In large enterprises, AI adoption creates a conflict. The CTO pushes for speed and innovation via AI agents, while the CISO worries about security risks from a flood of AI-generated code. Successful devtools must address this duality, providing developer leverage while ensuring security for the CISO.

Vercel is building infrastructure based on a threat model where developers cannot be trusted to handle security correctly. By extracting critical functions like authentication and data access from the application code, the platform can enforce security regardless of the quality or origin (human or AI) of the app's code.

Contrary to fears that AI would replace security firms, the consensus has shifted. Analysts now believe AI massively increases the surface area for vulnerabilities, compounding the need for security. This creates a multi-billion dollar opportunity for firms protecting new AI-driven attack vectors, making cyber a resilient software sector.

The emergence of AI that can easily expose software vulnerabilities may end the era of rapid, security-last development ('vibe coding'). Companies will be forced to shift resources, potentially spending over 50% of their token budgets on hardening systems before shipping products.

As AI generates more code, the developer tool market will shift from code editors to platforms for evaluating AI output. New tools will focus on automated testing, security analysis, and compliance checks to ensure AI-generated code is production-ready.

The core value proposition of no-code platforms—building software without code—is being eroded by AI tools. AI-assisted 'vibe coding' makes it much easier for non-specialists to build internal line-of-business apps, a key use case for no-code, posing an existential threat to major players.

An AI agent capable of operating across all SaaS platforms holds the keys to the entire company's data. If this "super agent" is hacked, every piece of data could be leaked. The solution is to merge the agent's permissions with the human user's permissions, creating a limited and secure operational scope.

As autonomous agents become prevalent, they'll need a sandboxed environment to access, store, and collaborate on enterprise data. This core infrastructure must manage permissions, security, and governance, creating a new market opportunity for platforms that can serve as this trusted container.

While AI accelerates the creation of UIs and features, it's ill-suited for critical infrastructure like authentication and compliance. WorkOS provides these enterprise-ready components as a service, allowing startups to quickly sell up-market without spending years building the unglamorous but essential security foundations.