The running app
Your app live in the window as it changes — or open on your phone for mobile. You watch it work, you don't imagine it.
Describe it.
Watch it get built.
Coding agents can already write code and run commands. Gravy runs the whole application — starts it, shows it to you live, deploys it through your own accounts, and surfaces the errors your users hit — all in one desktop workspace, on the models you already pay for.
App screenshot
01 · The gap today
The agent wrote the code. Now what?
The hard part of building an application was never typing the code. It's everything wrapped around it — getting the thing to actually run, seeing it work, hosting it somewhere real, and finding out fast when it breaks. Today's editor and terminal agents are genuinely good at writing and editing files. Then they hand you a summary and stop, and the running, hosting, and watching are still yours.
Gravy is built for the part that's left. It lives in its own desktop workspace — not an editor pane, not a chat tab — and treats a finished outcome as the unit of work: a passing build, an app you can click, a live deploy, a production error tracked down. You direct it and watch it happen, in front of you, the whole time.
02 · The loop
From a sentence to production.
The whole loop runs in one window — not just the writing part. Every step shows its work as it goes.
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01 · Describe
Say what you want shipped.
Open a repo you already have, or start fresh, and describe the outcome. Your codebase, conventions, and past decisions are already loaded — you don't paste files or re-explain the project every session.
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02 · Write
It edits the real files.
Changes land as patches to actual files, each shown as a reviewable diff before it touches disk — so you approve the work, you don't fish it out of a chat window.
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03 · Run & test
It runs the project for real.
Installs dependencies, sets up the environment, and runs the build, tests, and type-checks in a live terminal. A red test or a stack trace feeds straight back in and gets fixed — you're not the courier between the error and the agent.
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04 · Preview
It shows you the app running.
Gravy figures out what the repo can run — a web app, an API, a mobile build — starts it, and opens the result in front of you. Web previews embed in the window; mobile opens on your actual phone over Expo Go. Not a localhost URL you go chase.
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05 · Deploy
Ship it in a sentence.
Connect Vercel or Fly once. Say "deploy" and Gravy picks the right account and ships — no copy-pasting tokens, no re-authing a CLI, no remembering which project maps to which environment.
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06 · Monitor
Catch what breaks in production.
Connect Sentry and the real errors your users hit show up inside Gravy — so you reproduce and fix them where you wrote the code, instead of bouncing to a dashboard and back.
03 · What it actually removes
The parts that slow real builds.
Not abstract features — the specific friction that turns a two-hour change into a two-day one.
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"It runs on the agent's machine, not mine."
Most agents hand you a diff and a localhost URL, then leave the running to you. Gravy installs, configures, and starts the app itself — and embeds the running result so you see it work the moment it's ready.
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Environment setup eats the first hour.
Missing dependencies, the wrong Node version, an unset env var, a port already in use. Gravy resolves what the project needs to run and surfaces the failures in plain language instead of a wall of red.
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Deploying is its own separate ritual.
Tokens, CLI logins, picking the right project and environment. Connect Vercel, Supabase, Sentry, or Fly once and Gravy resolves the right account automatically — no per-command prompts, no secrets pasted into a chat.
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Production breaks where you can't see it.
The error lives in a dashboard you have to remember to check. Gravy pulls Sentry errors into the workspace so a real user-facing bug becomes a task you can act on, not a tab you forgot to open.
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Every new chat forgets your project.
Re-explaining the codebase, the conventions, the decisions you made last week. Gravy keeps project memory across sessions, so context carries forward and the work picks up where it left off.
04 · The work area
Everything in one place, as it happens.
Building normally means juggling an editor, a terminal, a browser, a deploy dashboard, and an error tracker. Gravy puts the four things you keep alt-tabbing to in a single view, each updating live as the work runs.
The terminal
Every command and its output, streamed — installs, builds, tests, deploys. Nothing happens in a process you can't see.
The diff
Each change as a reviewable diff before it lands, so you approve edits instead of discovering them later.
The files
Your project tree, shared by you and the workspace — open anything, edit by hand whenever you want.
05 · Integrations
The tools you'd reach for, already wired.
Connect a service once. From then on Gravy uses it on your behalf — picking the right account automatically, with no per-command permission prompts and no tokens to paste. Web apps today; mobile previews on a real device over Expo Go.
- GitBranches · commits · push
- VercelDeploy from a sentence
- SupabaseDatabase & auth
- SentryProduction errors in-app
- ExpoPreview mobile on a real device
- ExaWeb search & fetch
06 · Models
Strong defaults. Your model when you want it.
Out of the box, coding runs on a GPT-5-class model, with Claude Opus for design-heavy frontend work. Bring a subscription you already pay for — Claude, Codex, Copilot, Gemini — drop in your own key across 14+ providers, or run on managed Gravy AI. Switch per project, per task, per turn, and your credentials never leave your machine.
14+
providers, plus Bedrock, Azure, and Vertex for enterprise
FAQ
What people ask before switching.
What's the difference between an AI coding assistant and an AI coding agent?
An assistant suggests — autocomplete, inline edits, chat in a sidebar. An agent acts — it edits the files, runs the build, opens the app, deploys it, and reads the errors that come back. Cursor and Copilot started as assistants and are growing toward agents inside the editor. Claude Code and Codex are terminal agents. Gravy is a desktop workspace where the agent owns the whole loop, not just the editing.
Can an AI agent actually run my app and show me when something breaks?
Some can run commands; very few show you the running app. In Gravy, when the agent makes a change, the app restarts and the preview updates in the same window — web embedded, mobile streamed to a real device over Expo Go. Build errors, runtime crashes, and production Sentry errors come back into the workspace as items the agent can fix, instead of dashboards you have to remember to open.
How do AI coding tools handle deployment?
Most don't — you copy what the agent wrote, switch to a terminal, and run a deploy command with your own tokens. Gravy connects to Vercel, Supabase, Sentry, and Fly via OAuth, picks the right account automatically, and runs the deploy from inside the workspace. The agent treats deployment as a step in the loop, not a separate ritual.
Can an AI agent preview an app on my phone while it builds it?
Yes — Gravy uses Expo Go to stream the running mobile app to your real device over the local network. You see real touch, real keyboards, real navigation as the agent edits. That's a faster signal than a desktop simulator and it catches the things simulators miss.
Will an AI coding agent remember my project between sessions?
Most chat-style agents start every conversation cold, so you re-explain the codebase and the decisions every time. Gravy uses persistent project memory (Honcho) so conventions, structure, and prior decisions carry across sessions. The next chat picks up with context instead of from zero.
Which AI model is best for coding?
It depends on the task. GPT-5-class models tend to be strong at backend and systems work; Claude Opus is a popular pick for frontend and UI-heavy tasks; Gemini and others do well on long-context refactors. Gravy lets you switch model per task across 14+ providers, OAuth a subscription you already pay for (Claude, Codex, Copilot, Gemini), or use managed Gravy AI that picks per task.
Do I need to use Cursor or VS Code to use an AI coding agent?
No. Cursor and Copilot live inside the editor; Claude Code and Codex live in the terminal. Gravy is its own desktop workspace — the editor, terminal, preview, deploy, and errors all sit in one window. You can still keep your editor for hand-edits; Gravy opens the same files on disk.
Stop reading summaries. Start watching it run.
Download Gravy and point it at a real project — yours, or one it sets up for you. You'll have something running in minutes.