Snap's $400M deal with Perplexity, paid largely in stock, pioneers a new strategy for consumer platforms. They can leverage their massive user bases as a capital asset, trading distribution for significant equity stakes in capital-rich AI startups that desperately need user growth.
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While tech giants could technically replicate Perplexity, their core business models—advertising for Google, e-commerce for Amazon—create a fundamental conflict of interest. An independent player can align purely with the user's best interests, creating a strategic opening that incumbents are structurally unable to fill without cannibalizing their primary revenue streams.
Tech giants like Google and Meta are positioned to offer their premium AI models for free, leveraging their massive ad-based business models. This strategy aims to cut off OpenAI's primary revenue stream from $20/month subscriptions. For incumbents, subsidizing AI is a strategic play to acquire users and boost market capitalization.
The partnership where OpenAI becomes an equity holder in Thrive Holdings suggests a new go-to-market model. Instead of tech firms pushing general AI 'outside-in,' this 'inside-out' approach embeds AI development within established industry operators to build, test, and improve domain-specific models with real-world feedback loops.
The AI fundraising environment is fueled by investors' personal use of the products. Unlike B2B SaaS where VCs rely on customer interviews, they directly experience the value of tools like Perplexity. This firsthand intuition creates strong conviction, contributing to a highly competitive investment landscape.
The massive OpenAI-Oracle compute deal illustrates a novel form of financial engineering. The deal inflates Oracle's stock, enriching its chairman, who can then reinvest in OpenAI's next funding round. This creates a self-reinforcing loop that essentially manufactures capital to fund the immense infrastructure required for AGI development.
Perplexity's CEO argues that building foundational models is not necessary for success. By focusing on the end-to-end consumer experience and leveraging increasingly commoditized models, startups can build a highly valuable business without needing billions in funding for model training.
Companies like Snap are in a "crucible moment," stuck between tech giants and nimble startups. They face the high operational costs of a large user base without the revenue or market power of giants, creating intense pressure to innovate and operate efficiently.
Recent acquisitions of slow-growth public SaaS companies are not just value grabs but turnaround plays. Acquirers believe these companies' distribution can be revitalized by injecting AI-native products, creating a path back to high growth and higher multiples.
Similar to how mobile gave rise to the App Store, AI platforms like OpenAI and Perplexity will create their own ecosystems for discovering and using services. The next wave of winning startups will be those built to distribute through these new agent-based channels, while incumbents may be slow to adapt.
Instead of short-term data licensing deals, Perplexity is building a publisher program that shares ad revenue on a query-level basis. This Spotify-inspired model creates a long-term, symbiotic relationship, incentivizing publishers to partner with the AI platform.