The traditional design-to-engineering handoff is plagued by tedious pixel-pushing. As AI coding tools empower designers to make visual code changes themselves, they will reject this inefficient back-and-forth, fundamentally changing team workflows.

AI's productivity gains mean that on a lean, early-stage team, there is little room for purely specialized roles. According to founder Drew Wilson, every team member, including designers, must be able to contribute directly to the codebase. The traditional "design artifact" workflow is too slow.

To adapt to AI-driven workflows, Microsoft's LinkedIn combined product managers, designers, and engineers into a single "full stack builder" role. This structural change eliminates communication bottlenecks and empowers individuals to leverage AI tools for end-to-end product development, drastically increasing speed.

AI empowers coders, designers, and product managers to perform each other's core tasks. This creates a "Mexican standoff" where individuals in each role believe they no longer need the other two, fundamentally changing team structures.

Dylan Field predicts that AI tools will blur the lines between design, engineering, and product management. Instead of siloed functions, teams will consist of 'product builders' who can contribute across domains but maintain a deep craft in one area. Design becomes even more critical in this new world.

The traditional tech team structure of separate product, engineering, and design roles is becoming obsolete. AI startups favor small teams of 'polymaths'—T-shaped builders who can contribute across disciplines. This shift values broad, hands-on capability over deep specialization for most early-stage roles.

AI tooling is creating a 'fluid model' where any employee, regardless of role, can potentially ship code. This dramatically expands the design system team's responsibility, which must now create tooling and guardrails to support a much broader and less technical user base across the entire organization.

AI co-pilots have accelerated engineering velocity to the point where traditional design-led workflows are now the slowest part of product development. In response, some agile teams are flipping the process, having engineers build a functional prototype first and then creating formal Figma designs and UI polish later.

AI tools are collapsing the traditional moats around design, engineering, and product. As PMs and engineers gain design capabilities, designers must reciprocate by learning to code and, more importantly, taking on strategic business responsibilities to maintain their value and influence.