workflowAItemplates

From Script to Short: Using AI to Generate Vertical Episodes (Workflow Template)

UUnknown

2026-02-16

10 min read

A practical AI + human workflow to convert scripts into caption-ready vertical episodes—step-by-step template for microdrama creators.

Turn a long-form script into bingeable vertical episodes — fast

Pain point: You have a script or long-form episode but publishing polished, caption-ready vertical episodes feels slow, manual, and expensive. This workflow template shows how to use AI generation (visuals, voice, assembly), human editing, and accessibility-first captioning to produce microdrama-style vertical episodes at scale in 2026.

Executive summary — what you'll get

In this article you'll find a step-by-step, repeatable workflow that converts a script into a series of vertical episodes optimized for TikTok, Instagram Reels, YouTube Shorts, and emerging vertical streaming platforms like Holywater. The template balances AI generation (visuals, voice, assembly) with essential human passes (performance editing, caption QC) and includes concrete prompts, file naming conventions, export specs, time estimates, and a publish checklist.

Why this matters in 2026

Short-form serialized storytelling — often called microdrama — became mainstream between 2023 and 2026. Large funding rounds and platform launches (for example, Holywater's expansion in early 2026 and rapid growth from AI-driven companies like Higgsfield) reflect how the industry is optimizing for mobile-first episodic formats and AI-assisted production workflows.

Today, creators who harness AI correctly win two advantages: dramatically faster output and the ability to iterate using data-driven creative optimization. But the pitfalls are real: hallucinated captions, poor voice clones, and out-of-context AI visuals. This workflow mitigates those risks with human checkpoints and accessibility-first practices.

Overview: the 9-step workflow template

Script audit & episodic breakdown
Create a vertical storyboard & shot list
Generate visuals with AI (scenes, backgrounds, elements)
Produce or synthesize voices (AI TTS or recorded VO)
Assemble a rough cut with automated tools
Human editing pass: pacing, performance, color
Generate accurate captions & accessibility markup
Finalize branding, metadata, and platform specs
Publish, monitor, and iterate

Step-by-step: From script to vertical episode

1) Script audit & episodic breakdown (30–90 minutes)

Open the master script and treat it like a serialized outline. For mobile-first microdrama, aim for episodes that are 30–90 seconds. Longer arcs work too, but short episodes improve retention and discovery on vertical platforms.

Identify natural beats and cliffhangers — mark them as episode end candidates.
Create an episode sheet: title, runtime target, 3-4 key beats, opening hook, cliffhanger or CTA.
Flag any assets that need rights clearance (music, brand logos, real locations).

Example: A 12-minute script can become 8 x 90s episodes or 16 x 45s episodes depending on pacing and distribution strategy.

2) Vertical storyboard & shot list (30–60 minutes)

Design scenes specifically for 9:16. Vertical framing changes blocking and visual language — close-ups, vertical motion (rising/falling), and foreground elements work better than wide landscapes.

Create 1-slide storyboards per episode: main shot, B-roll, transition, on-screen text cues.
List visual assets: characters, props, backgrounds, VFX, SFX cues, subtitle window placement (top/middle/bottom).

3) AI visual generation: scenes, motion, and continuity (30–180 minutes per episode; parallelizable)

Use multimodal AI tools to generate vertical-friendly scene elements. In 2026, platforms like Higgsfield, Runway, and other generative-video providers offer rapid scene synthesis and style transfer — but they differ in continuity and control.

Practical tips:

Set the canvas to 9:16 from the start.
Use consistent scene prompts to maintain character apparel, lighting, and color grade across episodes.
Export elements as layered or alpha-video clips when possible so editors can combine AI backgrounds with human-shot plates.

Sample prompt for a microdrama scene (adjust for your chosen generator):

"Vertical 9:16 cinematic close-up of a woman holding a weathered photograph. Moody neon rim light, shallow depth, film grain, evening street reflected in glass. Maintain same jacket and hairstyle across shots. 24fps. Export 1920x1080 cropped to 9:16."

