Trojanowski: DeepSeek-R1 succeeded by scaling outcome supervision over process supervision
Mitch Trojanowski · How to Build Autonomous, Long-Horizon AI Agents | Basis · Aug 5, 2026 · at 20:03
Mitch Trojanowski, co-founder of Basis, analyzes how reasoning models like DeepSeek-R1 use RL with verifiable rewards (RLVR) based on final outcomes rather than intermediate step supervision.
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“If you look, you know, if you fast forward a bit and you look at the, like the DeepSeq R-one paper where they effectively laid out, you know, what I think all the labs were doing at that time, or at least OpenAI was doing in terms of you know, RLVR reasoning from reinforcement learning from verifiable rewards that effectively had very little process supervision. And instead was essentially just saying, hey, did you get the outcome right? Yes. Okay. Let me reward you. And then scaling that up which, you know, obviously worked well.”
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