Auto-grading decade-old Hacker News discussions with hindsight

One thing this really highlights to me is how often the "boring" takes end up being the most accurate. The provocative, high-energy threads are usually the ones that age the worst.

If an LLM were acting as a kind of historian revisiting today’s debates with future context, I’d bet it would see the same pattern again and again: the sober, incremental claims quietly hold up, while the hyperconfident ones collapse.

Something like "Lithium-ion battery pack prices fall to $108/kWh" is classic cost-curve progress. Boring, steady, and historically extremely reliable over long horizons. Probably one of the most likely headlines today to age correctly, even if it gets little attention.

On the flip side, stuff like "New benchmark shows top LLMs struggle in real mental health care" feels like high-risk framing. Benchmarks rotate constantly, and “struggle” headlines almost always age badly as models jump whole generations.

I bet theres many "boring but right" takes we overlook today and I wondr if there's a practical way to surface them before hindsight does

This suggests that the best way to grade predictions is some sort of weighting of how unlikely they were at the time. Like, if you were to open a prediction market for statement X, some sort of grade of the delta between your confidence of the event and the “expected” value, summed over all your predictions.

Exactly, that's the element that is missing. If there are 50 comments against and one pro and that pro has it in the longer term then that is worth noticing, not when there are 50 comments pro and you were one of the 'pros'.

Going against the grain and turning out right is far more valuable than being right consistently when the crowd is with you already.