Vibecode Descript
track this build5 steps, step by step0%KINDA · weekend project
You can build transcript-based cutting for simple clips, but Descript's editor, media pipeline, AI voice/video tooling, publishing, and collaboration are a serious product.
the project pack4 files · fastest path to a working personal build
You are building a lean indie version of Descript. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== README.md ===== # Descript indie build ## Goal Build the smallest trustworthy replacement for the core Descript workflow for one developer or a tiny team. ## Scope Transcribe media, map words to timestamps, allow text deletion to cut audio/video, then render via ffmpeg. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - polished nonlinear editor - overdub/voice tools - filler-word workflows - templates - cloud collaboration - rendering reliability If those capabilities are essential, use Kdenlive instead of pretending the gap is solved. ===== AGENTS.md ===== # Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs". ===== BUILD_PLAN.md ===== # Build plan ## Original build brief Build me a text-based clip cutter to replace Descript for simple edits. Requirements: - A local web app: Node + Express with a plain JS frontend, binds to localhost. - I drop an audio/video file into ./media/; the app transcribes it with whisperX for word-level timestamps, or the OpenAI Whisper API if a key is in .env. - The transcript renders as clickable words. I select and delete words or whole sentences; deleted spans go into a cut list I can undo from. - Render: build one ffmpeg trim/concat command that removes the cut spans from the original and writes ./output/<name>-cut.mp4 (or .mp3 for audio-only). - Pad each cut by about 80 ms so words are not clipped mid-syllable. - Save each project as JSON next to the media file (transcript + cut list) so an edit can be reopened later. - No accounts, no telemetry; everything stays on my machine except the optional Whisper API call. - Out of scope: multitrack timeline, overdub or AI voices, filler-word auto-removal, cloud anything. This is a cutter, not an editor. - README: installing ffmpeg and whisperX, and a warning that local transcription of long video is slow on CPU. ## Required capabilities - ffmpeg - speech-to-text/alignment - desktop or web editor - video rendering pipeline - optional hosted storage ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden. ===== .env.example ===== # Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
You are building a lean indie version of Descript. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== README.md ===== # Descript indie build ## Goal Build the smallest trustworthy replacement for the core Descript workflow for one developer or a tiny team. ## Scope Transcribe media, map words to timestamps, allow text deletion to cut audio/video, then render via ffmpeg. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - polished nonlinear editor - overdub/voice tools - filler-word workflows - templates - cloud collaboration - rendering reliability If those capabilities are essential, use Kdenlive instead of pretending the gap is solved. ===== AGENTS.md ===== # Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs". ===== BUILD_PLAN.md ===== # Build plan ## Original build brief Build me a text-based clip cutter to replace Descript for simple edits. Requirements: - A local web app: Node + Express with a plain JS frontend, binds to localhost. - I drop an audio/video file into ./media/; the app transcribes it with whisperX for word-level timestamps, or the OpenAI Whisper API if a key is in .env. - The transcript renders as clickable words. I select and delete words or whole sentences; deleted spans go into a cut list I can undo from. - Render: build one ffmpeg trim/concat command that removes the cut spans from the original and writes ./output/<name>-cut.mp4 (or .mp3 for audio-only). - Pad each cut by about 80 ms so words are not clipped mid-syllable. - Save each project as JSON next to the media file (transcript + cut list) so an edit can be reopened later. - No accounts, no telemetry; everything stays on my machine except the optional Whisper API call. - Out of scope: multitrack timeline, overdub or AI voices, filler-word auto-removal, cloud anything. This is a cutter, not an editor. - README: installing ffmpeg and whisperX, and a warning that local transcription of long video is slow on CPU. ## Required capabilities - ffmpeg - speech-to-text/alignment - desktop or web editor - video rendering pipeline - optional hosted storage ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden. ===== .env.example ===== # Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
