The Stanford AI Index 2026 establishes something the benchmark-saturated conversation had been avoiding: performance on narrow tasks does not transfer to the judgment-intensive work that defines scientific progress. AI agents that score competitively on structured subtasks fall to roughly half the performance of human PhDs once the task requires sequencing decisions, adapting when results are unexpected, or resolving ambiguous objectives. The matters precisely because it is not a critique from skeptics—it is the authoritative annual account of where the field stands, published…