Using OpenClaw to Research and Organize Video Ideas

Matthew Berman demonstrates an assistant that gathers sources and creates a task in a video-production pipeline.

MBMatthew Bermanホスト · Forward Future
チャンネル
Matthew Berman
公開日
2026年2月11日
動画
0:51
読了時間
1 分
スライド
1
原文
英語
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要約

30 秒でわかる

In this February 2026 short, Matthew Berman shows an OpenClaw assistant researching a proposed video and adding a task to Asana. The accompanying prompt describes a broader workflow for research, duplicate checks and concise production briefs; its similarity threshold is a configuration choice, not a guarantee of accuracy.

  1. 1Start with an ideaBerman asks his assistant to find sources and visual material for a proposed video.
  2. 2Create a production taskThe assistant adds a card to an Asana video pipeline with researched material.
  3. 3Research and deduplicateThe description supplies a longer prompt for searching sources, comparing past ideas and creating a brief.

ポイント

  1. A chat message can trigger research for articles, videos, posts and visual material related to an idea.
  2. The example creates an Asana task containing research links and a production outline.
  3. The supplied prompt proposes similarity-based duplicate checks, but the short does not establish their accuracy.
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01

From an idea to a task

Berman demonstrates research from a chat request and shows the resulting Asana task. He shares a broader prompt for a content pipeline.

My team shares articles that might make interesting videos. In this OpenClaw example, I tell my assistant that an article is a video idea and ask it to find relevant articles, videos, posts and graphs I could show alongside it.

Research material in the video pipeline
スライド 1 / 1Research material in the video pipelineThe task contains links and proposed visual assets gathered for the video idea.

When the research finishes, the assistant creates a card in my Asana video pipeline. I open the card to show source material and a video outline assembled from the article; the short shows a result, not a systematic assessment of source quality.

The video description provides a broader content-idea prompt: research a topic, compare it with past ideas using semantic and keyword similarity, and create a concise task if it passes a duplicate check. Its proposed 40% cutoff is a chosen rule and can produce false matches or miss duplicates, so the output still needs review.

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