Caret vs Onboarding0

Caret brings system-wide AI autocomplete to macOS with a single keystroke: Tab. Unlike tools that require you to open a specific app or switch contexts, Caret operates at the OS input layer — any text field, any application, anywhere on your Mac. It reads the surrounding text for context and offers completions inline, with zero UI chrome. The implementation uses macOS Accessibility APIs to hook into the text input stack across all applications. Context is gathered from the active window's text content, and completions are generated via a cloud LLM (with local model support on the roadmap). There's no menu bar app cluttering your workflow — just Tab when you want help, nothing when you don't. The simplicity is the product. While Raycast, Copilot, and similar tools add layers of UI, Caret bets that the right abstraction is "Tab, everywhere." For high-volume writers, support staff, and developers who live in diverse tools all day, this is the kind of ambient AI that actually reduces friction rather than adding it.

Onboarding0 is an AI agent that transforms a company's scattered documentation and organizational knowledge into a structured, personalized onboarding experience for new hires. Built by Leon Arnovitz (former VP of Engineering), the tool connects to existing docs, maps the org structure, and then deploys an AI agent that guides each new employee to productivity — replacing the patchwork of wikis, Slack DMs, and first-day confusion that plagues most companies. The core insight is that onboarding failure is usually a knowledge retrieval problem, not a motivation problem. New hires spend weeks hunting for the right person to ask or the right document to read. Onboarding0's agent knows the entire knowledge graph upfront and serves answers proactively, adapting to each hire's role and department. Onboarding0 is currently free, which makes it an easy experiment for any startup or mid-size company tired of watching expensive new hires flounder in week one. The agentic approach distinguishes it from static wikis like Confluence or Notion — the agent asks follow-up questions, routes to the right person when it hits the edges of its knowledge, and tracks what each new hire has actually understood.