---
name: create-and-send-thank-you-machine-videos
description: "Make a short, real thank-you. Send or share it only in the way the job calls for."
category: Content Factory — Promote
stage: Promote
definitive_article: /thank-you-machine
status: complete
---

# Create and send Thank You Machine videos

Someone helped you, and you want to say thanks in a personal way. This guide helps you make a short video that names what they did. Start with the real moment and who should receive the message.

**The path:** Real moment → personal recording → scoped delivery → observed response.

**Use this when:** A verified referral, review, useful contribution or milestone deserves a personal acknowledgment.

## Inputs
- The exact person, factual trigger and appropriate destination, plus the scope for a private message, public post, tag or later reuse.
- The real speaker and recording device, approved facts/voice, and permission for any client details or third-party media.
- Access to the specific authorized sending/posting channel and a tracker for the recording, sent copy and any response. Paid promotion is separate scope.

## First-run prompt

> Prepare a brief thank-you from these facts: who helped, what they did and why it mattered. Have the actual speaker record it; do not invent their experience. Use only the authorized destination and send/share scope, verify any sent copy, and record the response as unknown until observed.

## Steps
1. Verify the trigger in its source record and choose the right recipient. Name a concrete contribution rather than generic praise. Do not call a person a client, mentor or close friend unless that relationship is supported.
2. Write a short recording brief with the person’s name, what happened, why it mattered and a sincere close. Aim for about a minute; do not force filler or invent business results to hit exactly 60 seconds.
3. Have the actual person record in their own voice. Keep it natural, with readable framing and a quiet setting. An agent can prepare the brief and process the file; it must not fabricate a human recording or first-person experience.
4. Check the file, captions and public/private details before delivery. Keep agent playback muted at volume zero. If spoken accuracy cannot be checked silently from a reliable transcript or by the speaker, record that review gap.
5. For an already authorized private send, verify the exact thread/recipient and send the agreed file or accessible link. Read back the sent copy. A prepared message, queued upload and delivered message are different states; do not resend from uncertainty alone.
6. Publish or tag the recipient only when that specific public use is in scope and the content is appropriate to share. A private thank-you does not automatically become public content. A recipient is free not to reply or reshare.
7. Consider derivatives only when useful, permissioned and authorized. Your thanks to someone is not their testimonial about your service. Any paid boost requires its own proven-content, audience and budget checks; it is not a mandatory part of saying thanks.
8. Save the trigger, actual recording, delivery state and any observed response. Route a future content idea or follow-up to its owner without manufacturing a testimonial, referral or new relationship claim.

## Definition of done (QA checklist)

- [ ] Trigger, recipient and relationship wording are supported by the source.
- [ ] The actual speaker’s recording and factual message are used.
- [ ] Private send, public post/tag, reuse and paid promotion each match existing scope.
- [ ] Any send/post has a read-back receipt; unknown response stays unknown.
- [ ] The result is not represented as a recipient endorsement or guaranteed referral.

## Example(s)

**Fictional teaching example:** A shop owner thanks a volunteer who helped arrange a community repair day. The brief says exactly what the volunteer did and why it helped. The owner records 48 seconds. The authorized scope is one private email, so the operator verifies the recipient and sent copy; there is no public tag or boost. A reply two days later says the video was appreciated. The log records that reply, not a testimonial about the shop’s repair quality or a new sale.

## Handoff and Content Factory context

Give any authorized public-content candidate to the actual content owner and [record one minute videos](https://local-service-spotlight.github.io/task-library/?task=record-one-minute-videos#task-record-one-minute-videos) or the appropriate Post task. Eligible thank-you moments from [engage with social comments](https://local-service-spotlight.github.io/task-library/?task=engage-with-social-comments#task-engage-with-social-comments) are inputs, not automatic send triggers.

This task is in Promote within the [Content Factory](https://blitzmetrics.com/content-factory/). Produce gathers real source material; Process makes useful assets; Post places and checks them; Promote distributes suitable work within its own scope. Use the proof and checked posts from earlier stages; a Promote task does not automatically redo all four stages. Use the actual next step above; catalog neighbors are not prerequisites.

