AI has forever changed the structure and economics of software. * The myth: AI will let us one-shot everything from scratch, making SaaS, open-source libraries, and frameworks obsolete.
* The reality: AI makes good components and abstractions more valuable than ever before, because it unbundles the knowledge within them and lowers the cost of assembling them.

Real-world problems are complex, and both nature and humans solve them by dividing them up in hierarchical, fractal, and iterated ways. Systems — biological, mechanical, or digital — are built on layers of robust components, which themselves encode the results of earlier feedback loops. Abstraction, encapsulation, and modularity aren’t just concessions to limited human cognition; they are part of the physics of successful systems. There is no compression algorithm for experience, and AI makes components that encode experience more valuable, not less.

This talk offers concrete predictions about how AI will reshape the software landscape and make the fundamental principles of systems and software engineering even more required:

* For SaaS: Value shifts from simple glue to complex encoded domain knowledge, composability, efficiency, and operational expertise. Procurement collapses from enterprise sales cycles to agent-driven assembly of components.

* For Software Engineering: Teams shrink and roles widen. TDD / BDD, compiled and strongly-typed languages, observability, and progressive delivery all become more important.

Come for the myth-busting, stay for the practical framework.