PocketBot: AI compiles automations to JavaScript for cost-effective, deterministic scheduling

How PocketBot works

PocketBot takes a different approach to agent-style automation by eliminating LLM calls during execution. Instead of having an AI re-reason every time an automation runs, the system compiles your natural language request into a JavaScript script that runs on a schedule in a sandboxed runtime.

The process works like this:

• You describe what you want in plain language (e.g., "Send me a Slack summary of my unread Gmail every morning at 8am")
• A fast model (Tier 1) checks if a script already exists for this request
• If not, a coding model (Tier 2) writes the JavaScript, tests it in a sandbox, resolves your actual Slack channels and Gmail account, and saves it
• From then on, it runs as a cron job with deterministic code - no AI in the loop

Key architecture: Pocks and Mocks

PocketBot uses two main components:

• Pocks: Your personal automations running with your data, stored on your device. Your data doesn't go anywhere else.
• Mocks: General templates used to create automations (like sending an email) that contain no sensitive data, just the actions. As more users contribute Mocks to the community, less LLM involvement is needed.

Technical benefits

• Cost reduction: JavaScript execution is significantly cheaper than LLM inference on every trigger
• Deterministic behavior: Same input produces same output every time
• Offline capability: Scripts work offline once created (running server-side on schedule)
• Performance: Eliminates the latency of LLM calls during execution

Launch integrations

PocketBot launches with 20+ integrations including Google Suite, Slack, WhatsApp, TikTok, Twitter, Notion, and Todoist.

Privacy and security

• No account system - your identity is a random device UUID
• OAuth for all integrations - PocketBot never sees your passwords
• Once compiled to JavaScript, no AI reads your data on every run
• Mock data is used to test automations during creation, with PII sanitization
• AWS Bedrock ensures inputs/outputs aren't used to train models

Current status

The mobile app has 800+ testers on iOS TestFlight (free and available now), with an App Store release coming soon. The pricing will be $5/month with additional integrations planned. The tool is designed as a phone-first experience for setting up automations from your pocket.