---
name: record-one-minute-thank-you-video
description: "Make a short thank-you clip. Use this when you have a real deed to thank someone for."
category: Thank You Machine
stage: Produce
definitive_article: /thank-you-machine
status: complete
---

# Record a One-Minute Thank-You Video

A short video can make your thanks feel personal. This guide helps a business owner thank one person for one real deed. Start with your notes and a phone. Finish with a clear clip that is ready to check.

**The path:** Checked note → short recording → checked clip.

**Use this when:** you have a specific reason for thanks and recording is suitable for the person and intended use.

## Inputs

- The checked note from [Find a Real Reason to Say Thanks](https://local-service-spotlight.github.io/task-library/?task=identify-thank-you-triggers#task-identify-thank-you-triggers).
- A phone or camera, a quiet place, enough light and a place to save the original file.
- The intended viewer and any limits on public use of the person’s name, story or image.

## First-run prompt

> Turn this checked note into three brief talking points for a thank-you video. Help me record and review one clear clip. Keep the person’s deed and my reason for thanks accurate. Save the original and a review copy.

## Steps

1. Use the note to say who you are thanking, what they did and why it mattered. Speak to the person. Aim for about a minute and one point; do not add a sales pitch.
2. Choose a quiet space with light on your face. Frame for the planned use, leave room for captions and clear private details from the background.
3. Make a short test to check framing and sound. An agent must keep playback muted with volume zero; use captions and audio metadata, or ask the human recorder to assess sound without starting speaker playback.
4. Record in your own words from the talking points. A natural take is useful, but redo a wrong name, unsupported claim, inaudible line or major interruption. One take is a preference, not a rule that overrides accuracy.
5. Save the original file before editing. Label it with date, person or safe project code and topic, without exposing private facts in a public filename.
6. Review the clip against the source. Check the name, deed, meaning, framing and intended duration. Use a transcript to catch errors; do not treat generated captions as proof that the spoken name is correct.
7. Save a checked review copy and the transcript. Record any sound check that a person still needs to make. Hand off the file and sharing limits; recording does not itself mean the clip has been sent or posted.

## Definition of done (QA checklist)

- [ ] The clip thanks one correct person for one sourced deed.
- [ ] A usable original and review copy are saved and open successfully.
- [ ] Framing and transcript are checked; sound verification and any limits are recorded.
- [ ] The message has no invented result, favor request or implied endorsement.
- [ ] Sharing scope and the next owner are attached to the files.

## Example(s)

**Fictional teaching example — no client result or completed run.** The owner records a 48-second clip thanking Jordan for covering the desk. The first take uses the wrong day, so the owner records it again. The corrected clip and note are saved for review; no send or public post is claimed.

## Handoff and Content Factory context

Send the checked files to [Process the Thank-You Clip](https://local-service-spotlight.github.io/task-library/?task=process-through-content-factory#task-process-through-content-factory). Deliver a private message only when that send is within the user’s instructions, then verify the actual sent copy.

This fits the [Content Factory](https://blitzmetrics.com/content-factory/): Produce a true story, Process it into useful files, Post only in the agreed places, and Promote a suitable post when its test has a budget. Each stage passes its checked files and next owner forward.

## When this runs

Run when a checked thank-you note is ready. Record a fresh clip for a new event; a file download does not start a recording or create a recurring task.

## First-run setup and continuity

Use the files and accounts this task actually needs. A skill is a written recipe; the [AI worker](https://blitzmetrics.com/build-agents/) needs suitable tools and access to follow it. This file does not install an app, connect an account or start a timer. Follow the [setup guide](https://localservicespotlight.com/install/) for the chosen app. Carry out work already covered by the user's instructions; ask only for an exact missing item or a new action outside that scope.

Save the source, current state, checked result and next owner in the project files. Check that record before retrying or handing work to another person. Configure a repeat only when requested, with its time zone, actual runtime and first successful firing. An app or model name does not prove persistence, memory or a schedule.

Keep every agent media check muted with volume zero before playback. If that cannot be verified, use captions, metadata or still frames and record the limit. Do not play sound through the user's speakers without their current request.

## Write up the real run

For each real attempt, [write the meta article](https://blitzmetrics.com/meta-article-prompt/): its task and source revision, starting point, work done, evidence, measured result, gaps and next handoff. Save one execution ID across retries and edits. Partial, blocked and failed work also gets a record. A saved draft satisfies writing while any public release is pending. Writing does not grant publication authority.

A teaching example is not a real execution. Do not count it, a repeated check or a revision as another run. The [recipe and meta-article guide](https://localservicespotlight.com/meta-articles/) explains the link between reusable instructions and actual work.


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

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

- **Phase:** Produce
- **Importance:** 3/5 `●●●○○` — frequency 3, revenue 3, gating 2 (supporting)
- **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:** Raw files in Content Library `01-Raw/` plus a tracker row (question, date, speaker). Next skill never needs the chat — it needs the files.

## Model routing (same factory, any engine)

- **This task's lane:** `any` — Any capable chat model (Claude, ChatGPT, Grok, Gemini). SOP following, drafts, checklists.
- **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

- Exact task: [Record a One-Minute Thank-You Video](https://local-service-spotlight.github.io/task-library/?task=record-one-minute-thank-you-video#task-record-one-minute-thank-you-video)
- [One-minute video guide](https://blitzmetrics.com/one-minute-video-guide/) — how to record one clear point.
- [Content Factory](https://blitzmetrics.com/content-factory/) — how the source becomes checked posts.
- [Dollar-a-Day guide](https://blitzmetrics.com/dollar-a-day/) — the paid test method; current platform controls still need checking.

## Review and evidence still needed

The original contributor state is preserved. Instruction review, article certification, account access and completed work are separate states.

- Source mapping needs repair: on September 6, 2026, the recorded /thank-you-machine/ hub redirected to /face-socks/, a gift-ordering guide. That live gift recipe does not certify this video workflow. Keep the task ID and contributor state; use the relevant video and process guides below until the owner resolves the canonical video hub.
- Add a dated, real execution record with the actual checked output. The example below does not fill that gap.