Instead of merely 'sprinkling' AI into existing systems for marginal gains, the transformative approach is to build an AI co-pilot that anticipates and automates a user's entire workflow. This turns the individual, not the software, into the platform, fundamentally changing their operational capacity.

AI is fundamentally changing SaaS interaction. Instead of users clicking buttons to take action, AI will perform the tasks. The UI will then transform into a surface where users primarily review AI-driven outcomes, get insights, and make corrections, often interacting via conversational language.

The key product innovation of Agent Skills is changing the user's perception of AI. Instead of just a tool that answers questions, AI becomes a practical executor of defined workflows, making it feel less like a chat interface and more like powerful, responsive software.

Most users only scratch the surface of complex enterprise software. AI agents will bridge this gap by interpreting natural language requests and executing complex tasks on the user's behalf. This transforms the user experience from learning features to simply stating goals, unlocking decades of untapped capabilities.

Traditional enterprise software is a usability compromise designed for everyone. LLMs move beyond simple personalization (showing relevant data) to full individualization, creating unique interfaces and experiences for each user based on their role and context, finally solving the 'mega menu' problem.

AI won't just help people use applications like Excel; it will eliminate the need for them entirely. The final user interface will be a conversational agent that manages underlying data and executes complex tasks on command, making traditional software and its associated friction obsolete.

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.

The primary interface for managing AI agents won't be simple chat, but sophisticated IDE-like environments for all knowledge workers. This paradigm of "macro delegation, micro-steering" will create new software categories like the "accountant IDE" or "lawyer IDE" for orchestrating complex AI work.

The most effective application of AI isn't a visible chatbot feature. It's an invisible layer that intelligently removes friction from existing user workflows. Instead of creating new work for users (like prompt engineering), AI should simplify experiences, like automatically surfacing a 'pay bill' link without the user ever consciously 'using AI.'