CONTENT CREATION

Nightly backfill of missing hero images on published posts

Runs nightly, queries your Postgres CMS for published posts missing a hero image, generates a palette-constrained illustration for each, uploads to R2, and updates the post record.

CategoryContent Creation
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNightly schedule fires
  • ActionQuery Postgres for published posts missing heroPostgreSQLPostgres
  • ActionBuild palette-locked prompt per post
  • ActionRender illustration via ReplicateReplicateReplicate
  • ActionUpload image to public R2 bucketCloudflareCloudflare R2
  • OutputUpdate post row with hero URL and timestampPostgreSQLPostgres

What it does

Closes the gap on older content that shipped without art. On a schedule, it finds published posts that lack a hero image, generates an on-brand illustration for each, stores it in R2, and updates the database so the site renders the new art on next load.

When to use it

Use it after adopting hero images on a blog that has a backlog of imageless posts, or as a safety net that catches any post that slipped through without art. It steadily improves the whole archive without manual effort.

How it works

  1. 1A nightly schedule trigger starts the run.
  2. 2A Postgres query selects published posts where the hero image column is null, capped at a nightly batch size to control cost.
  3. 3For each post, a prompt is built from its title and excerpt with the brand palette and style locked in.
  4. 4Replicate renders the illustration.
  5. 5The image is uploaded to a public R2 bucket.
  6. 6The post row is updated with the new hero URL and a generated-at timestamp so it is not reprocessed.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PostgresAny Postgres URL — query, write, migrate.
  2. 2
    Connect ReplicateImage, video, and model inference.
  3. 3
    Connect Cloudflare R2Object storage, S3-compatible.
  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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