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.

As AI handles coding, traditional tech roles will merge. At Anthropic, PMs, designers, and engineers all code. The future is a generalist "Builder" who can handle multiple disciplines, making role specialization obsolete.

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.

With AI coding assistants, the barriers to shipping software are eroding. At Ramp, designers and customer support agents are now shipping code to production. This suggests a future where the traditional, siloed Engineering, Product, and Design (EPD) team structure becomes obsolete.

AI development makes identifying the right use case and wrangling data the new bottlenecks, not coding. This flattens traditional hierarchies. The most effective teams are integrated 'tiger teams' where UX designers manage RAG files and developers talk to customers, valuing adaptability over rigid job descriptions.

AI agents empower individuals to perform tasks outside their core roles. At OpenAI, designers now write significant code, and PMs build functional prototypes. This blurs the lines between engineering, design, and product, unifying them under the umbrella of being "builders."

The new norm, enabled by AI, is that all employees, regardless of role, contribute across functions. Everyone is expected to ship code, run marketing campaigns, build apps, and promote their work on social media, in addition to their core specialty.

The creator of Claude Code prioritizes hiring generalists who possess skills beyond coding, such as product sense and a desire to talk to users. This 'full-stack' approach, where even PMs and data scientists code, fosters a more effective and versatile team.

Top engineers are no longer just coding specialists. They are hybrids who cross disciplines—combining product sense, infrastructure knowledge, design skills, and user empathy. AI handles the specialized coding, elevating the value of broad, system-level thinking.