Bespoke Labs

Data and Environment Curation for Post-Training LLMs — Mahesh Sathiamoorthy, Bespoke Labs

Jul 31, 2026 · 19:12

Mahesh Sathiamoorthy, CEO of Bespoke Labs, argues that data and RL environments, not algorithms, are the bottleneck in post-training LLMs, and shares open-source work including OpenThoughts and Curator. He details the OpenThoughts curation recipe, built with Stanford, Berkeley, and UW, whose counterintuitive lessons include that sampling multiple answers per question works well, stronger teachers are not always better, and synthetic rewriting failed for agent tasks. He notes that for agents, SFT still contributes most of the gains, with RL only adding the last few percentages. A concrete production case: Credit Karma needed compliant credit card recommendations, and tagging fine-tuning data lifted compliance metrics while improving latency and throughput. He closes with the full stack needed to build RL environments and post-train agents.

OpenThoughts: Data Recipes for Reasoning Models — Ryan Marten, Bespoke Labs

Jul 19, 2025 · 19:59

Ryan Marten, co-lead of the OpenThoughts collaboration and founding engineer at Bespoke Labs, reveals the missing data recipe for open-source reasoning models, presenting OpenThoughts 3, a state-of-the-art 7B reasoning dataset that outperforms DeepSeek R1 Qwen 7B and Nematron Nano on benchmarks like AIME, Live Code Bench, and GPQA Diamond. Through over 1,000 experiments and 5,000 datasets, key findings include that sampling multiple reasoning traces per question scales performance by 16x, Qwen 32B surpasses DeepSeek R1 as a teacher model, synthetic question generation is highly effective, and filtering by difficulty or response length works better than embeddings. Surprisingly, verification of answers in SFT distillation did not improve results, and focusing on fewer high-quality sources outperformed maximizing diversity. For domain-specific reasoning, Marten advises starting with the OpenThoughts recipe, using synthetic data generation (via the open-source Curator library), and rigorous evaluation (via EvalComet). A legal reasoning example shows that distillation can surpass the teacher model. All resources are open-source.