Control macOS GUI from the CLI so an AI can test, click, type, and see screens

Many engineering and QA teams in enterprises are stuck: web automation tools can't touch native macOS UIs, manual testing is slow and error-prone, and brittle screen-scraping or image-only bots create high maintenance costs. This is a tangible problem for enterprise software vendors, banks, healthcare, and corporate IT—roughly 100,000 organizations whose combined addressable spend supports an estimated $12.0B market (about $120k ACV per enterprise) for enterprise-grade GUI automation and developer productivity. You could build a CLI-first macOS GUI controller: a lightweight agent plus CLI and SDK that exposes accessibility-backed selectors and actions (click/type/read), a vision fallback, an action protocol that is easy for LLMs to call, and built-in audit logs and replay for CI. Focus on integrations for LLM orchestrators, CI runners or ephemeral macOS hosts, enterprise auth/consent flows, and developer ergonomics (deterministic selectors, retries, visual diffs) so an AI agent can plan, execute, verify, and report multi-step GUI flows reliably. Market timing is favorable because agentic LLMs can now plan multi-step automation and many critical workflows still live in native macOS apps that web tooling cannot reach, which explains the high market score (92/100) and attractive revenue potential (86/100). Standing out requires practical defensibility: prioritize reliability, security, and enterprise SLAs over flashy demos, acknowledge hard challenges (Apple API limits, permissions model, OS churn, and high support cost), and compete on stability, auditability, and CI/agent integration rather than just vision-based clicks.