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title: 'Stop Making Models Bigger, Make Them Behave — Kobie Crawford, Snorkel'
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  Qwen 3 235B was asked for YouTube's year over year ad revenue growth from 2023
  to 2024. It queried a table that didn't exist, tried again, got nothing back
  both times, and hallucinated an answer. The 4B model Snorkel finetuned with RL
  called `get_table_name` first, inspected the schema, ran a query, hit a column
  error, self-corrected, and got the right answer. The training run cost under
  $500. Kobe Crawford covers why tool discipline matters more than reasoning
  depth for this class of tasks, how single table training transferred cleanly
  to harder multi table problems (13.9% to 26.6% on the FinQA reasoning
  benchmark), and why breaking evals into rubrics helps identify which specific
  behavior to fix before writing any training data. Speaker info: -
  https://www.linkedin.com/in/kobie-crawford -
  https://snorkel.ai/author/kobie-crawford/ --- Watch along with the corrected
  transcript, summary, timestamps and resources on this talk's official AIE
  page:
  https://ai.engineer/talks/TNwJ1LMiENk-stop-making-models-bigger-make-them-behave-kobie-crawford-snorkel
  Join our upcoming AI Engineer conferences (see https://ai.engineer landing
  page): - AIEi Shanghai, November 5–6 — the first for meeting top Chinese labs
  and engineers - AIE CODE in SF, November 10–12 — the top AI Coding conference
  returns - AIEi Sydney, December 7–8 — the first AIEi run alongside NeurIPS
  2026 in Sydney ---
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# Stop Making Models Bigger, Make Them Behave — Kobie Crawford, Snorkel

Qwen 3 235B was asked for YouTube's year over year ad revenue growth from 2023 to 2024. It queried a table that didn't exist, tried again, got nothing back both times, and hallucinated an answer. The 4B model Snorkel finetuned with RL called \`get_table_name\` first, inspected the schema, ran a query, hit a column error, self-corrected, and got the right answer. The training run cost under $500. Kobe Crawford covers why tool discipline matters more than reasoning depth for this class of tasks, how single table training transferred cleanly to harder multi table problems (13.9% to 26.6% on the FinQA reasoning benchmark), and why breaking evals into rubrics helps identify which specific behavior to fix before writing any training data. Speaker info: - https://www.linkedin.com/in/kobie-crawford - https://snorkel.ai/author/kobie-crawford/ --- Watch along with the corrected transcript, summary, timestamps and resources on this talk's official AIE page: https://ai.engineer/talks/TNwJ1LMiENk-stop-making-models-bigger-make-them-behave-kobie-crawford-snorkel Join our upcoming AI Engineer conferences (see https://ai.engineer landing page): - AIEi Shanghai, November 5–6 — the first for meeting top Chinese labs and engineers - AIE CODE in SF, November 10–12 — the top AI Coding conference returns - AIEi Sydney, December 7–8 — the first AIEi run alongside NeurIPS 2026 in Sydney ---

Canonical: https://liquidgold.cc/channel/aidotengineer/explore/video/stop-making-models-bigger-make-them-behave-kobie-cr-9e00a245b431 · Channel: [AI Engineer](https://liquidgold.cc/channel/aidotengineer.md)

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