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 will make the traditional "product pod" structure obsolete for design. Designers, empowered to learn contexts faster and cover more ground, will operate in a more fluid, centralized team. They will be deployed across entire user journeys that span multiple teams, rather than being calcified within a single product area.
Industry leaders from LinkedIn and Salesforce predict that AI will automate narrow, specialized tasks, fundamentally reshaping careers. The future workforce will favor 'professional generalists' who can move fluidly between projects and roles, replacing rigid departmental structures with dynamic 'work charts.'
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.
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.
AI reverses the long-standing trend of professional hyper-specialization. By providing instant access to specialist knowledge (e.g., coding in an unfamiliar language), AI tools empower individuals to operate as effective generalists. This allows small, agile teams to achieve more without hiring a dedicated expert for every function.
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.
AI's rise means traditional product roles are merging. Instead of identifying as a PM or designer, focus on your core skills (e.g., visual aesthetics, systems thinking) and use AI to fill gaps. This 'builder' mindset, focused on creating end-to-end, is key for future relevance.
The traditional "assembly line" model of product development (PM -> Design -> Eng) fails with AI. Instead, teams must operate like a "jazz band," where roles are fluid, members "riff" off each other's work, and territorialism is a failure mode. PMs might code and designers might write specs.
Powerful AI assistants are shifting hiring calculus. Rather than building large, specialized departments, some leaders are considering hiring small teams of experienced, curious generalists. These individuals can leverage AI to solve problems across functions like sales, HR, and operations, creating a leaner, more agile organization.