It's not just that, but the core is just that, even with reasoning models. Harness can only get you closer to the good result, but can't save you from every pitfall. As for PM analogy - don't forget that models don't learn and keep doing same stupid stuff they were doing a month ago.
Agents are perfectly capable of learning. Why would the model need to learn? The harness and tooling are all that matter.
I would suggest you examine current harness memory persistence. Any reprimand you give your model will be remembered, in the same way a puppy that has a bad social experience will become more shy.
They will not save you from every pitfall, but that isn't the point; engineers walk into pitfalls all the time. This can get you in, and out, much much quicker.