Can Gamma be vibe coded?
AI presentation and document builder for decks, docs, and sites
An AI slide generator is buildable, but Gamma's strength is layouts, editing model, exports, hosting, analytics, and shareable deck/site UX.
Jump to the build brief ↓Checked Jul 2026
What you pay today, before any DIY hosting
medium editorial confidence
Buildability by layer
Screens, forms, and focused interactions
The repeatable job the product performs
Availability and legality of required data
Uptime, queues, support, and maintenance
Security, compliance, and user confidence
The achievable core
- Prompt an LLM for outline, generate slide/cards JSON, render with templates, export PDF/PPTX, and host a share page.
- Build a focused single-user workflow with real persistence, search, and export.
- A responsive interface with real empty, loading, success, and error states.
The parts a prompt cannot buy
- polished editor
- responsive card model
- exports
- analytics
- The last 20 percent is sync, migration fidelity, speed, and edge cases.
- Licensed content and distribution rights are not reproducible with an LLM.
Why people still pay
They pay because the output looks acceptable without wrestling with PowerPoint.
The last 20 percent is sync, migration fidelity, speed, and edge cases.
Licensed content and distribution rights are not reproducible with an LLM.
The brief
Context, requirements, acceptance criteria, non-goals, and the full production standard — as Markdown, ready for any coding agent.
Build brief — a focused alternative to Gamma
Context
**Gamma** — AI presentation and document builder for decks, docs, and sites. It currently costs $12/mo.
An AI slide generator is buildable, but Gamma's strength is layouts, editing model, exports, hosting, analytics, and shareable deck/site UX.
This brief describes a focused, single-operator replacement for the part of Gamma that is genuinely reproducible. It is deliberately narrower than the product it replaces, and it says so in writing. Build the useful core; do not pretend to have rebuilt the rest.
What you are building
Prompt an LLM for outline, generate slide/cards JSON, render with templates, export PDF/PPTX, and host a share page.
Build a focused single-user workflow with real persistence, search, and export.
A responsive interface with real empty, loading, success, and error states.
Requirements
Functional
Slide renderer.
Template system.
Export pipeline.
Hosted app.
Data and integrations
LLM API.
Optional image API.
Each of these needs a real account, credential, or quota. Set them up before writing feature code.
Non-functional
Accessibility: semantic markup, labelled controls, visible focus, and reduced-motion support.
Security: server-side secrets, validated input, and no credentials in the client bundle.
Reliability: retries with backoff on external calls, and a clear failure state when a provider is down.
Portability: the operator can export their data and leave without losing it.
Implementation brief
Build me an AI slide-deck generator to replace Gamma. Requirements:
A Node CLI around Slidev. `deck new "<topic>"` asks an LLM (key in .env) for
an outline, then slide-by-slide content as JSON: title, bullets, speaker
notes, layout name.
Render that JSON to a Slidev slides.md; `deck preview` runs the Slidev dev
server, `deck export` writes PDF and PPTX.
Five layouts: title, bullets, two-column, big-quote, image-right. Images are
optional via an image API key in .env; skip them cleanly when absent.
One theme file for fonts and colors so every deck matches without redesign.
`deck redo <n>` regenerates a single slide by number and leaves the rest
untouched.
Decks are files in ./decks/<slug>/ (slides.md plus assets), kept in git and
hand-editable after generation. No database.
No accounts, no telemetry; the only network calls are the LLM and optional
image API.
Out of scope: a web editor, share links with analytics, collaboration.
slides.md in my editor is the editor.
README: keys, export commands, and how to add a layout.
Delivery standard
Inspect the repository first, then write a short implementation plan before writing code.
Deliver the smallest complete end-to-end workflow first; every primary control must work against persisted data.
Use real validation and storage; never substitute fake dashboards, decorative controls, hard-coded success states, or mock integrations.
Include responsive layouts plus genuine empty, loading, success, validation, and failure states.
Keep secrets server-side in environment variables, provide .env.example, and never commit credentials or user data.
Add structured logs around every external call and return actionable errors without leaking sensitive details.
Write unit tests for the core logic and one automated test of the main user journey.
Finish with a README covering setup, architecture, data location, backups, tests, deployment, and known limitations.
Acceptance criteria
A clean install starts the app using only the README and .env.example.
The primary journey works from first visit through saved result, reload, edit, export, and deletion where applicable.
Invalid input, missing configuration, provider failure, and an empty database each have a usable state.
The interface works at 390px and 1440px, is keyboard navigable, and shows visible focus on every control.
Tests, type checking, linting, and a production build all pass with no ignored failures.
No part of the interface implies a live integration, security guarantee, or scale capability that was not actually built and verified.
Non-goals
Do not build these, and do not claim to have replaced them:
Polished editor.
Responsive card model.
Exports.
Analytics.
The last 20 percent is sync, migration fidelity, speed, and edge cases.
Licensed content and distribution rights are not reproducible with an LLM.
What you still own after launch
Secure credentials, rotate secrets, and handle provider rate limits.
Run migrations, backups, restores, and dependency updates.
Test the critical journey after every model, API, or hosting change.
Monitor failures and fix the edge cases a first prompt will miss.
Risk
**Manageable.** A personal version is realistic if you test the critical journey and keep reliable backups.
Editorial confidence in this assessment: medium. No independent one-shot implementation is linked yet.
Prior art
Working open-source software you can read, fork, or borrow from before starting:
[Slidev](https://github.com/slidevjs/slidev) — Open-source Markdown/HTML slide deck generator; good foundation for a developer-oriented c
Generated by [Can It Be Vibe Coded?](https://www.canitbevibecoded.com) · Full report: https://www.canitbevibecoded.com/gamma
You still own the product
- Secure credentials, rotate secrets, and handle provider rate limits.
- Run migrations, backups, restores, and dependency updates.
- Test the critical journey after every model, API, or hosting change.
- Monitor failures and fix the edge cases a first prompt will miss.
Open-source prior art
Before you start
Can Gamma be vibe coded?
Partly, if you narrow it. An AI slide generator is buildable, but Gamma's strength is layouts, editing model, exports, hosting, analytics, and shareable deck/site UX.
What can an AI coding agent reproduce from Gamma?
Prompt an LLM for outline, generate slide/cards JSON, render with templates, export PDF/PPTX, and host a share page. Build a focused single-user workflow with real persistence, search, and export. A responsive interface with real empty, loading, success, and error states.
What will a DIY Gamma replacement still be missing?
polished editor; responsive card model; exports; analytics; The last 20 percent is sync, migration fidelity, speed, and edge cases.; Licensed content and distribution rights are not reproducible with an LLM.
What do I still own after building a Gamma alternative?
Secure credentials, rotate secrets, and handle provider rate limits. Run migrations, backups, restores, and dependency updates. Test the critical journey after every model, API, or hosting change. Monitor failures and fix the edge cases a first prompt will miss.