I thought "The Bitter Lesson" was that whole a specialised system will outperform in the short term, generalized systems with lots of data win in the long term.
But it's informative for the engineers that need something right now, because it means taking the best general purpose tool and specializing it will outperform the general tool, and you can sustain that if you are willing to always hop tools and respecialize. As we may.
Sure you can throw more compute at it. But it cost a lot of money and you hit resource limits.
We have been doing an end run around the bitter lesson with prompt engineering. Also by using different models for vision vs. text. By getting (human coding) agents to "think" and run code.
The bitter lesson might be that you cant predict what the thing is that will be most optimal tomorrow and any player in the AI game can be innovated out of existence at any time.
Maybe anyone except TMSC.