CONTENT CREATION

Approved Podcast Clips to Multi-Platform Social Posts

When a producer marks clip candidates as approved in Airtable, draft platform-tailored captions for each and queue them as posts across your social channels.

CategoryContent Creation
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerAirtable clip record set to ApprovedAirtableAirtable
  • LogicFilter: confirm clip has start and end timestamps
  • ActionDraft per-platform captions from clip snippetOpenAI
  • ActionQueue draft posts across social platformsSocial publishing
  • OutputMark Airtable record as QueuedAirtableAirtable

What it does

Takes the human-approved clip moments from an episode and turns each into ready-to-publish social posts, with captions written specifically for each platform's format and tone. It closes the gap between "we found good clips" and "the clips are scheduled."

When to use it

Use it after a producer has reviewed auto-detected clip candidates and flipped a status to Approved. Ideal for teams that batch-promote a single episode across multiple networks and don't want to rewrite the same hook five different ways by hand.

How it works

  1. 1An Airtable record updated to status Approved triggers the flow.
  2. 2A filter step confirms the record is a clip candidate with both a start and end timestamp before proceeding.
  3. 3OpenAI drafts distinct captions per platform from the clip's transcript snippet and reason, respecting length and hashtag conventions for each.
  4. 4The captions and clip metadata are pushed to the social scheduler as draft posts across the connected platforms.
  5. 5The Airtable record is updated to Queued so producers can see what advanced.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AirtableBases, tables, views, automations.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect Social publishingCross-post to X, LinkedIn, Instagram, TikTok, and 4 more in one call.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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