Build a Descript-style editor
~25 min TypeScript PythonWhat you’re building: Edit video by editing the transcript.
Primitives you’ll use: Sandbox, Agent and harness, Deployment (Docker Host)
Agent prompt
Start with your coding agent
A few quick questions, then copy a prompt for any coding agent.
Who is it for?
Pick one to start. The rest adapts to it.
What you're building
a video and audio editor where you edit the transcript Modelled on Descript, by Descript.
Media is transcribed; edits to the text (deleting words, rearranging) are applied to the underlying audio and video.
Primitives you'll use: Sandbox · Agent and harness · Deployment (App Engine)
- Edit media by editing a transcript
- Remove filler words
- Captions
- Publish or export
Source: www.descript.com. Descript is a trademark of its owner; this guide is not affiliated with or endorsed by them.
What you need on MIOSA
Each row is one thing to create before you start. The number matches the step that uses it.
- Organization and API key Scopes every call; a workspace key is all a worker needs.
miosa api-key create app-key --preset agentDocs - Sandbox The isolated Linux workspace the agent writes code and runs commands in.
miosa create app-box --template nextjs --waitDocs - A workspace per customer Isolates each customer’s machines, deployments, and data as they onboard.
miosa workspace create customer-1Docs - Branding and white-label Your name and slug on previews, deployments, and the desktop; customers never see MIOSA.
miosa orgDocs - Usage metering and bill-to Usage per customer, and which account pays for new machines.
miosa org billDocs - Agent and harness Turns a prompt into work: pick the harness and model a run uses.
miosa agent harnessesDocs - Deployment (App Engine) Publishes the app to an immutable, versioned URL with rollback.
miosa deploy create --from-sandbox app-box --name app --waitDocs
Architecture
How it maps onto MIOSA
Prompt to asset -> agent runs (`miosa prompt`, client.runs) streaming events that call your generation provider and write results into the sandbox
Heavy rendering and encoding -> a MIOSA sandbox jobs (ffmpeg or headless rendering), sized up with `--size`
Projects and assets -> managed Postgres (`DATABASE_URL`) for job metadata; files and volumes for the media
Preview before export -> a sandbox preview URL (`miosa preview create`)
Data and storage
Jobs (status, inputs, output path) are metadata; the media itself is large, so keep it as files in the render sandbox and a volume, not in Postgres.
Assets are content-addressed by hash so identical inputs are never regenerated.
Auth and tenancy
Your organization is the platform; customers never get a MIOSA account, they sign into YOUR product. One workspace per customer, created as they onboard, isolates their machines, runs and data.
miosa workspace create descript-customer-1Tag every machine and run with the customer id in `metadata`, and never query across customers. Meter usage per customer with GET /api/v1/usage and set who pays with PUT /api/v1/bill-to (/docs/platform/usage-and-billing).
Agent loop
Harness: OSA is MIOSA's own harness and works with any model provider you connect, including your own model.
Model: Anthropic (Claude). Calls use my own provider key (`miosa connections add models`); MIOSA platform keys are never used.
Sessions: one chat per project or conversation, so the agent keeps its context. The first `miosa prompt` on a sandbox uses `--new-chat` (a chat id is printed); every later turn passes `--chat <chat-id>`. `--reuse chat` keeps one new machine per chat so files persist.
Streaming: follow a run with `miosa run follow <run-id>` or client.runs.streamEvents(run.id), and steer or stop it with `miosa run steer` and `miosa run interrupt`.
The generation model is a provider you bring; the harness orchestrates the job in a sandbox and runs ffmpeg for everything deterministic. Keep generation and rendering as separate, retryable steps.
Steps
Create the render worker: a larger sandbox for encoding and compositing.
miosa create descript-box --size large --waitCheck: The sandbox is running.
Ingest: transcribe the media with a speech-to-text provider you bring, and store the transcript with word timestamps.
Check: The provider returns a clip or transcript and you store its job id.
Apply edits: deleting or moving words becomes a list of cuts that ffmpeg applies to the original media.
miosa prompt --sandbox descript-box --harness osa --model <anthropic-model-id> --chat <chat-id> "Assemble the final video from /workspace/jobs/<id> with ffmpeg and write it to /workspace/out"Check: The output plays, has the right duration, and the job row points to it.
Show progress: stream run events to the UI so a long render never looks hung.
miosa run follow <run-id>Check: The UI shows progress while the job runs and the final file when done.
Preview and export: serve the output for playback, and offer a download.
miosa preview create descript-box 3000 --name webCheck: The preview plays the clip; the download has the right size and format.
Publish the app that accepts jobs and plays results.
miosa deploy create --from-sandbox descript-box --name descript --dir /workspace --port 3000 --run-command "npm start" --waitCheck: The public_url accepts a job and plays the finished result.
Limits and costs
Rendering is the cost: size the sandbox to the job, set `timeout_sec` up to the longest render, and pause or destroy workers when the queue is empty.
Provider usage (generation, speech) is billed by those providers; store your own job-level cost.
Prototype: keep it to one machine at the default size, skip replicas and custom hostnames you do not need, and delete everything when you are done.
Acceptance checks
A job runs from input to a playable output file.
A failed provider call leaves the job retryable, not stuck.
Progress is visible while a job runs.
Each customer is isolated in its own workspace and usage is metered against them.
Everything it created can be deleted with nothing left running.