What does it mean for AI development to be driven by the right task?

The bitterest lesson in AI is that the task you choose determines everything. It determines what data is valuable, what capabilities get surfaced, what kind of intelligence you can build. Algorithms and compute matter, but data matters more than both, and having the right northstar matters more than data. This has happened maybe two and a half times in large language model history. RLHF established instruction following as a northstar. RLVR made a slight edit toward benchmark optimization. And RLCD is our new task: making AI reliable for programmatic, machine-native use. Most researchers do not spend enough time asking whether the task they are optimizing for is actually the right one. That is the question that everything else depends on.