4) Voice & performance: AI TTS vs. human VO (15–60 minutes + reviews)

AI voice cloning and TTS in 2026 are far more natural, but do your due diligence. Use AI voices for placeholders and rapid prototyping; use human voice actors or legally licensed clones for final deliverables.

If using voice cloning, obtain written consent and document rights.
Prefer hybrid approaches: AI for iterations, human VO for final performance or as a safety pass.
For microdrama, subtle emotional cues matter — schedule a human ADR pass if budget allows.

Prompt template for voiced line (for TTS fine-tuning): "Deliver with restrained panic, breathy, 0.5s inhale before last word, 3% volume dip on 'remember'."

5) Automated assembly: the AI rough cut (10–45 minutes per episode)

Move raw assets into an AI-assisted editor (Descript, Runway, or Higgsfield-style editors). Your goals: align dialogue with visuals, auto-generate captions, and create a pacing baseline for human editors.

Import script or transcript to auto-place subtitles and voice lines.
Use automated scene transitions and pacing presets (e.g., "microdrama-pace: 45s").
Export a rough MP4 with burned-in timecode for review.

This step turns hours of manual assembly into minutes — but treat it as a first draft, not a final product.

6) Human editing pass: pacing, continuity, and color (60–180 minutes per episode)

Now a human editor refines the AI rough cut. Focus on emotional beats, continuity across episodes, and platform-specific pacing (e.g., faster hooks for TikTok).

Trim to tighten — remove any redundant lines the AI left in.
Match cuts to sound design cues for emotional hits.
Do a color-grade pass that unifies AI-generated footage and live plates.

Collaboration tips: use cloud-based review tools (frame.io, Descript comments) so directors and producers can annotate exact frames.

7) Captioning & accessibility: accuracy-first (15–45 minutes per episode)

Accurate captions are non-negotiable. AI-generated captions speed things up, but humans must QA them for names, slang, non-speech audio cues, and timing.

Export both embedded (burned) captions and separate SRT/VTT files.
Follow readability rules: 32–42 characters per line, 1–3 lines, 2–3 second minimum display time.
Include speaker labels and sound effect annotations when relevant (e.g., [door creaks], [siren].)
For accessibility compliance, keep transcripts verbatim and supply them with metadata (language, timestamps).

Sample QA checklist: spelling of characters' names, punctuation for pauses, accurate speaker mapping, ensure captions don't block on-screen text.

8) Branding, export specs, and metadata (15–30 minutes per episode)

Optimize each episode for the target platform. Vertical episodes need platform-specific delivery settings and metadata to succeed in discovery.

Export: H.264 or H.265 for vertical; 9:16 resolution (1080x1920 recommended).
Thumbnail: create vertical-first stills, include readable title text in the top third (avoid platform UI overlays).
Metadata: concise episode title, a 2-line episode description, hashtags, and chapter markers if supported.
Deliverables: final MP4, SRT/VTT, closed-captioned MP4 (burned and soft), thumbnail JPG/PNG.

9) Publish, monitor, and iterate (ongoing)

Release on a cadence (daily, weekly) and monitor retention metrics and audience feedback. Let data guide creative changes; use AI-driven A/B testing to try alternative hooks or caption styles.

Track first 3–7 days of watch-through rate, replays, and comments per episode.
Iterate on hooks and opening 3 seconds — the highest impact area for retention.

Template resources: file naming, roles, and timings

Standardize your pipeline with names and roles so automation works reliably.

File naming (example): SERIES_S01_E01_v01_edit.mp4, SERIES_S01_E01_v01_captions.srt — see more on file naming & docs.
Roles: Producer (oversees cadence), Script Editor (episodic breakdown), AI Designer (prompts & generation), VO Director (talent & rights), Editor (final cut), Captioner (QC), Distribution Manager (upload & metadata).
Rough timing per 60–90s episode: script breakdown 15m, AI generation 45–120m (parallel), rough assembly 20m, human edit 60–120m, caption QC 20m, export 10m.