You are building a production product version of Descript. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== PRODUCT.md ===== # Descript product brief ## Problem You can build transcript-based cutting for simple clips, but Descript's editor, media pipeline, AI voice/video tooling, publishing, and collaboration are a serious product. ## Product outcome Transcribe media, map words to timestamps, allow text deletion to cut audio/video, then render via ffmpeg. ## Target user A serious builder who needs a maintainable product foundation rather than a one-off demo. ## Required capabilities - ffmpeg - speech-to-text/alignment - desktop or web editor - video rendering pipeline - optional hosted storage ## Explicit non-goals for v1 - polished nonlinear editor - overdub/voice tools - filler-word workflows - templates - cloud collaboration - rendering reliability ## Success criteria - The primary workflow is measurable end to end. - Setup is reproducible in a clean environment. - Failure, recovery, and support paths are documented. - Product claims match what the implementation actually guarantees. ===== ARCHITECTURE.md ===== # Architecture ## Starting brief Build me a text-based clip cutter to replace Descript for simple edits. Requirements: - A local web app: Node + Express with a plain JS frontend, binds to localhost. - I drop an audio/video file into ./media/; the app transcribes it with whisperX for word-level timestamps, or the OpenAI Whisper API if a key is in .env. - The transcript renders as clickable words. I select and delete words or whole sentences; deleted spans go into a cut list I can undo from. - Render: build one ffmpeg trim/concat command that removes the cut spans from the original and writes ./output/<name>-cut.mp4 (or .mp3 for audio-only). - Pad each cut by about 80 ms so words are not clipped mid-syllable. - Save each project as JSON next to the media file (transcript + cut list) so an edit can be reopened later. - No accounts, no telemetry; everything stays on my machine except the optional Whisper API call. - Out of scope: multitrack timeline, overdub or AI voices, filler-word auto-removal, cloud anything. This is a cutter, not an editor. - README: installing ffmpeg and whisperX, and a warning that local transcription of long video is slow on CPU. ## Boundaries Separate the product into replaceable modules for interface, application logic, persistence, external integrations, and operational concerns. Keep domain logic independent from delivery frameworks and vendors. ## Production baseline - Configuration: validated at startup with safe local defaults where possible. - Security: least privilege, input validation, secret redaction, rate limits on abuse-prone paths, and no invented security primitives. - Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore instructions. - Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, and timeouts. - Observability: structured logs with request or operation IDs, an error-tracking hook, and health/readiness checks where a server exists. - Quality: unit tests for domain rules, integration tests at module boundaries, and one end-to-end critical-path test. ## Decision records For each major dependency, document why it was chosen, its failure mode, and how it can be replaced. Do not introduce infrastructure until a requirement justifies it. ===== AGENTS.md ===== # Agent instructions - Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code. - Implement milestone by milestone; keep each change reviewable and leave the application runnable. - Treat authentication, payments, encryption, imports, webhooks, and destructive actions as high-risk boundaries when present. - Never invent cryptography or silently weaken a requirement to make a test pass. - Use provider interfaces for external services and deterministic fakes in tests. - Add migrations and rollback or recovery notes for persistent data changes. - Log useful operational context without credentials, tokens, passwords, or personal data. - Update documentation and run all checks before completing a milestone. ===== MILESTONES.md ===== # Delivery milestones ## M0 — Decisions and scaffold - Confirm the runtime, persistence model, threat boundaries, and deployment target. - Create a reproducible local environment and continuous checks. ## M1 — Core workflow - Implement the smallest end-to-end product path with validation and tests. - Keep integrations behind interfaces. ## M2 — Trust layer - Add secure failure behavior, recovery paths, audit-relevant events, and data safeguards. - Test abuse cases and destructive operations. ## M3 — Operability - Add structured logs, error reporting hooks, health signals, backup/restore documentation, and deployment configuration. ## M4 — Release gate - Run a clean-install test, critical-path end-to-end test, dependency review, and documented rollback exercise. - Compare the shipped behavior with `PRODUCT.md` and publish remaining limitations. ===== OPERATIONS.md ===== # Operations ## Before release - Validate configuration and secrets at startup. - Define backup, restore, and rollback procedures and test them. - Document logs, error tracking, health signals, and alert ownership. - Set dependency update and vulnerability review expectations. ## Incident checklist 1. Contain the issue without destroying evidence or user data. 2. Record the timeline and affected scope. 3. Rotate exposed secrets and revoke compromised sessions or credentials. 4. Restore from a verified source when needed. 5. Document the root cause, remediation, and regression test. ## Launch constraint Do not market omitted Descript capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.
