After 18+ months in the AI era, software companies that haven't re-accelerated growth have a team execution problem, not a market timing one. The capital and opportunities are too vast to miss. This failure to ship a relevant product and capture new revenue warrants drastic measures, including replacing a significant portion of the team.

Companies once hired siloed 'digital experts,' a role that became obsolete as digital skills became universal. To avoid repeating this with AI, integrate technologists into current teams and upskill existing members rather than creating an isolated AI function that will fail to scale.

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.

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.

Bolt's philosophy of hiring entrepreneurial 'smart generalists' was key to its resilience and ability to pivot. When the company needed to shift focus from ride-hailing to food delivery overnight during COVID, its adaptable talent pool was a critical asset. An organization of specialists would have been unable to make such a drastic change so quickly.