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title: 'Building a Chess Coach — Anant Dole and Asbjorn Steinskog, Take Take Take'
description: >-
  LLMs can explain things clearly but can't play chess reliably. Take Take Take
  (Magnus Carlsen's app) solved this by separating concerns: Stockfish handles
  position evaluation, tactical and positional detectors extract concepts like
  forks, pins, and structural weaknesses, and the LLM's only job is translating
  those structured signals into English. Keeping the model as a translator
  rather than a reasoner is what makes it work at sub-3-second latency for a
  consumer app. Anant Dole and Asbjørn Steinskog also walk through how they
  closed the feedback loop. When a user flags bad commentary, it posts to Slack
  and injects the event into a running Claude Code session via Channels, a new
  MCP feature in research preview. Claude investigates the position, modifies
  prompts or detectors, regenerates the commentary, and asks clarifying
  questions back through Slack. During the live demo, Anant was reviewing the PR
  from his phone. Speaker info: -
  https://www.linkedin.com/in/asbj%C3%B8rn-ottesen-steinskog-a8000241/ -
  https://www.linkedin.com/in/anantdole/ --- Watch along with the corrected
  transcript, summary, timestamps and resources on this talk's official AIE
  page: https://ai.engineer/talks/FlzpEGHNVKQ-building-a-chess-coach 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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# Building a Chess Coach — Anant Dole and Asbjorn Steinskog, Take Take Take

LLMs can explain things clearly but can't play chess reliably. Take Take Take (Magnus Carlsen's app) solved this by separating concerns: Stockfish handles position evaluation, tactical and positional detectors extract concepts like forks, pins, and structural weaknesses, and the LLM's only job is translating those structured signals into English. Keeping the model as a translator rather than a reasoner is what makes it work at sub-3-second latency for a consumer app. Anant Dole and Asbjørn Steinskog also walk through how they closed the feedback loop. When a user flags bad commentary, it posts to Slack and injects the event into a running Claude Code session via Channels, a new MCP feature in research preview. Claude investigates the position, modifies prompts or detectors, regenerates the commentary, and asks clarifying questions back through Slack. During the live demo, Anant was reviewing the PR from his phone. Speaker info: - https://www.linkedin.com/in/asbj%C3%B8rn-ottesen-steinskog-a8000241/ - https://www.linkedin.com/in/anantdole/ --- Watch along with the corrected transcript, summary, timestamps and resources on this talk's official AIE page: https://ai.engineer/talks/FlzpEGHNVKQ-building-a-chess-coach 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/building-a-chess-coach-anant-dole-and-asbjorn-stein-f8fdaa59cdf5 · Channel: [AI Engineer](https://liquidgold.cc/channel/aidotengineer.md)

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