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SOCIAL MEDIA

Quote-card generation with Slack approval gate before publishing

On a scheduled run, generates branded quote cards from the latest transcript and posts them to Slack with Approve/Reject buttons.

CategorySocial Media
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule fires the run
  • ActionSelect pull-quotes and render branded cardsImage generation
  • ActionPost cards to Slack with Approve/Reject buttonsSlack
  • LogicKeep only cards the reviewer approved
  • OutputPublish approved cards to social platformsSocial publishing

What it does

This workflow adds a human checkpoint to quote-card publishing. It builds the candidate cards automatically, but nothing goes live until a teammate clicks Approve in Slack. Rejected cards are dropped silently, keeping off-brand or out-of-context quotes from shipping.

When to use it

Use it when brand safety matters and you want speed without losing editorial control — for example a founder-led show where one wrong quote screenshot can cause problems. Good for teams that already live in Slack.

How it works

  1. 1A daily schedule triggers the run and the latest transcript is pulled from the source folder.
  2. 2A model selects three pull-quotes and a branded quote card is rendered for each.
  3. 3The cards are posted to a Slack review channel as an interactive message with Approve and Reject actions per card.
  4. 4A logic step waits for the reviewer's decision and filters to only the approved cards.
  5. 5Approved cards are published to the connected social platforms; a confirmation summary is posted back to the Slack thread.

Set it up

What you configure once, before turning it on.

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

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