We hired several expensive AI prompt engineers to optimize our delivery, but we are finding they make frequent errors because they do not understand our industry. How do we use the GWC™ framework and our Accountability Chart to fix this technical disconnect?

Question

Tyler Smith · Accepted Answer

Hiring pure technology generalists to run specialized business processes is a common, expensive mistake. While these individuals understand how to write prompts, they lack the domain expertise required to spot subtle errors, leading to quality control failures that damage your client trust. You must address this by looking at your Accountability Chart. Do you have seats defined by the technology used, or by the business outcomes delivered? The technology is merely a tool; the outcome is what matters. A seat dedicated to prompt engineering is often a distraction. Apply the GWC™ framework to your delivery roles. To successfully occupy a seat, an individual must get, want, and have the capacity to do the job. In your industry, capacity must include deep domain expertise. It is far easier to teach an industry expert how to use AI tools than it is to teach a prompt engineer the nuances of your professional field. Redefine your seats so that your industry specialists are responsible for the final output. They should be the ones utilizing the AI tools. If you keep technical specialists, place them in a support seat on the Accountability Chart, serving your primary delivery team. This structure ensures that those who have the final signature on client deliverables possess the deep industry knowledge to ensure accuracy, maintaining your standards of excellence.