CONTENT CREATION
Loom demo clip auto-chaptered into a Coda tutorial doc
When a Loom product demo finishes processing, splits its transcript into logical chapters, generates a cover image per chapter.
How it runs
The automated pipeline, trigger to output.
- TriggerLoom recording finished processingLoom
- ActionFetch transcript and metadata from LoomLoom
- ActionSegment transcript into titled chapters with timestampsOpenAI
- ActionGenerate a cover image per chapterImage generation
- ActionBuild Coda doc with one section per chapterCoda
- OutputReturn published Coda tutorial URLCoda
What it does
Turns a raw Loom screen recording into a polished, navigable Coda tutorial. It reads the Loom transcript, asks an LLM to detect natural topic boundaries, names each chapter, and builds a Coda doc where every section has a heading, a deep-linked timestamp into the video, the relevant transcript excerpt, and a freshly generated cover image.
When to use it
Use it when your team records ad-hoc product walkthroughs in Loom and wants them to become reusable help-center or onboarding content without an editor manually rewatching and writing each one up.
How it works
- 1A finished Loom recording fires the trigger with its video ID and transcript.
- 2An OpenAI step segments the transcript into chapters, each with a title, summary, and start timestamp.
- 3For each chapter, generate-image produces a cover thumbnail from the chapter summary.
- 4A Coda action creates the tutorial doc, then writes one section per chapter with heading, timestamped Loom deep-link, transcript excerpt, and cover image.
- 5The published Coda doc URL is returned as the final output.
Set it up
What you configure once, before turning it on.
- 1Connect LoomVideo transcripts, libraries.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect Image generationManaged Nano Banana image renders, metered per image.
- 4Connect CodaDocs, packs, automations.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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