Large tech companies are committee-driven and risk-averse, filtering out controversial human elements like persuasion or sexuality from their products. This creates a market opportunity for startups to build AI products, particularly in companionship, that engage with these core aspects of humanity that incumbents are afraid to touch.
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When evaluating AI startups, don't just consider the current product landscape. Instead, visualize the future state of giants like OpenAI as multi-trillion dollar companies. Their "sphere of influence" will be vast. The best opportunities are "second-order" companies operating in niches these giants are unlikely to touch.
Startups can explore core human experiences like companionship, persuasion, and sexuality that AI models can reflect. Large corporations are structurally incapable of shipping such 'weird' products because their internal committees are designed to sanitize and de-risk everything, creating a market gap for startups.
Startups like ElevenLabs and Midjourney compete with large AI labs by imbuing their models with a founder's specific 'taste.' This unique aesthetic, from voice texture to image style, creates a product identity that is difficult for a general, large-scale model to replicate.
Unlike social media's race for attention, AI companion apps are in a race to create deep emotional dependency. Their business model incentivizes them to replace human relationships, making other people their primary competitor. This creates a new, more profound level of psychological risk.
Product managers at large AI labs are incentivized to ship safe, incremental features rather than risky, opinionated products. This structural aversion to risk creates a permanent market opportunity for startups to build bold, niche applications that incumbents are organizationally unable to pursue.
YC Partner Harsh Taggar suggests a durable competitive moat for startups exists in niche, B2B verticals like auditing or insurance. The top engineering talent at large labs like OpenAI or Anthropic are unlikely to be passionate about building these specific applications, leaving the market open for focused startups.
AI services that simulate conversations with deceased loved ones, while ethically controversial, will likely achieve product-market fit. They tap into the powerful and universal human fear of loss, creating durable demand from those experiencing grief, much like how people use chatbots for companionship.
The business model for AI companions shifts the goal from capturing attention to manufacturing deep emotional attachment. In this race, as Tristan Harris explains, a company's biggest competitor isn't another app; it's other human relationships, creating perverse incentives to isolate users.
Despite massive spending and partnerships, Microsoft, Amazon, Apple, and Meta have failed to launch a defining, consumer-facing AI product. This surprising lack of execution challenges the assumption that incumbents would easily dominate the AI space, leaving the door open for native AI startups.
Investing in startups directly adjacent to OpenAI is risky, as they will inevitably build those features. A smarter strategy is backing "second-order effect" companies applying AI to niche, unsexy industries that are outside the core focus of top AI researchers.