Free Guide · AI Presenter Workflow

Build the presenter. Then earn the publish.

A practical production and review path for generated presenter videos: stable references, controlled motion, approved voice audio, corrected lip sync, human QA, and a real resource connected before release.

Jump to the workflow

Worked Example: Captain AI Series

The series uses Seedance 2.5 motion, assigned approved ElevenLabs voices and a separate Sync3 pass for visible dialogue. Keep each presenter’s identity and voice distinct. Check the last spoken words in the exported video, not just the opening sample.

This is a reviewable workflow, not a guarantee of perfect identity, reach, leads, revenue, or any other outcome.

Control the inputs

Lock the presenter reference, voice assignment, script, and selected motion take.

Separate the reviews

Motion generation, lip-sync correction, and final edit each get their own pass.

Release the full path

The content, scheduler, promised guide, and comment delivery must all be ready.

The Production Path

Seven gates from reference to release.

Tool interfaces and model availability change. Keep the control points even when the exact buttons, names, or current model change.

Lock the character references

Treat identity as an input you control, not something to rediscover on every render.

1.Choose the approved reference images for each presenter before writing motion prompts.
2.Record the distinguishing details that must stay stable, including face shape, hair, wardrobe, accessories, framing, and setting.
3.Keep Ian and Hailey in separate named reference packs so a prompt, voice, or render cannot be assigned to the wrong presenter.
4.Reject a reference with unclear facial detail, heavy occlusion, or a look you would not want repeated.

Pass when: A reviewer can identify the intended presenter and the non-negotiable visual details without opening the generation tool.

Build the scene and motion in Higgsfield

Create the performance around a locked reference instead of asking one prompt to solve identity, scene, and movement at once.

1.Create the scene in Higgsfield with the approved reference pack attached to the correct presenter.
2.Use the currently selected model for the production run. The Ian and Hailey worked example used Seedance 2.5.
3.Describe one shot at a time: framing, camera behavior, body movement, expression, and the action the presenter performs.
4.Generate short reviewable takes. Select for usable identity and movement before moving to voice or lip sync.

Pass when: The silent take holds the presenter identity well enough for review and the motion supports the script rather than distracting from it.

Produce the approved voice audio in ElevenLabs

Make the voice track a controlled production asset with a named owner, approved text, and a repeatable file.

1.Assign only the approved ElevenLabs voice for the named presenter.
2.Confirm the final script, pronunciation, and presenter assignment before generating audio.
3.The series targets a comfortable delivery around 180 WPM. Preserve approved inflection and let the voice determine scene length; never squeeze narration to fit footage.
4.Listen for skipped words, wrong emphasis, awkward pauses, and voice mismatch. Regenerate the audio before video correction if any of those fail.

Pass when: The audio is approved on its own and its filename identifies the presenter, script version, and review state.

Run a separate lip-sync correction pass

Motion generation and mouth timing are different review problems. Keep the correction pass explicit.

1.Pair the approved voice file with the selected motion take.
2.Run Sync Lipsync 3 with the approved audio and selected motion instead of assuming the first motion render is ready.
3.Review every visible speaking line at normal speed, especially the final words of each closing CTA. Extend the shot when needed; do not let a silent reaction play under an on-camera line.
4.If timing still fails, return to the clean audio or selected take. Do not hide a bad sync with captions.

Pass when: Words, pauses, and visible mouth shapes track closely enough to pass a human review at playback speed.

Review identity, mouth timing, and movement

Use a three-part QA pass so a strong result in one area cannot hide a failure in another.

1.Identity: compare the face, hair, wardrobe, and presenter assignment against the locked references.
2.Mouth timing: watch the full clip, then replay the most demanding phrases with sound on and off.
3.Movement: look for sudden pose changes, drifting hands, frozen gestures, camera jumps, and motion that conflicts with the words.
4.Mark pass, revise, or reject for each category. A clip only advances when all three are reviewed.

Pass when: Identity, Mouth timing, and Movement each have an explicit reviewer decision.

Add captions and finish the edit

Turn the corrected performance into a clear piece of content without using editing to disguise generation errors.

1.Add captions from the approved script or transcript and check them against the final audio.
2.Keep caption line breaks readable and inside safe areas for the destination platform.
3.Add only the cuts, overlays, music, and brand elements needed to support the lesson.
4.Watch the final export once on a phone-sized screen and once with sound off before release review.

Pass when: The final file has accurate captions, clear audio, intentional edits, and no unresolved generation artifacts.

Complete the release gate before publishing

A video is not ready when the export finishes. The promised resource and delivery path must be real first.

1.Upload only through the approved scheduler and confirm the intended profile, caption, media, date, time, and current status.
2.Create and test the real comment-to-DM rule for the exact keyword before release. For this campaign, the keyword is CREATE.
3.Use a two-step Instagram flow: comment CREATE, receive an opening DM, tap YES, then receive this guide. Test every step with a non-owner account.
4.Do not release while the resource, automation, destination, or approval is missing. A draft with a stored date is still a draft.

Pass when: The final approver can open the guide from the tested DM and confirm the scheduler is intentionally ready for release.

Use and Disclosure

Generated is not documentary.

Generated presenters should not be presented as documentary proof or real client footage. Do not use a generated scene to imply that an event happened, a client appeared, or a result was witnessed when it was not.

Add context or disclosure wherever a reasonable viewer could mistake the presenter, setting, action, endorsement, or outcome for a real recording.

Current Tools, Durable Process

Keep the gates when tools change.

This worked example uses Higgsfield, Seedance 2.5, ElevenLabs, and a separate correction step. It does not claim that any third-party UI, model, or feature will remain permanent.

If the stack changes, document the current selected model and preserve the same approvals: references, motion, voice, sync, QA, edit, delivery, and release.

Copy or Print

The release checklist.

Copy this into the project record or print the page. There is no separate file and no fake download.

Reference pack approved and assigned to the correct presenter.
Scene and motion created with the current selected model recorded in the project notes.
Approved ElevenLabs voice assigned and final audio reviewed.
Separate lip-sync correction pass completed.
Identity, mouth timing, and movement each reviewed.
Captions checked against final audio and the edit watched on a phone-sized screen.
Generated presenter disclosure and context reviewed. The clip is not framed as documentary proof or real client footage.
Approved scheduler profile, caption, media, date, time, and status confirmed.
CREATE comment-to-DM path tested through the public guide link before release.
Final human approval recorded.

Keep the whole workflow connected

From an approved video to a useful next step.

For the earlier workflow, HeyGen supplied the presenter and Zernio handled publishing. This series uses Higgsfield plus dedicated lip sync. Use GoHighLevel Social Planner or your connected scheduler, and verify the saved account, media, time zone and status before release.

To delegate draft preparation and scheduling through your coding agent, read the GHLCLI phone-to-post field guide.

Watch Jay’s walkthrough on YouTube. The example uses Codex and requires configured tools and permissions.

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Need help adapting the review gates to your content system? Contact Ian.

Looking for the older full no-camera field guide using HeyGen and HyperFrames? Read the AI Shorts Machine.