CONTENT CREATION

Loom demo chaptered to Coda and announced in Slack

When a Loom demo lands, chapters it into a Coda tutorial with per-section cover images, then posts a formatted announcement with the doc link and chapter list to a Slack channel.

CategoryContent Creation
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerLoom recording finished processingLoomLoom
  • ActionSegment transcript into chapters and write blurbOpenAI
  • ActionGenerate cover image per chapterImage generation
  • ActionAssemble Coda tutorial docCodaCoda
  • OutputPost announcement with doc link to SlackSlack

What it does

Extends the core chaptering flow with a distribution step: after a Loom demo becomes a structured Coda tutorial, it drops a clean announcement into the right Slack channel so the team actually sees the new doc instead of it sitting unread.

When to use it

Use it when freshly recorded walkthroughs need to reach a team channel immediately — for example, support or sales enablement where a new feature demo should be in front of everyone the moment it is documented.

How it works

  1. 1A finished Loom recording triggers the flow.
  2. 2An OpenAI step segments the transcript into titled chapters with timestamps and writes a short blurb.
  3. 3generate-image creates a cover image for each chapter.
  4. 4A Coda action assembles the tutorial doc with sections, timestamped Loom links, and images.
  5. 5A Slack action posts an announcement message containing the blurb, the Coda doc link, and a bulleted chapter list with jump links.
  6. 6The Slack message permalink and Coda URL are returned.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect LoomVideo transcripts, libraries.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect Image generationManaged Nano Banana image renders, metered per image.
  4. 4
    Connect CodaDocs, packs, automations.
  5. 5
    Connect SlackChannels, DMs, threads, mentions.
  6. 6
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  7. 7
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  8. 8
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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