Don't view AI as just a feature set. Instead, treat "intelligence" as a fundamental new building block for software, on par with established primitives like databases or APIs. When conceptualizing any new product, assume this intelligence layer is a non-negotiable part of the technology stack to solve user problems effectively.

Effective enterprise AI needs a contextual layer—an 'InstaBrain'—that codifies tribal knowledge. Critically, this memory must be editable, allowing the system to prune old context and prioritize new directives, just as a human team would shift focus from revenue growth one quarter to margin protection the next.

Don't just sprinkle AI features onto your existing product ('AI at the edge'). Transformative companies rethink workflows and shrink their old codebase, making the LLM a core part of the solution. This is about re-architecting the solution from the ground up, not just enhancing it.

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.

Enterprises are trapped by decades of undocumented code. Rather than ripping and replacing, agentic AI can analyze and understand these complex systems. This enables redesign from the inside out and modernizes the core of the business, bridging the gap between business and IT.

Legacy systems like CRMs will lose their central role. A new, dynamic 'agent layer' will sit above them, interpreting user intent and executing tasks across multiple tools. This layer, which collapses the distance between intent and action, will become the primary place where work gets done.

The future of software isn't just AI-powered features. It's a fundamental shift from tools that assist humans to autonomous agents that perform tasks. Human roles will evolve from *doing* the work to *orchestrating* thousands of these agents.

The fundamental shift from AI isn't about replacing foundational model companies like OpenAI. Instead, AI creates a new technological substrate—productized intelligence—that will engender an entirely new breed of software companies, marking the end of the traditional SaaS playbook.