> A hand-crafted approach can absolutely beat data if your approach unlocks more search and/or learning than the general solution.

Now let's look at the bitter lesson again. It says that general methods that leverage computation are ultimately the most effective, and by a large margin.

That's different from just saying to leverage computation (which is how I would interpret "unlocks more search/learning"). If the lesson is "more computation wins, when sufficiently channeled" you're basically looking at a truism. Of course more computation beats less when it's used right. The bitter lesson is about abandoning specialization in order to get more computation, and while there's a couple ways where that helps with chess, there's a lot more ways where it's counterproductive. It looks like it's more true for Go than it is for chess, and that it's not universally true. It probably correlates with the state space.