GRPO and OPD: practical paths for post-training
A publication dated August 26, 2026 presents two resources on post-training with reinforcement learning: one on scaling vanilla GRPO and another focused on OPD.
Source: Recursos práticos sobre GRPO e OPD (cameronrwolfe.substack.com). Text prepared with AI from this source.
What happened and what to do
On August 26, 2026, the publication presented two practical resources on post-training with reinforcement learning beyond SFT. One addresses challenges in making vanilla GRPO work at scale; the other covers OPD. The text notes that the GRPO guide may help engineers tackle practical difficulties when scaling RL training.
For a company evaluating these techniques, a concrete first step is to assess data, infrastructure, metrics, and training stages before expanding experiments. Wendelmaques can structure that assessment and implement data and monitoring pipelines, along with internal tools to track runs and results, without assuming RL is the right solution for every case.
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Wendelmaques can diagnose the opportunity and data and infrastructure requirements, define an implementation scope, and develop and operate training and monitoring pipelines suited to the case.
Next step
Send a short description of your training or evaluation scenario. Wendelmaques can assess the case and prepare a scoped proposal.
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