README.md
# Descript indie build ## Goal Build the smallest trustworthy replacement for the core Descript workflow for one developer or a tiny team. ## Scope Transcribe media, map words to timestamps, allow text deletion to cut audio/video, then render via ffmpeg. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - polished nonlinear editor - overdub/voice tools - filler-word workflows - templates - cloud collaboration - rendering reliability If those capabilities are essential, use Kdenlive instead of pretending the gap is solved.
AGENTS.md
# Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs".
BUILD_PLAN.md
# Build plan ## Original build brief Build me a text-based clip cutter to replace Descript for simple edits. Requirements: - A local web app: Node + Express with a plain JS frontend, binds to localhost. - I drop an audio/video file into ./media/; the app transcribes it with whisperX for word-level timestamps, or the OpenAI Whisper API if a key is in .env. - The transcript renders as clickable words. I select and delete words or whole sentences; deleted spans go into a cut list I can undo from. - Render: build one ffmpeg trim/concat command that removes the cut spans from the original and writes ./output/<name>-cut.mp4 (or .mp3 for audio-only). - Pad each cut by about 80 ms so words are not clipped mid-syllable. - Save each project as JSON next to the media file (transcript + cut list) so an edit can be reopened later. - No accounts, no telemetry; everything stays on my machine except the optional Whisper API call. - Out of scope: multitrack timeline, overdub or AI voices, filler-word auto-removal, cloud anything. This is a cutter, not an editor. - README: installing ffmpeg and whisperX, and a warning that local transcription of long video is slow on CPU. ## Required capabilities - ffmpeg - speech-to-text/alignment - desktop or web editor - video rendering pipeline - optional hosted storage ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden.
.env.example
# Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
PRODUCT.md
# Descript product brief ## Problem You can build transcript-based cutting for simple clips, but Descript's editor, media pipeline, AI voice/video tooling, publishing, and collaboration are a serious product. ## Product outcome Transcribe media, map words to timestamps, allow text deletion to cut audio/video, then render via ffmpeg. ## Target user A serious builder who needs a maintainable product foundation rather than a one-off demo. ## Required capabilities - ffmpeg - speech-to-text/alignment - desktop or web editor - video rendering pipeline - optional hosted storage ## Explicit non-goals for v1 - polished nonlinear editor - overdub/voice tools - filler-word workflows - templates - cloud collaboration - rendering reliability ## Success criteria - The primary workflow is measurable end to end. - Setup is reproducible in a clean environment. - Failure, recovery, and support paths are documented. - Product claims match what the implementation actually guarantees.
ARCHITECTURE.md
# Architecture ## Starting brief Build me a text-based clip cutter to replace Descript for simple edits. Requirements: - A local web app: Node + Express with a plain JS frontend, binds to localhost. - I drop an audio/video file into ./media/; the app transcribes it with whisperX for word-level timestamps, or the OpenAI Whisper API if a key is in .env. - The transcript renders as clickable words. I select and delete words or whole sentences; deleted spans go into a cut list I can undo from. - Render: build one ffmpeg trim/concat command that removes the cut spans from the original and writes ./output/<name>-cut.mp4 (or .mp3 for audio-only). - Pad each cut by about 80 ms so words are not clipped mid-syllable. - Save each project as JSON next to the media file (transcript + cut list) so an edit can be reopened later. - No accounts, no telemetry; everything stays on my machine except the optional Whisper API call. - Out of scope: multitrack timeline, overdub or AI voices, filler-word auto-removal, cloud anything. This is a cutter, not an editor. - README: installing ffmpeg and whisperX, and a warning that local transcription of long video is slow on CPU. ## Boundaries Separate the product into replaceable modules for interface, application logic, persistence, external integrations, and operational concerns. Keep domain logic independent from delivery frameworks and vendors. ## Production baseline - Configuration: validated at startup with safe local defaults where possible. - Security: least privilege, input validation, secret redaction, rate limits on abuse-prone paths, and no invented security primitives. - Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore instructions. - Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, and timeouts. - Observability: structured logs with request or operation IDs, an error-tracking hook, and health/readiness checks where a server exists. - Quality: unit tests for domain rules, integration tests at module boundaries, and one end-to-end critical-path test. ## Decision records For each major dependency, document why it was chosen, its failure mode, and how it can be replaced. Do not introduce infrastructure until a requirement justifies it.
