakes points to a huge market demand for unrestricted AI models, similar to the demand for free music during the Napster era. While illegal, this user behavior signals a massive, untapped business opportunity for companies that can eventually license the content and provide a legitimate service to meet this demand.

Higgsfield initially saw high adoption for viral, consumer-facing AI features but pivoted. They realized foundation model players like OpenAI will dominate and subsidize these markets. The defensible startup strategy is to ignore consumer virality and solve specific, monetizable B2B workflow problems instead.

AI video startup Higgs Field deliberately uses shocking content, misleading marketing (like passing stock video as AI), and controversial social media strategies to generate attention. This "rage bait" approach has fueled explosive revenue growth to a $300M run rate in under a year, but also exposes the company to significant backlash and platform risk.

Video-gen startup Higgs Field achieved unprecedented hypergrowth by evolving beyond its initial base of casual content creators. The company now reports that 85% of its usage comes from social media managers who treat the platform as essential production infrastructure for their entire workflow.

Days after the controversy over generating child sexual abuse material erupted, xAI successfully raised $20 billion, surpassing its $15 billion goal. This demonstrates that for some investors, aggressive, boundary-pushing growth and compute acquisition are more critical than immediate ethical concerns or the lack of robust safety guardrails.

The narrative of "0 to $100M in a year" often reflects a startup's dependence on a larger, fast-growing customer (like an AI foundation model company) rather than intrinsic product superiority. This growth is a market anomaly, similar to COVID testing labs, and can vanish as quickly as it appeared when competition normalizes prices and demand shifts.

Many companies market AI products based on compelling demos that are not yet viable at scale. This 'marketing overhang' creates a dangerous gap between customer expectations and the product's actual capabilities, risking trust and reputation. True AI products must be proven in production first.

A core conceit of fraud is faking business growth. Consequently, fraudulent enterprises often report growth rates that dwarf even the most successful legitimate companies. For example, the fraudulent 'Feeding Our Future' program claimed a 578% CAGR, more than double Uber's peak growth rate. This makes sorting by growth an effective detection method.