Prompts, automation snippets, and practical examples

AI scene prompt (concise)

"9:16, close-up, dusk, rain on window, female protagonist (green coat, short hair) stares; subtle hand tremor; cinematic, neon rim light; maintain character continuity across episodes."

AI voice prompt (concise)

"Female voice, late 20s, weary but defiant, pacing 120 wpm max, soft sigh before each sentence end, slight reverb for intimate mic."

FFmpeg crop example to derive vertical from widescreen (automation)

ffmpeg -i input.mp4 -vf "crop=1080:1920:420:0,scale=1080:1920" -c:a copy output_vertical.mp4

Adjust crop offsets to keep subject framed vertically. This is useful when repurposing existing horizontal footage — and when you're exporting from a local edit machine like a Mac mini M4.

Case study: A 6-episode microdrama run (example)

Scenario: You have a 12-minute short script. Convert into 6 x 60–90s vertical episodes.

Episode planning and script split: 60 minutes.
AI scene generation for key backgrounds and one VFX shot per episode: 6–12 hours total, parallel.
Voice rough TTS lines and one human VO session for final: 90 minutes.
Assembly and two human edit passes: 8–12 hours total.
Caption QC and exports: 3 hours.

Outcome: From raw script to publishable vertical series in ~3–5 working days with a small team, versus weeks with a traditional workflow.

Accessibility, ethics, and legal guardrails

AI accelerates production but raises rights and trust issues. Follow these rules:

Document consent for any cloned voice or likeness; keep written licenses.
Label AI-generated content where required by platform policy.
Keep an auditable transcript and source prompts for fact-checking and dispute resolution.
Use human caption QC for speaker accuracy and to avoid hallucinated text.

Advanced strategies & 2026 predictions

Expect these shifts through 2026:

Personalized episodic feeds: Platforms will stitch micro-episodes into custom sequences per user behavior, making granular episode metadata even more valuable.
AI-driven creative optimization: Real-time A/B testing of hooks and captions using generative variants will become routine.
Vertical streaming hubs: Players like Holywater are scaling mobile-first catalogs and investing in data-driven IP discovery — creators should tailor metadata and episode structure for these new distribution channels.
Hybrid production: The dominant model will be AI-first prototyping + human-finalization; full-AI releases will remain edge cases due to trust and legal concerns.

Companies like Holywater (expanded funding in January 2026) and AI video startups that reached large-scale valuations recently signal that both demand and tooling are aligned for serialized vertical content. Use this window to build repeatable processes.

Checklist: Quick quality-assurance before publish

First 3 seconds: strong hook (visual + caption) — yes/no?
Caption file synced and human-QA'd — yes/no?
Voice rights & VO credits documented — yes/no?
Thumbnail legible on small screens — yes/no?
Export matches platform specs (codec, bitrate, resolution) — yes/no?

Final takeaway: Balance speed with human judgment

AI shortens iteration loops and reduces assembly time, but human editorial judgment remains essential for emotional storytelling, legal safety, and accessible captions. Use the template above to run fast experiments, then lock in the best-performing creative with human polish.

Start your first episode — quick action plan

Pick one script and split it into a single episode target (60s).
Run one AI visual pass and one TTS draft in parallel.
Assemble a rough cut and perform a single-human edit pass.
Generate captions and publish to one vertical platform.
Measure retention for 7 days and iterate on the hook.

Call to action

If you want a ready-made, editable workflow checklist (includes prompt templates, file naming rules, and FFmpeg snippets), download the free template and try it on your next script. Transform your scripting process into a scalable vertical episode factory — faster, accessible, and ready for platforms like Holywater and the major socials in 2026.

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Contributor

Senior editor and content strategist. Writing about technology, design, and the future of digital media. Follow along for deep dives into the industry's moving parts.