AI coding tools integrate poorly with IDEs, servers, and workflows

Developers and technical workers find that AI coding assistants—whether embedded in IDEs or running as CLI agents—create friction rather than reducing it: small agent windows feel cramped, editor UX breaks (hidden close buttons, unwanted editor groups), and MCP/skill integrations are absent from most tools. Non-technical users who vibe-code working prototypes hit a wall when it's time to deploy to enterprise servers, since AI agents can't directly reach internal infrastructure. Underlying models powering IDE-embedded search are often cheap and unreliable, forcing users to route queries through slower external tools like Codex. No single tool cleanly covers the full loop from code generation to search to deployment, leaving users stitching together CLI agents, IDEs, and manual git diffing.