To prevent burnout from constant AI model releases, GitHub's product leader treats his team like athletes who need rest for peak performance. This includes rotating high-stress roles, proactively increasing headcount, forcing focus on only the top three priorities, and enforcing recovery periods.

A pragmatic way to fund expensive AI tools is to reallocate the budget from headcount that leaves through natural attrition. When a GTM role departs, use their budgeted salary to fund AI agents that can scale the work of the remaining team, avoiding new budget requests and the need to fire performers.

Simply hiring superstar "Galacticos" is an ineffective team-building strategy. A successful AI team requires a deliberate mix of three archetypes: visionaries who set direction, rigorous executors who ship product, and social "glue" who maintain team cohesion and morale.

The true ROI of AI lies in reallocating the time and resources saved from automation towards accelerating growth and innovation. Instead of simply cutting staff, companies should use the efficiency gains to pursue new initiatives that increase demand for their products or services.

For established software companies with sluggish growth, the path forward is clear: find a way to become relevant in the age of AI. While they may not become the next Harvey, attaching to AI spend can boost growth from 15% to 25%, the difference between a viable public company and a sale to a private equity firm.

In the current market, AI companies see explosive growth through two primary vectors: attaching to the massive AI compute spend or directly replacing human labor. Companies merely using AI to improve an existing product without hitting one of these drivers risk being discounted as they lack a clear, exponential growth narrative.

Firing decisions should be a function of both incompetence and business constraint. Not all underperformers are equal priorities. Some are like a "trash can on fire in the driveway"—a problem, but not the company's main bottleneck. Focus firing efforts on roles that are the direct constraint to growth.

Drawing from experience at big tech, Surge AI's founder believes large organizations slow down top performers with distractions. By building a super-small, elite team, companies can achieve more with less overhead, a principle proven by Surge's own success.

While AI-driven efficiency is an obvious first step, it often results in workforce reduction if company growth is flat. True differentiation and sustainable advantage come from using AI for innovation—creating new products, markets, and business models to fuel growth.