Instead of hiring a 'Chief AI Officer' or an agency, the most successful GTM AI deployments empower existing top performers. Pair your best SDR, marketer, or RevOps person with AI tools, and let them learn and innovate together. This internal expertise is more valuable than any external consultant.

To find talent capable of managing an AI stack, traditional interviews are insufficient. A better test is to provide candidates with platform credits (e.g., Replit) and challenge them to build a functional agent that automates a real business task, proving their practical skills.

The talent pool for experienced AI GTM managers doesn't exist yet. Instead of hiring externally, find an internal employee—perhaps a quantitative SDR or RevOps analyst—who loves data, enjoys training systems, and is eager to manage your agents.

For roles leveraging new technologies like AI, where tools are nascent and constantly changing, competency is a fleeting metric. Instead, hire for curiosity. A curious mind will adapt, learn, and master new tools as they emerge, making them a more valuable long-term asset.

Dreamer's hiring process now evaluates an engineer's ability to work with and through AI coding agents. Beyond a basic coding screen, the main interview involves a project built using tools like Codex, testing the candidate's skill in prompting, reviewing, and orchestrating AI to be productive.

To build an AI-native team, shift the hiring process from reviewing resumes to evaluating portfolios of work. Ask candidates to demonstrate what they've built with AI, their favorite prompt techniques, and apps they wish they could create. This reveals practical skill over credentialism.

Instead of immediately seeking outside consultants, leaders should identify and empower employees who are already using AI effectively. This validates their initiative, leverages existing knowledge, and provides them with a clear path for professional development and company-wide impact.

With AI tools being so new, no external "experts" exist. OpenAI's Chairman argues that the individuals best positioned to lead AI adoption are existing employees. Their deep domain knowledge, combined with a willingness to learn the new technology, makes them more valuable than any outside hire. Call center managers can become "AI Architects."

In rapidly evolving fields like AI, pre-existing experience can be a liability. The highest performers often possess high agency, energy, and learning speed, allowing them to adapt without needing to unlearn outdated habits.