AGENTS.md
# Agent instructions - Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code. - Implement milestone by milestone; keep each change reviewable and leave the application runnable. - Treat authentication, payments, encryption, imports, webhooks, and destructive actions as high-risk boundaries when present. - Never invent cryptography or silently weaken a requirement to make a test pass. - Use provider interfaces for external services and deterministic fakes in tests. - Add migrations and rollback or recovery notes for persistent data changes. - Log useful operational context without credentials, tokens, passwords, or personal data. - Update documentation and run all checks before completing a milestone.
MILESTONES.md
# Delivery milestones ## M0 — Decisions and scaffold - Confirm the runtime, persistence model, threat boundaries, and deployment target. - Create a reproducible local environment and continuous checks. ## M1 — Core workflow - Implement the smallest end-to-end product path with validation and tests. - Keep integrations behind interfaces. ## M2 — Trust layer - Add secure failure behavior, recovery paths, audit-relevant events, and data safeguards. - Test abuse cases and destructive operations. ## M3 — Operability - Add structured logs, error reporting hooks, health signals, backup/restore documentation, and deployment configuration. ## M4 — Release gate - Run a clean-install test, critical-path end-to-end test, dependency review, and documented rollback exercise. - Compare the shipped behavior with `PRODUCT.md` and publish remaining limitations.
OPERATIONS.md
# Operations ## Before release - Validate configuration and secrets at startup. - Define backup, restore, and rollback procedures and test them. - Document logs, error tracking, health signals, and alert ownership. - Set dependency update and vulnerability review expectations. ## Incident checklist 1. Contain the issue without destroying evidence or user data. 2. Record the timeline and affected scope. 3. Rotate exposed secrets and revoke compromised sessions or credentials. 4. Restore from a verified source when needed. 5. Document the root cause, remediation, and regression test. ## Launch constraint Do not market omitted Descript capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.
$ choose a build depth, inspect the files, then open the complete pack in your agent · this prompt is generated from the build plan · improve it via PR
They pay to avoid building and babysitting a media editor, not just for transcription.
xpolished nonlinear editor
xoverdub/voice tools
xfiller-word workflows
xtemplates
xcloud collaboration
xrendering reliability
share on X ↗"I just replaced Descript ($24/mo) with one prompt"
Don't feel like building it? These folks already made it free.
KdenliveA real editor with local transcription and transcript-based cutting; the AI copywriter did not come along.open source↗no votes, no pay-to-list · just what's real
Descript pricing
| plan | monthly | annual (per mo) | what you get |
|---|---|---|---|
| free | $0/user | $0/user | 1 media hour/editor/month; 100 AI credits one-time; 720p watermarked exports; unlimited projects |
| hobbyist | $24/user | $16/user | 10 media hours/editor/month; 400 AI credits/month; 1080p; 30 AI Speech minutes/month |
| creator | $35/user | $24/user | 30 media hours/editor/month; 800 AI credits/month; 4K; 120 AI Speech minutes/month |
| business | $65/user | $50/user | 40 media hours/editor/month; 1,500 AI credits/month; 300 AI Speech minutes/month |
| enterprise | custom | — | Custom media hours, AI credits, seats, security, support and contract terms |
free tier1 media hour/editor/month; 100 AI credits once; 720p watermarked exports; SquadCast 1 recording hour/editor/month, 1 show, 10 participants and 1 integration
billingmonthly + annual (up to 35% lower); annual billed upfront; paid editors billed separately
hidden costsExtra media hours and AI-credit top-ups are sold only on Creator and Business; adding editors multiplies the subscription.
verified 2026-08-14 · source ↗
Vibecode Descript
Kinda. The core of Descript is buildable in a weekend with the prompt on this page, but there are real gaps: polished nonlinear editor, overdub/voice tools. Read the honest list above before committing.
How much does Descript cost?
Descript costs about $24/month (Hobbyist, checked 2026-07-30), which is $288 per year.
What do I lose by replacing Descript?
Honestly: polished nonlinear editor; overdub/voice tools; filler-word workflows; templates; cloud collaboration; rendering reliability. If any of those are load-bearing for you, keep paying.
Is there an open-source alternative to Descript?
Yes: Kdenlive (A real editor with local transcription and transcript-based cutting; the AI copywriter did not come along.) The prompt is for when you want it exactly your way.