AI disproportionately benefits people who are competent but not expert in a given area. The key requirement is knowing enough to tell the difference between hallucination and sound advice — you don’t need deep expertise, but you do need enough judgement to evaluate what AI gives you.
This means you can get a lot of mileage out of being adjacent to a skill rather than deep in it. A UI-focused full-stack engineer can use AI to become genuinely capable on the back-end — not just scraping by, but producing solid work. The same applies in reverse: a back-end engineer with some frontend intuition can lean on AI to close the gap and ship polished interfaces.
The effect extends beyond technical sub-disciplines. An engineer with some product sense or UX ability can use AI to strengthen those muscles too — writing better specs, thinking through user flows, pressure-testing assumptions. The gaps between traditionally separate roles shrink.
Jakob Nielsen observed exactly this in Rebirth of the UX Unicorn: empirical studies consistently show that AI narrows the performance gap between specialists and generalists. The floor rises for everyone, but it rises fastest for the people who were already competent enough to ask the right questions.
This is why Being T shaped becomes increasingly powerful. The horizontal bar of the T — breadth across adjacent domains — is exactly the territory where AI has the most leverage.