How to Build an AI Video Editing Workflow with Claude Code and Hyperframes
Claude Code and Hyperframes let you generate motion graphics, animated overlays, and synced captions from plain-language prompts. Here's how it works.
Why Video Editing Workflows Are Ripe for Automation
Video production bottlenecks rarely happen in the camera room. They happen in post — specifically in the repetitive, time-consuming work of adding motion graphics, syncing captions, and building animated overlays frame by frame in a timeline editor.
A single short-form video can require hours of work that follows the exact same pattern every time: drop in a lower third, animate the title card, sync captions to the audio transcript, apply brand colors, export. That’s not creative work. It’s mechanical work that follows rules — and that’s exactly the kind of work Claude Code handles well.
This guide walks through how to build an AI video editing workflow using Claude Code and Hyperframes. By the end, you’ll have a working system that generates motion graphics, animated overlays, and synced captions from plain-language prompts, without touching a timeline editor for any of it.
What Claude Code and Hyperframes Do Separately
Before getting into how they work together, it helps to be clear on what each tool actually does.
Claude Code
Claude Code is Anthropic’s agentic coding environment. It’s not a chat interface where you ask questions — it’s an agent that can plan multi-step tasks, write and execute code, call external APIs, read and modify files, and chain together operations autonomously.
The key thing for video workflows is that Claude Code can receive a plain-language instruction like “add a lower third with the speaker’s name at the 0:04 mark, styled to match our brand guide,” and then figure out the steps required to make that happen — including calling the right API with the right parameters.
If you’re new to how Claude Code organizes reusable tasks, understanding Claude Code skills is a good starting point. Skills are the building blocks that let you define repeatable operations Claude can reuse across projects.
Hyperframes
Hyperframes is a motion graphics and video overlay generation platform built for programmatic use. Rather than requiring manual keyframing or After Effects templates, it exposes an API that accepts structured instructions — element type, timing, style, text content, position — and returns rendered video layers or composited clips.
This makes it a natural fit for agentic workflows. Claude Code can generate the structured API calls. Hyperframes executes the rendering. You get the output.
What the Combined Workflow Produces
When you connect Claude Code to the Hyperframes API, you can automate three categories of video post-production work:
Motion graphics — Title cards, animated intros, kinetic text, logo reveals. You describe what you want in plain language and Claude Code translates that into Hyperframes API calls with timing, style, and animation parameters.
Animated overlays — Lower thirds, speaker labels, stat callouts, product highlights, progress bars. These are time-coded overlays that appear and disappear at specific moments in the video.
Synced captions — Word-level or sentence-level captions that animate in sync with an audio transcript. Claude Code can parse a transcript (or generate one from an audio file via a transcription API), then pass the timing data to Hyperframes to render styled caption tracks.
The workflow handles all three. You don’t need separate tools or separate processes for each type.
Prerequisites
Before building, make sure you have:
- Claude Code access via the Anthropic API or Claude.ai Pro
- A Hyperframes API key — available through the Hyperframes developer dashboard
- Basic familiarity with Claude Code skills — if you haven’t set one up before, installing and customizing Claude Code marketplace skills covers the setup process
- A transcript file or audio file if you want synced captions (
.srt,.vtt, or raw text with timestamps works) - Brand style reference — a JSON or markdown file with your brand colors, fonts, and spacing rules. Claude Code will use this to style everything consistently.
You don’t need to know Python or JavaScript at a deep level to follow this guide. Claude Code will write most of the code. But understanding what it’s doing helps you prompt it accurately and troubleshoot when something goes wrong.
Step 1: Define Your Skill Structure
Claude Code works best when you give it well-scoped skills rather than one massive instruction. For a video editing workflow, three skills make sense:
generate-motion-graphic— Takes a description, timing, and style reference, returns a rendered motion graphic clipadd-animated-overlay— Takes element type, text content, timecode, and position, returns an overlay layersync-captions— Takes a transcript and style preferences, returns a rendered caption track
You can chain these skills into a full workflow so that a single top-level prompt triggers all three in sequence and stitches the results together.
To create the first skill, open Claude Code and describe what you need:
Create a skill called generate-motion-graphic. It should:
- Accept a plain-language description of the motion graphic
- Accept a timecode (start and duration in seconds)
- Accept a brand style JSON file path
- Call the Hyperframes API to render the result
- Return the rendered file path and any error messagesClaude Code will scaffold the skill, write the API integration, handle errors, and create the input/output structure. You review and adjust.
Step 2: Build the Hyperframes API Integration
Once the skill structure is in place, Claude Code needs to know how to talk to Hyperframes. The key API endpoints you’ll use are:
/elements— Create text, shape, or image elements with animation properties/compositions— Combine elements into a single composition with a timeline/render— Trigger rendering and get back a file URL or download link
Ask Claude Code to write a reusable API wrapper:
Write a Hyperframes API client that:
- Authenticates with an API key stored in environment variables
- Exposes functions for creating elements, creating compositions, and triggering renders
- Handles rate limiting with exponential backoff
- Returns structured responses with the rendered asset URLClaude Code will produce a working client. This becomes the foundation for all three skills.
