Tago Movie

Tago Movie

Turn your story into a short drama with an AI Agent that helps plan, script, and produce it.

Coming soonLaunches Monday, Nov 9 · in 24 days

Design Tools·AI & Machine Learning

What is Tago Movie?

Tago Movie is a browser-based tool for creating AI short dramas. You bring an idea, a novel, or an existing script, and the Agent helps organize the story, episodes, script, characters, scenes, and shots. The site describes a six-step guided workflow that runs from story outline through episodes, script, characters and scenes, shot videos, and finally subtitles and upscaling.

It is aimed at first-time creators who have no screenwriting, camera, or prompting experience, as well as novelists and scriptwriters who want to turn their chapters into characters and shots. Brands and content teams can use it for product stories, branded series, and promotional content.

What sets it apart, according to the page, is the combination of agent-assisted drafting with editable control. Users can reuse character designs, voices, and locations across shots and episodes to support continuity, edit dialogue and shots, regenerate selected clips, and use a canvas mode for flexible asset organization on a paid plan. Text input of up to 400,000 characters is supported, and TXT, DOC, and DOCX uploads up to 5 MB each are accepted.

Tago Movie runs in the browser without local model installation, though generation and previews require an internet connection. Credit costs vary with features, models, and settings, and AI results can vary, so the page advises reviewing each shot.

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PricingUsage-based

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Joined Oct 2026

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Shipping
Don't waste your time on polishing it up thinking about adding one more killer feature that would definitely get you a ton of users. No, don't do it. Get it ready, bugs free, just one single feature — ship it and let users tell you what they think about it while you're building another app.

Ship One Bug-Free Feature And Let Users — Not Your Roadmap — Pick The Next One

Max's one-line MVP rule: scope to a single feature, fix the bugs, then move on. He explicitly rejects the urge to add 'one more killer feature' pre-launch — the next app is the better use of that time, and real users will tell you what to build next. The portfolio approach only works if each app reaches users fast.

Pricing
our test showed us that 99 would have made us more when you calculate all the numbers in the spreadsheet it was like a little bit better right it wasn't like massively better and so it's kind of like why don't we do that and it was like I don't know it just felt like overreaching right we were doubling our price we want good vibes to continue we can always go up

Double the price but stop short of the data-maximizing number

Skylight's tests showed $99 narrowly beat $79 on spreadsheet ARPU but felt like overreaching after doubling from $39. They chose $79 as a middle ground with high confidence it would hold, leaving room to raise again later. Optimizing purely for ARPU-max ignores brand equity and customer sentiment; leaving a little on the table today preserves the ability to raise again in future without triggering a backlash moment.

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