> High-performing teams have always managed technical debt intentionally. As AI is adopted by startups and large companies, the question becomes how teams will manage cognitive debt.

"Technical" and "cognitive" debt aren't really distinct phenomena; the spirit of the original definition of "technical debt" was that it WAS the delta between the system-as-it-is, and the human understanding of how best to solve whatever problem the system was intended to solve [1].

If we accept collapsing them back down to one term, then "managing cognitive debt" is the same thing as "managing technical debt": work to match the system to the human understanding of the problem the system is meant to address. The article calls out "emerging" techniques to do just this:

- More rigorous review practices

- Writing tests that capture intent

- Updating design documents continuously

- Treating prototypes as disposable

To me these are not "emerging," but rather "well-known industry best practices." Though maybe they're not that well known in fact? [EDIT TO ADD] On the other hand, it would make sense that they ARE well known, and that teams therefore reach for these familiar techniques to try and solve this "new" problem.

Putting in my 2c for the closing questions/thoughts in the article:

> How will they shape socio-technical practices and tools to externalize intent and sustain shared understanding?

Honestly? We'll probably end up doing these things more or less the same ways we always have. AI has not actually changed anything fundamental about how an individual encounters the world; there always was, and always will be, and always will have been, WAY more going on that we can fully get our heads around, but it's also always been the case that we can partially get our heads around most any problem space

> How will they use Generative and Agentic AI not only to accelerate code production, but to maintain their collective theory?

I suspect the answer to this one might well be that high-performing teams will have to scrupulously AVOID "accelerating code production" using AI in order to make sure what they are creating actually composes into the system they think they're building. If human understanding is the bottleneck, then the humans will have to produce less crap they need to understand!

[1]: https://wiki.c2.com/?WardExplainsDebtMetaphor, particularly the "Burden" and "Agility" sections.