PERSONAL PRODUCTIVITY

Daily Loom Standup to Threaded Slack Recap

Collects each team member's daily Loom video update, transcribes it, and posts one threaded standup recap in Slack so the team skips the live sync.

CategoryPersonal Productivity
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekday morning schedule fires
  • ActionFetch Loom videos posted since last runLoomLoom
  • ActionRetrieve transcript for each Loom videoLoomLoom
  • LogicSkip members with no update today
  • ActionSummarize each transcript into done/next/blockersOpenAI
  • OutputPost parent recap with threaded per-person repliesSlack

What it does

Every morning this workflow gathers the Loom updates your team recorded since the last run, transcribes each one, and assembles a single threaded Slack recap. The parent message is a roll-up of who shipped what; each person's full transcript and Loom link lives in a reply, so the channel stays clean and scannable.

When to use it

Use it when your team has abandoned the live daily standup but still wants shared visibility. Ideal for distributed teams across time zones where a synchronous meeting is impractical and a wall of raw video links is unhelpful.

How it works

  1. 1A scheduled trigger fires each weekday morning.
  2. 2The flow pulls all Loom videos posted to your team workspace since the previous run.
  3. 3Each video's transcript is fetched and the agent summarizes it into a tight blockers/done/next format.
  4. 4A logic step skips contributors who posted nothing, so the recap never shames absentees.
  5. 5The agent composes one parent recap message listing each person's headline.
  6. 6Slack posts the parent message, then threads each full summary and Loom link as replies.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect LoomVideo transcripts, libraries.
  2. 2
    Connect SlackChannels, DMs, threads, mentions.
  3. 3
    Connect OpenAIModels, embeddings, files.
  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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