The next major evolution in AI will be models that are personalized for specific users or companies and update their knowledge daily from interactions. This contrasts with current monolithic models like ChatGPT, which are static and must store irrelevant information for every user.

Instead of being stuck with rigid software, a future powered by decentralized AI could allow users to modify their tools directly. For example, a doctor frustrated with an electronic medical record system could use natural language to instantly change the software to fit their workflow, reclaiming control over their digital environment.

AI is becoming the new UI, allowing users to generate bespoke interfaces for specific workflows on the fly. This fundamentally threatens the core value proposition of many SaaS companies, which is essentially selling a complex UX built on a database. The entire ecosystem will need to adapt.

A huge portion of product development involves creating user interfaces for backend databases. AI-powered inference engines will allow users to state complex goals in natural language, bypassing the need for traditional UIs and fundamentally changing software development.

While chatbots are an effective entry point, they are limiting for complex creative tasks. The next wave of AI products will feature specialized user interfaces that combine fine-grained, gesture-based controls for professionals with hands-off automation for simpler tasks.

The surprising success of Dia's custom "Skills" feature revealed a huge user demand for personalized tools. This suggests a key value of AI is enabling non-technical users to build "handmade software" for their specific, just-in-time needs, moving beyond one-size-fits-all applications.

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.

AI will fundamentally change user interfaces. Instead of designers pre-building UIs, AI will generate the necessary "forms and lists" on the fly based on a user's natural language request. This means for the first time, the user, not the developer, will be the one creating the interface.

While the internet has consolidated around major platforms, AI presents a counter-force. By drastically lowering the cost and complexity of building mobile apps, new tools could enable a 'Cambrian explosion' of personalized applications, challenging the one-size-fits-all model.