Reinforcement Learning from Verifiable Rewards emerged in 2025 as the most consequential training breakthrough since pretraining itself. The mechanics are deceptively simple — but the implications reshape the entire AI landscape.
The Five Scaling Phases of AI — Animated Explainer
Instead of training against human preferences (RLHF), models train against automatically verifiable reward functions — math problems with deterministic answers, code challenges with compiler and test suite feedback, logic puzzles with provably correct solutions.
The DeepSeek R1 Inflection Point
DeepSeek demonstrated something remarkable: by training a base model purely through RL against verifiable rewards (R1-Zero), the modelspontaneously developed sophisticated reasoning behaviors — self-reflection, verification, backtracking, strategy switching — without ever being shown examples.
The full R1 pipeline achieved performance matching OpenAI’s o1 at a reported training cost of approximately $5.6 million.
Why RLVR Is Structurally Different
Objective signal: Correctness is checkable. No noise, no disagreement, no gaming.
Emergent behaviors: Models discover reasoning strategies through optimization pressure alone — not programmed, not demonstrated.
Economics flip: Post-training went from thin finishing layer to 40%+ of total compute budget.
The Compound Flywheel
Every domain with a natural verifier becomes a new RLVR training environment. Every training environment produces models capable of tackling the next domain. Better reasoning → harder domains → richer verifiers → repeat.
The expansion accelerates. Build better verifiers, and you expand what’s trainable. That’s the frontier.
Gennaro is the creator of FourWeekMBA, which reached about four million business people, comprising C-level executives, investors, analysts, product managers, and aspiring digital entrepreneurs in 2022 alone | He is also Director of Sales for a high-tech scaleup in the AI Industry | In 2012, Gennaro earned an International MBA with emphasis on Corporate Finance and Business Strategy.