## When this runs

One acknowledgment per real trigger. A same-day aim is useful, but a standing monitor requires an explicit channel/cadence, actual access and duplicate checks. The guide creates no continuous watcher or follow-up schedule.

## First-run setup and continuity

Open the supplied task file and its linked source. Verify the project’s real inputs, account, access and output folder before work. This Markdown file is a guide; it does not install an app, connect an account, supply a subscription or create a schedule. Carry out work already authorized; do not ask for the same approval again. Keep any unsupplied destination or new action outside that scope clearly pending.

Save source IDs, versions, decisions, checked outputs and next owner in the project tracker. Before a retry, check the saved state and other workers’ changes. A model name does not guarantee memory or a running timer. Repeated work needs an actual configured trigger and durable state; one-off work can be started by the prompt above.

Keep agent media muted with volume zero before playback. If mute cannot be verified, use captions, metadata or still frames. State the limit: silent visual checks do not prove spoken-word accuracy or audio quality. Do not start sound through the user’s speakers unless explicitly asked.

## Write up the real run

For every actual attempt, [write its meta article](https://blitzmetrics.com/meta-article-prompt/) with this recipe and revision, trigger, steps performed, output evidence, measured result, gaps and next owner. Failed, blocked and partial attempts also get a written record. A draft can satisfy writing; publishing it follows the existing job scope.

Keep one stable execution ID across retries and edits. A separately scoped child task may have its own ID linked to its parent. Writing the parent’s meta record is part of that run, not an endless new chain. The [recipe and meta-article guide](https://localservicespotlight.com/meta-articles/) explains this distinction. Teaching examples are not real executions and must not enter the run count.


<!-- factory-layer:start -->

## Factory chain (do not treat this as isolated)

- **Phase:** Promote
- **Importance:** 5/5 `●●●●●` — frequency 4, revenue 5, gating 3 (runs every factory cycle or weekly; ads/revenue path)
- **Suggested previous station:** —
- **Suggested next station:** —
These stations are generated neighbors, not verified prerequisites or handoffs. Follow the task’s actual Inputs and Handoff sections.
- **Handoff:** Organic metrics CSV (or Ads Manager export), pixel ID, creative filenames, kill/scale log. Next week's ranking starts from this file.

## Model routing (same factory, any engine)

- **This task's lane:** `computer` — Logged-in UI (Meta Ads Manager, Descript, GSC, wp-admin when REST is blocked). Requires a supported browser tool and the right account access.
- **Single-engine path:** Use the capable AI app you already have. Check its required tools and access before starting. Pass the actual result and proof to the next task.
- **Optional multi-engine:** A tested local model may draft; a stronger model may review facts and voice. Use supported tools for approved actions. Pick models from observed quality and cost; a model name does not prove it can run this task.
- **Never** store the working state in one vendor's memory. Files in the Content Library are the bridge.

<!-- factory-layer:end -->
## Definitive article & links

- Source article mapping on hold: https://blitzmetrics.com/thank-you-machine (currently redirects to the Face Socks gift recipe; it is not the canonical video procedure).
- Exact task: [Create and send Thank You Machine videos](https://local-service-spotlight.github.io/task-library/?task=create-and-send-thank-you-machine-videos#task-create-and-send-thank-you-machine-videos)
- Writing standard: [Article Guidelines](https://localservicespotlight.com/article-guidelines/)
- [One-minute video guide](https://blitzmetrics.com/one-minute-video-guide/)
- [Content Factory](https://blitzmetrics.com/content-factory/)
- [Dollar-a-Day method](https://blitzmetrics.com/dollar-a-day/)

## Review and evidence still needed

The source contributor status is preserved. It is not certification of this draft or proof of account access, completed work or a live outcome. The worked example teaches the method and is explicitly fictional.
- URL semantic hold: the source’s /thank-you-machine/ route currently resolves to the face-socks gift recipe, not this video procedure. Keep this task source as the video method until the owning article mapping is corrected.
- No real recording, send permission, recipient or response is supplied by the teaching example.