Frontier is designed to be a central hub for deploying and managing AI agents across enterprise systems. This positions OpenAI to become the primary user interface for work, potentially demoting established SaaS tools like CRMs to mere data repositories.

AI agents make it dramatically easier to extract and migrate data from platforms, reducing vendor lock-in. In response, platforms like Snowflake are embracing open file formats (e.g., Iceberg), shifting the competitive basis from data gravity to superior performance, cost, and features.

Snowflake's CEO views giants like OpenAI as "empires that have not met their oceans"—believing they can expand anywhere. To compete, companies must identify and avoid areas where these platforms have a natural 'right to win' (like coding agents), and instead build differentiated value elsewhere.

The ability for AI agents to access and operate on a SaaS platform's data is becoming critical. Companies that lock down their data risk being isolated, while those with open data APIs will become part of the new AI ecosystem, even if it means ceding the primary 'workspace' layer.

OpenAI CEO Sam Altman now publicly hedges that winning requires the best models, product, *and* infrastructure. This marks a significant industry-wide shift away from the earlier belief that a sufficiently advanced model would make product differentiation irrelevant. The focus is now on the complete, cohesive user experience.

OpenAI's new platform, Frontier, is designed for building 'AI co-workers' that can access a company's various data sources and systems. This represents a strategic move beyond single-user chatbots toward an enterprise-grade orchestration layer for managing teams of interconnected AI agents.

Value in the AI stack will concentrate at the infrastructure layer (e.g., chips) and the horizontal application layer. The "middle layer" of vertical SaaS companies, whose value is primarily encoded business logic, is at risk of being commoditized by powerful, general AI agents.

Snowflake's CEO warns that traditional software firms with walled-garden data models are vulnerable. If they don't develop their own compelling agentic interfaces, they risk being reduced to mere data sources for dominant AI platforms, losing their customer relationship and pricing power.

The current market of specialized AI agents for narrow tasks, like specific sales versus support conversations, will not last. The industry is moving towards singular agents or orchestration layers that manage the entire customer lifecycle, threatening the viability of siloed, single-purpose startups.