As AI agents become the primary 'users' of software, design priorities must change. Optimization will move away from visual hierarchy for human eyes and toward structured, machine-legible systems that agents can reliably interpret and operate, making function more important than form.

The 1956 Dartmouth Conference proposal and early connectionists assumed AI would be created by first precisely describing human intelligence and then simulating it. In reality, deep learning evolved to reverse-engineer cognitive functions without a pre-existing human understanding, a 180-degree turn from original expectations.

Liskov developed her famous principle by analyzing Smalltalk's inheritance. Her research group focused on defining modules by their specified behavior, not their internal implementation. This perspective allowed her to solve a problem the implementation-focused OOP community was struggling with: a subclass must behave like its superclass to be substitutable.

The idea that design systems stifle creativity stems from the high cost of re-coding components after a design change. In a world with a single source of truth, where design changes automatically update the code, this cost disappears, allowing systems to be radically changed without engineering overhead.

The classic domain-model hierarchy in OOP is architecturally weak because many essential features, like multi-selecting and editing a common property (e.g., color), are cross-cutting. This forces developers to pollute the base class with accessors, breaking the encapsulation the hierarchy was meant to provide.

The famous quote wasn't a license to ignore performance. It was a corrective for 1970s programmers who over-indexed on low-level tricks, neglecting the growing need for maintainability and structured design during the era's "software crisis."

The worst code often stems from detailed upfront design. Architects simply cannot hold all the system's complexities in their heads, leading to designs that are disconnected from the practical realities discovered only during implementation. This results in convoluted and inefficient code.

Projects like Rio OS, which recreate old operating systems, show that fundamental UI concepts—windows, text editors, icons—are timeless. Despite massive technological leaps, we are still using the same core patterns established decades ago. This suggests that lasting design focuses on these enduring interaction models rather than fleeting trends.

Instead of designing an abstract API first, build the core, functional code (e.g., a rasterizer). Then, create the API by abstracting the patterns from that working implementation. This bottom-up approach ensures the final API is practical and well-suited to the actual problem.