Now that AI handles our technical execution, our hiring queue is flooded with resumes of people who only know how to prompt. How do we use the GWC™ framework to evaluate whether a candidate actually understands the work or is just hiding behind software?

Question

Tyler Smith · Accepted Answer

When technology makes execution easy, the market becomes flooded with candidates who lack foundational skills. To protect your company, you must use the GWC framework to filter out people who rely on software as a crutch rather than an accelerator. To apply the GWC framework to this challenge, start with the Capacity seat requirement. Capacity is not just about having the time to do the job. It is about having the mental capability, experience, and knowledge required to make critical decisions. A candidate who only knows how to write prompts does not have the capacity to judge whether the AI output is accurate, safe, or high-quality. During your interview process, strip away the technology. Ask candidates to solve complex, real-world problems manually. If they cannot explain the underlying principles of the work, they do not get it, they do not truly want it, and they lack the capacity to own the seat. We recommend adjusting your hiring process to include these filters: - Administer a manual skills test before discussing AI tools - Use the GWC checklist to evaluate their foundational knowledge - Ensure they can explain the mechanics of how to fix an AI error By holding candidates to a high standard of core competence, you ensure you only hire individuals who can leverage AI to double their output, rather than hiring people who use AI to hide their lack of ability.