Platform Risk: How AI Founders Navigate the Threat of Becoming a Feature

The competitive landscape for AI startups has shifted in a fundamental way. Rather than fearing other founders, many are now watching the foundation model companies—OpenAI, Anthropic, Google—with greater concern. Each major platform release raises an uncomfortable possibility: the differentiated feature you've invested months or years developing could be absorbed into the base product, overnight.

This threat is reshaping how AI companies approach product strategy, capital raising, and long-term valuation. The strategic question has evolved from "Can we build it?" to "Can we still own it?" The implications ripple through every decision founders make about where to invest engineering effort and how to articulate defensibility to investors.

At TechCrunch Disrupt 2026, taking place October 13–15 at Moscone West in San Francisco, a Builders Stage session titled "What Happens When OpenAI Ships Your Roadmap" will bring together Michel Tricot, CEO and Co-founder of Airbyte; Rob Toews, Partner at Radical Ventures; and Linda Tong, CEO of Webflow, to examine this challenge from three angles. The event draws 10,000+ founders, investors, and operators for 250+ sessions on how startups are built and scaled.

When products become features

The core risk is straightforward: as foundation models evolve rapidly, capabilities that once set an AI startup apart can quickly become baseline expectations. Founders increasingly find themselves competing not just with other startups but with the platforms themselves.

The winners in the next phase of AI may not be determined by the quality of their underlying models. Instead, they'll be separated by what models cannot easily replicate: proprietary datasets, embedded customer workflows, established relationships, specialized domain knowledge, and earned trust. The question founders must answer is whether customers will continue to find value in what they've built after the next model release arrives.

This session will explore where defensibility remains possible, how founders should respond when AI giants expand into adjacent spaces, and what distinguishes companies that avoid becoming features from those that remain independent businesses.

Three perspectives on AI's biggest strategic question

The Builders Stage brings together a founder, an operator, and an investor to examine how lasting value gets created when the underlying technology shifts constantly.

Building durable infrastructure beyond the model

Michel Tricot has built his career around data integration infrastructure that supports analytics, operations, and AI systems. At Airbyte, which he co-founded and leads as CEO, the open-source platform now serves more than 7,000 customers, including 18% of the Fortune 500. His experience offers direct insight into where sustainable businesses are constructed in the AI era.

Maintaining differentiation as AI reshapes expectations

Linda Tong, as CEO of Webflow, is steering one of the industry's most prominent visual development platforms through a major technology transition. Her background includes leadership roles at Google, Cisco, and the NFL, providing practical perspective on how to evolve products while preserving competitive advantage.

Identifying defensibility from an investor's view

Rob Toews evaluates AI startups regularly as a Partner at Radical Ventures, assessing where competitive advantages genuinely exist and where products face the risk of becoming features. His perspective addresses what convinces investors that an AI company will retain relevance years into the future.

Building lasting defensibility as models improve

Foundation models will continue advancing—that outcome is certain. As OpenAI and Anthropic expand their capabilities, founders must determine how they'll maintain differentiation. The companies that lead in the next era of AI will be those built on elements the models themselves cannot easily replicate: the workflows they enable, the data they control, the specific problems they solve, and the trust they've cultivated.

Rather than reacting to each new model release, this session will examine where defensibility persists, what enterprise and startup buyers actually value, and how to construct companies that remain relevant as AI evolves. The greatest danger isn't building a weak product—it's building a strong one that eventually becomes someone else's feature. For founders building AI companies, the question isn't whether foundation models will continue to improve. It's whether your company will continue creating value as they do.