PERSONAL PRODUCTIVITY

Coda OKR edit to narrated change-log clip on update

When an OKR row changes in Coda, captures the before-and-after, narrates a short spoken change note with ElevenLabs.

CategoryPersonal Productivity
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerCoda OKR row updatedCodaCoda
  • LogicDiff old vs new; skip cosmetic edits
  • ActionDraft spoken change noteOpenAI
  • ActionNarrate note with ElevenLabsElevenLabsElevenLabs
  • ActionAssemble Loom change-log clipLoomLoom
  • OutputArchive audio and Loom to Google DriveGoogle DriveGoogle Drive

What it does

Creates an audit trail of OKR changes as listenable clips. Whenever a key result's value, target, or status is edited in Coda, this workflow records what changed and produces a short narrated note plus a Loom clip, archiving both to a shared Google Drive folder for the quarter.

When to use it

Use this when OKR numbers get adjusted mid-quarter and you want a transparent, reviewable history of who changed what and why — without forcing anyone to read a raw revision log. Useful for finance and ops teams that need defensible records.

How it works

  1. 1A Coda row-update event triggers the workflow with the changed key result.
  2. 2A logic step diffs old vs. new values and skips cosmetic edits like formatting.
  3. 3An LLM drafts a concise spoken change note describing the delta and its owner.
  4. 4ElevenLabs narrates the note.
  5. 5A short Loom clip is assembled from the narration and the row context.
  6. 6The audio file and Loom link are saved to the quarter's Google Drive change-log folder.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect CodaDocs, packs, automations.
  2. 2
    Connect ElevenLabsText-to-speech, voice cloning.
  3. 3
    Connect LoomVideo transcripts, libraries.
  4. 4
    Connect Google DriveDocs, sheets, slides, files.
  5. 5
    Connect OpenAIModels, embeddings, files.
  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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