Next-generation hardware companies like SpaceX now operate like software firms, with designs and requirements changing daily. This departure from the rigid, top-down 'waterfall' process creates a new market for agile collaboration tools, analogous to how GitHub emerged to serve agile software teams.

Counterintuitively, the "move fast and break things" mantra fails in hardware. Mock Industries achieved a 71-day aircraft development cycle not by rushing tests, but by investing heavily in software and hardware-in-the-loop simulation to run thousands of virtual cases before the first physical flight.

For companies like NVIDIA or Google, moving from TSMC to Intel or Samsung is not a simple supplier switch. It necessitates a complete redesign of the chip's architecture to fit the new foundry's technology. This complex and costly process can take one to two years, making it a last resort.

Software companies struggle to build their own chips because their agile, sprint-based culture clashes with hardware development's demands. Chip design requires a "measure twice, cut once" mentality, as mistakes cost months and millions. This cultural mismatch is a primary reason for failure, even with immense resources.

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.

Unlike software, hardware iteration is slow and costly. A better approach is to resist building immediately and instead spend the majority of time on deep problem discovery. This allows you to "one-shot" a much better first version, minimizing wasted cycles on flawed prototypes.

The traditional, linear handoff from product spec to design to code is collapsing. Roles and stages are blurring, with interactive prototypes replacing static documents and the design file itself becoming the central place for the entire team to align and collaborate.

True co-design between AI models and chips is currently impossible due to an "asymmetric design cycle." AI models evolve much faster than chips can be designed. By using AI to drastically speed up chip design, it becomes possible to create a virtuous cycle of co-evolution.

The current 2-3 year chip design cycle is a major bottleneck for AI progress, as hardware is always chasing outdated software needs. By using AI to slash this timeline, companies can enable a massive expansion of custom chips, optimizing performance for many at-scale software workloads.