Michael Crawford is Vice President of Strategic Initiatives at America Succeeds, the nonprofit that popularized the term “durable skills” and built the employer-informed framework now used to develop them across K-12, higher education, and the workforce. Our conversation starts with the quote on Michael’s LinkedIn banner, “do not be afraid of work that has no end”, and the idea threads through everything that follows. We talk about why naming a skill is the precondition for developing it (”name it to tame it”), what America Succeeds learned studying a dozen high schools that do this well, and why the line between school and “the real world” is more porous than we assume. Then the harder part: as AI automates the clear-cut technical work, human skills grow more valuable, yet compared to technical skills and knowledge retention they are harder to assess. Michael describes these skills as living in the gray, where real-world evidence beats standardized tests, and the goal isn’t a perfect measure but a steadily better one.
Takeaways
Naming is the precondition for developing. You can’t teach or measure a skill you haven’t named. The schools doing this best make their skills explicit: on posters, in rubrics, in language students can articulate. That’s what opens a skill up to investment and measurement.
Name it, make it authentic, integrate it. Beyond naming, effective schools build authentic experiences — internships, client projects, not the poster board tossed after class — and weave skills throughout rather than bolting on a module. It works best when schools act as porous community institutions, letting parents, employers, and students help define what’s worth developing.
AI raises the value of durable skills but tempts us to game them. As AI automates technical work, skills such as judgment, communication, and creativity become relatively more valuable. But the moment these skills drive high-stakes decisions, Campbell’s Law kicks in, and could lead to test prep and coached performance on these durable skills. The fix is evidence and triangulation (portfolios, references, real work).
These skills live in the gray, and that’s largely the whole point. Unlike a fact with a right answer, durable skills operate in probability. The aim isn’t a perfect measure but a steadily better one. That irreducible gray is part of what keeps them human, and why the work of developing them has no end.
