Condense an article into a tight script, record the narration with a text-to-speech model, generate footage clip by clip and caption it from a transcript. Each stage runs in the same toolkit, and the final assembly happens in the video editor you already use.
You wrote a good article, a few hundred people read it, and then it sank down the archive. A short narrated video gives the same ideas a second life on the feeds where people scroll instead of search. The work is smaller than it sounds: cut the text into a script, record a voice, generate a few clips, caption it. Each stage has a model for it, and you stitch the result together yourself.
The research is already done. A finished article has a thesis, an order and examples, which is most of what a short video needs and exactly what a blank-page video lacks. You are not inventing content, you are changing its container, and that is a much easier job than starting a video from nothing.
The old objection is the cost of the pieces around the words: a voice, footage, captions. Picasso IA puts a language model, voice models, video models and a transcription model in one place, so a single sitting can cover all of it. The full catalog lists 502 models, and the pipeline below uses four kinds of them. New accounts get free credits, enough to run the whole chain once on a short post and see whether the format suits your writing.
It also fits what you already own. The same article can become a podcast episode or a faceless channel upload, so one piece of writing feeds several formats instead of one.
A post written to be read is a poor script. It has headings, links, asides and paragraphs that lean on the one before. Spoken, those become rambling. The condensing step is where most of the quality is decided, so give it a real prompt rather than pasting the post and hoping.
Use a language model for it. anthropic/claude-sonnet-5 and google/gemini-3.5-flash are both in the catalog, and both take a long article as input. Tell the model the format: one spoken script, one idea per sentence, a hook in the first line, no headings, no references to the page. Ask for the script split into short scenes, each with one line of narration and one line describing what should be on screen. That second line becomes your footage prompts later.
Keep the number of scenes honest. A short video that tries to cover every section of a long post will feel like a skim. Pick the one claim the article proves best and build the script around it, then link to the full post for everything else.
Read the script out loud before you generate a single voice file. Anything that makes you stumble will make the text-to-speech voice stumble, and fixing a sentence costs nothing while re-recording and re-generating footage costs credits.
Four jobs, four kinds of model. The names below are real catalog entries, but any of them can be swapped for a sibling if the first result does not fit.
| Stage | What it produces | Models to try | What you check |
|---|---|---|---|
| Script | Scene-by-scene narration and shot notes | anthropic/claude-sonnet-5, google/gemini-3.5-flash | Does it keep your main claim and drop the rest |
| Voice | The narration audio | elevenlabs/v3 | Pronunciation of names and terms, pacing |
| Footage | One clip per scene | google/veo-3.1, kwaivgi/kling-v3-video, bytedance/seedance-2.0 | Does each clip match the line it sits under |
| Stills | Optional key frames to animate | google/nano-banana-pro, black-forest-labs/flux-2-pro | Same look across scenes |
| Captions | Transcript of the finished voiceover | openai/gpt-4o-transcribe | Spelling of names, then timing in the editor |
The stills row is optional but useful. If the footage has to look like it belongs to one video, generate a still for each scene first in one image model, then animate the stills with a video model that accepts a starting image. Without that, each clip is a fresh roll of the dice and the look drifts from scene to scene. For a longer view of this technique, the page on AI B-roll covers how to prompt footage that supports a voiceover.
This is the order that wastes the fewest credits, because every stage is checked before the next one costs anything.
Most weak article videos fail the same few ways. They are all avoidable before generation, which is the cheap moment to fix them.
The tools produce parts, not a finished video. Nothing here assembles a timeline for you: the clips, the voiceover and the captions come out as separate files, and the cutting, timing and export happen in a video editor. That final step is real work, and a first edit usually takes longer than the generation did.
Pacing is the second limit. A language model can write a script that reads well, but it cannot hear whether a line lands too fast, and a voice model reads each sentence without knowing what the picture is doing. Expect to edit lengths and rebalance a few lines by ear.
Third, footage does not know your article. A video model makes a plausible clip from a description, so it cannot show your actual product screens, charts, quotes or data. Posts that depend on diagrams, code or numbers need those assets captured the normal way and dropped into the edit. And clips do not stay consistent on their own: a character or setting in scene one will look different in scene four unless you work from a shared reference image.
Finally, check the facts. A condensed script can drop a qualifier that made a claim true, and a spoken version feels more certain than the written one. Compare the script against the post before you record.
Technically yes, but some posts convert far better than others. Opinion pieces, how-tos, explainers and list articles map well to a script with a clear order. Posts built around screenshots, tables, code or long data walkthroughs lose most of their value when spoken, and the footage models cannot reproduce your real visuals. Choose the posts whose main idea survives being said out loud in under a minute or two.
Both anthropic/claude-sonnet-5 and google/gemini-3.5-flash are in the catalog and handle a full article as input. The difference is mostly taste: run the same prompt through each and keep the script that sounds more like you. What matters more than the choice of model is the instruction. Ask for spoken sentences, one idea each, a hook first and scene markers, and say what to leave out.
Write for the ear, then test. Short sentences, contractions and plain words read better than the formal register of a blog. In elevenlabs/v3 you can pick a voice, change the speed and push the style setting toward more expressive delivery, so try a couple of voices on the first paragraph before committing. Listen to the full file once, and respell any brand name or acronym the voice gets wrong.
Yes, for this workflow. The toolkit generates the script, the audio, the clips and the transcript, but it does not place them on a timeline. You will need an editor to lay the narration under the clips, trim to the beat, add captions and export for the platform. Any editor that takes audio, video and a text file works, including free ones, so the editor is not a new cost.
Run the finished narration through openai/gpt-4o-transcribe to get the text, correct the spelling, and bring it into your editor as captions. The transcript gives you the words, and the editor handles placement, styling and timing against the audio. Because you wrote the script, you can also paste it in directly and use the transcript only to check it. The page on automatic video subtitles goes deeper.
Only as well as your description does. A video model turns a text prompt or a starting image into a short clip, and it will not read your article for context. Write each shot as a concrete scene: subject, setting, camera movement, mood. Generate two options and pick the one that fits the line. For anything specific to you, such as your product, shoot or capture it yourself and cut it in.
Generate a still for each scene in one image model, such as google/nano-banana-pro or black-forest-labs/flux-2-pro, with a shared style description and the same reference image where you can. Then animate each still with a video model that accepts a starting image. This holds colors, characters and setting together better than generating every clip from text alone, although small differences between clips will still appear.
Only your own voice, or a voice you have clear permission to use. Do not recreate a real, identifiable person's voice or face without consent, and keep any people in generated footage fictional. The voices in elevenlabs/v3 are ready-made personas, so they sidestep the problem entirely. If your video quotes someone, attribute it in the narration instead of imitating them.
Mostly a question of each platform's current rules, so check them before posting. Requirements for length, aspect ratio, captions and the disclosure of AI-generated content differ by platform and change over time, and they are not something this page can quote reliably. Export from your editor in the shape the platform asks for, and label the video as AI-assisted where the platform requires it.
Every stage uses credits, and the cost depends on the model and the settings you pick. Text and speech are usually the cheapest steps, while video clips are the most expensive part, so the number of scenes and the number of retries decide the total. New accounts get free credits to try it. Current plans are on the pricing page, which is the only place to trust for numbers.
Your best article is already a script waiting to be cut. Open the Picasso IA toolkit, paste it into a language model and see how it sounds as a first scene list.
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