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The Profy desktop app is more than a web wrapper: it moves the AI’s entire execution plane onto your computer, while keeping assets — your account, skill library, and expert content — centrally managed in the cloud. This split lets the desktop operate on your local files, browser, and screen, while still sharing the same skill and expert ecosystem with the web and mobile clients.

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The Two-Plane Model

One rule explains the whole architecture: data lives where it is consumed.

Execution stays local

The agent loop runs directly on your machine, isolated by an OS-level sandbox (macOS Seatbelt). Working with local files, driving the browser, and recording the screen never round-trip through the cloud.

Assets stay in the cloud

Skills, experts, and memory have a single source of truth in the cloud — a skill created on the web is instantly available on desktop, and skills distilled on desktop show up on every other device.

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Two-Process Architecture

The desktop app is built from two cooperating processes:
  • Electron main process: windows, browser automation (CDP), computer use, the recording overlay, and other system capabilities
  • Python sidecar: runs the full agent loop; only two kinds of cloud communication remain — an entitlement check when a conversation starts (prepare) and a settlement write-back when it ends (finalize)

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Local-First Session State

Desktop session history is stored as append-only JSONL files under ~/.profy/ on your machine — the single source of truth for conversations:
1

Every turn lands on disk immediately

Each turn (user message, AI reply, tool calls) is written synchronously to a local rollout file. Cross-turn context is rebuilt from local history — cloud hiccups never break your conversation context.
2

Cloud projection with async compensation

After a conversation ends, a “projection” is sent to the cloud for web-side visibility and billing settlement. Failed write-backs are never dropped: they enter a local retry queue with exponential backoff until eventually consistent.
3

The UI reads local disk directly

Session lists and message history are read straight from local disk on desktop — your full history is browsable offline. Cloud sessions are merged into the view, with the local version winning for the same session.
Plugin activation is persisted locally too: once enabled, a plugin stays active across sessions and restarts — no need to reselect it every time.

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Authentication: Access + Refresh Credentials

Desktop background processes never hold a server-side secret (server secrets never leave the datacenter). Instead they use the same dual-credential model as leading desktop clients:
  • Session token = refresh credential: captured at login, revocable server-side at any time, only ever touches the mint endpoint
  • JWT = access credential: stateless and verifiable, used on every business-call hot path

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The Record → Skill → Replay Loop

A capability loop unique to the desktop:
1

Record

Start recording and system-level event capture logs your workflow (clicks, typing, navigation). Recording data stays local.
2

Distill into a skill

Stopping the recording automatically triggers AI analysis: it parses the event stream, extracts intent, and saves a structured skill to your cloud skill library — instantly available on all devices.
3

Replay

Activate the skill in a new conversation and the AI reproduces the workflow through browser automation (trusted input events) and computer use, verifying the result after each step.

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The Billing Gate

Local execution does not bypass billing: before every conversation, the sidecar must pass the cloud entitlement check (prepare) — if it fails, the conversation is blocked. This mirrors Codex’s design: threads live locally, inference is guarded by a cloud billing gate. In desktop mode the cloud never provisions a cloud sandbox (execution is already local), so no redundant resources are spent.

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How It Compares