As AI agents become primary consumers of documentation, the battle for superior developer experience shifts from visual design to content accuracy. An agent reading raw markdown doesn't care about UI, making the underlying information paramount and the foundation of a modern DevEx strategy.

There are two competing philosophies in the AI tool space: one aims to automate development entirely, while the other empowers users. Netlify is betting on the latter, building tools that treat the user as a developer, augmenting their abilities to create a massive new wave of builders.

The next generation of software may lack traditional user interfaces. Instead, they will be 'API-first' or 'agent-first,' integrating directly into existing workflows like Slack or email. Software will increasingly 'visit the user' rather than requiring the user to visit a dashboard.

A truly "AI-native" product isn't one with AI features tacked on. Its core user experience originates from an AI interaction, like a natural language prompt that generates a structured output. The product is fundamentally built around the capabilities of the underlying models, making AI the primary value driver.

The end state for enterprise AI is a unified, conversational agent serving as the primary interface for a brand. This "digital concierge" will handle sales, support, and other interactions, potentially replacing websites and mobile apps as the main customer touchpoint.

The best agentic UX isn't a generic chat overlay. Instead, identify where users struggle with complex inputs like formulas or code. Replace these friction points with a native, natural language interface that directly integrates the AI into the core product workflow, making it feel seamless and powerful.

Intercom's CEO predicts that companies will abandon separate AI agents for sales, service, and onboarding. A single, coordinated "customer agent" is necessary to avoid conflicting goals and create a seamless, high-touch experience for every user.

A new software paradigm, "agent-native architecture," treats AI as a core component, not an add-on. This progresses in levels: the agent can do any UI action, trigger any backend code, and finally, perform any developer task like writing and deploying new code, enabling user-driven app customization.

As foundational AI models become commoditized, the key differentiator is shifting from marginal improvements in model capability to superior user experience and productization. Companies that focus on polish, ease of use, and thoughtful integration will win, making product managers the new heroes of the AI race.