The key insight here is that you’re not writing this integration by hand — you’re specifying what it needs to do and letting Claude Code produce the implementation. This is the same approach that scales well across multi-step content workflows.
Step 3: Generate Motion Graphics from Plain-Language Prompts
With the API integration in place, the motion graphics skill is straightforward to test.
Try a prompt like:
Generate a motion graphic for a 4-second intro. It should show the company name "Northlight" fading in from the left against a dark background, followed by the tagline "Built for speed" appearing below it. Use the brand style from /assets/brand.json. Place it at the start of the video.Claude Code will:
- Parse the description into structured Hyperframes element parameters
- Map “fading in from the left” to the appropriate Hyperframes animation type (
slide-in-leftwith opacity transition) - Pull the font, color, and spacing values from your brand JSON
- Create the composition with correct timing
- Trigger the render and return the file path
The output is a video file — an actual rendered motion graphic clip, not a template or placeholder.
You can iterate quickly from here. Change the animation style, adjust the timing, try a different layout — each instruction goes to Claude Code, which handles the API calls, re-renders, and returns the updated file.
Step 4: Add Animated Overlays at Specific Timecodes
Animated overlays require more precision because they need to appear and disappear at specific moments in the source video.
The workflow here uses timecodes directly:
Add a lower third overlay at 0:32 that displays "Sarah Chen, Head of Product" in white text on a semi-transparent dark bar. Animate it sliding in from the left, hold for 4 seconds, then slide out. Use the standard lower-third position (bottom 20% of frame).Claude Code parses the timecode, converts it to seconds, builds the Hyperframes element with animation keyframes, and positions it correctly in the composition.
For multi-speaker videos, you can batch this:
Add speaker label overlays for each of the following timestamps:
- 0:12 — "Marcus Webb, CEO"
- 1:45 — "Priya Nair, Engineering"
- 3:20 — "David Lim, Sales"
Each should use the same style: white text, dark translucent background, slide in from left, hold 3 seconds.Claude Code processes all three as a loop, makes the API calls in sequence, and returns all three overlay files. You get batch output from a single instruction.
This kind of batched, timecoded overlay work is exactly where boosting productivity with AI video automation pays off most — the manual version of this takes 20–30 minutes per speaker label.
Step 5: Sync Captions to Audio Transcripts
Synced captions are the most technically involved part of this workflow, but also the most automatable.
The input is either:
- A pre-formatted transcript with timestamps (
.srtor.vtt) - A raw audio file, which Claude Code can send to a transcription API (like Deepgram or AssemblyAI) to get word-level timestamps
Once Claude Code has the transcript with timestamps, the caption skill works like this:
Generate a synced caption track for the attached transcript. Style the captions as:
- Sentence-by-sentence (not word-by-word)
- White text, bold, centered, bottom third of frame
- Fade in and out (200ms transitions)
- Use our brand font from brand.json
- Export as a composited video layerClaude Code segments the transcript into caption groups, maps each group to its start/end timecodes, creates Hyperframes text elements for each caption, and builds a composition that fires each caption in sequence.
The result is a caption track that looks designed — not the default auto-caption styling from most platforms.
For teams publishing video across multiple channels, this integrates naturally with social media content repurposing workflows where the same video gets reformatted for different platforms with different caption styles.
Step 6: Chain the Skills Into a Full Post-Production Pipeline
The real productivity gain comes from running all three skills in sequence against a single video.
Here’s what a full pipeline prompt looks like:
Post-produce this video file: /videos/product-launch-raw.mp4
1. Generate a 3-second animated intro using the brand style from brand.json
2. Add speaker labels from the attached timestamps CSV
3. Generate synced captions from the attached transcript
4. Composite everything into a single output file
Output the final video to /videos/product-launch-final.mp4Claude Code treats this as a sequential workflow: skill one outputs the intro file, skill two outputs the overlay layers, skill three outputs the caption track, and then a final composition step merges all four layers (source video + intro + overlays + captions) into the final output.
The whole thing runs without you touching a timeline editor.
For teams producing marketing campaign videos at scale, this kind of pipeline cuts post-production time dramatically. A process that took a video editor an afternoon runs in minutes.
Step 7: Add Review and Approval Steps
Fully automated video production is useful for high-volume, lower-stakes content. For anything going to a broad audience, you’ll want a review step before final export.
Two approaches work well:
Slack integration — Claude Code posts a preview link to a Slack channel after rendering. A team member reviews and replies “approve” or “revise.” If revise, Claude Code accepts the feedback as a new instruction and re-renders. This is the same pattern described in AI video generation with Slack for team review workflows.
Conditional logic in the workflow — You can set up the pipeline to pause after rendering and wait for a human confirmation signal before compositing the final output. Agentic workflows with conditional logic make this straightforward to implement without custom code.
Either approach keeps humans in the loop where it matters without slowing down the parts that don’t need review.
Step 8: Handle Errors and Edge Cases
A few things will go wrong when you first run this workflow. Common issues:
Timecodes don’t match the video duration — If your overlay timecodes extend past the video end time, Hyperframes will error. Add a validation step: Claude Code checks the video duration before generating overlays and warns you if any timecode exceeds it.
Brand JSON is missing required fields — Claude Code will either error or fall back to defaults. Define which fields are required in your brand JSON schema and have Claude Code validate the file on load.
Transcript segmentation produces awkward caption breaks — If your transcript has long sentences, auto-segmentation can create captions that are hard to read. Set a character limit per caption (40–50 characters works well for most screens) and have Claude Code re-segment accordingly.
Render queue delays — Hyperframes may queue renders during high-traffic periods. Build in a polling loop: Claude Code checks render status every 10 seconds and proceeds when the status returns complete.
These aren’t showstoppers. They’re one-time fixes that make the workflow robust.
Where Remy Fits Into This
If you want to take this workflow further — building a proper web interface around it, adding a database for storing video projects, or creating a client-facing portal where teams can submit video briefs and receive finished output — that’s where Remy comes in.
Remy compiles full-stack applications from annotated specs. You describe the video workflow tool you want — the project intake form, the asset library, the approval queue, the render history — and Remy generates the backend, database, auth, and frontend as a deployable application.
The Claude Code + Hyperframes workflow you built becomes the engine. Remy becomes the product wrapper around it.
For example, a spec section for a video production portal might read:
## Project Submission
Users can submit a video project with: title, source video URL, transcript file, speaker CSV, brand style selection. The system queues the project for post-production. Status updates are visible on the project dashboard.Remy turns that into a working application — real auth, real database, real backend — not a mockup. The AI video editing workflow you’ve built gets a proper interface without you writing frontend code from scratch.
You can try Remy at mindstudio.ai/remy.
Practical Use Cases
This workflow applies across several contexts where video production happens regularly:
Marketing teams — SaaS product demo videos need consistent branding across many assets. The pipeline handles title cards, overlays, and captions automatically for every new video.
Content creators — YouTube and blog content benefits from automated captions and branded intros without hiring a video editor for every upload.
Customer success — Video testimonials need speaker labels and captions. The batch overlay skill handles a full quarter of testimonials in one run.
Agencies — Teams that have scaled video production with AI use exactly this kind of pipeline to handle client work at volume without proportional headcount growth.
Frequently Asked Questions
Do I need coding experience to set this up?
You need to be comfortable giving precise instructions and reading code to spot errors. Claude Code writes the actual code. But you’ll need to understand what it’s doing well enough to catch mistakes and iterate. If you’ve worked with APIs or used Claude Code for other automations before, the learning curve is manageable.
Can Claude Code handle multiple video formats?
Yes, with caveats. Claude Code itself is format-agnostic — it generates the API calls based on your instructions. Hyperframes handles format support on its end. You’ll want to check Hyperframes’ supported input formats before building, but most common formats (MP4, MOV, WebM) are covered.
How do I keep captions consistent across different videos?
Store your caption style preferences in a reusable style JSON file and reference it every time you run the sync-captions skill. Claude Code pulls the settings from the file, so as long as the file doesn’t change, output is consistent. Update the file once when you want to change the style globally.
What’s the difference between this and using a video editing SaaS with AI features?
Most video editing SaaS tools with AI features give you a UI with preset options. This approach gives you a programmable workflow — one you can modify, extend, and integrate with other systems. You’re not limited to what the UI exposes. If you need batch processing, custom logic, or integration with your existing tools, a code-driven workflow is more flexible. The tradeoff is setup time upfront.
Can I use this for short-form social media content?
Yes. Vertical format, square format, and short durations all work. You’ll want to define separate brand style files for different aspect ratios (16:9 for YouTube, 9:16 for Reels, 1:1 for LinkedIn) and reference the right one based on the target platform. Claude Code can select the appropriate style automatically if you tell it the target platform in your prompt.
How do I handle videos in multiple languages?
The captions skill works with any transcript, regardless of language. The main consideration is font support — make sure your brand font includes the required character sets, or specify a fallback font for each language. Claude Code can manage conditional font selection based on detected language in the transcript.
Key Takeaways
- Claude Code translates plain-language prompts into structured Hyperframes API calls, handling motion graphics, overlays, and captions without manual timeline work.
- The workflow runs as three chained skills:
generate-motion-graphic,add-animated-overlay, andsync-captions. Each can run independently or as a full pipeline. - Batch processing is a core advantage — multiple speaker labels, multiple videos, or multiple caption styles can be processed from a single instruction.
- Review and approval steps integrate cleanly via Slack or conditional workflow logic, keeping human oversight without slowing down the automated parts.
- Common errors (timecode mismatches, missing brand fields, render delays) are all fixable with validation steps Claude Code can handle.
- If you want to wrap this workflow in a proper application — with a UI, user auth, and a project database — Remy compiles that from a spec, so you’re not writing the frontend from scratch.
