AI Interface Systems

Early thoughts on how AI is fundamentally changing interface design…

Terminal / Command Line - Traditional OS: CLI (bash, zsh) - AI OS: LLMs (text, voice) - What’s changing: - Language becomes the universal command surface - Power shifts from syntax → intent interpretation - Prompting evolves into command composition and reuse

• Process Manager
  • Traditional OS: init, schedulers, background processes
  • AI OS: Agents
  • What’s changing:
    • Execution becomes continuous, not request/response
    • Agents decide when to act, not just how
    • Orchestration over time becomes the core capability
• Kernel
  • Traditional OS: Resource coordination, system rules
  • AI OS: Plans (and logs)
  • What’s changing:
    • Plans are no longer documents; they are coordination primitives
    • They constrain execution across humans + machines
    • Planning shifts from prediction to alignment and constraint
• Filesystem
  • Traditional OS: Files, directories, permissions
  • AI OS: Information in files (not apps)
  • What’s changing:
    • “File over app” becomes foundational (Kepano’s philosophy)
    • Apps stop being the source of truth; files do
    • Memory moves from opaque storage → inspectable structure
• File Formats
  • Traditional OS: Fixed formats (.doc, .jpg, .mp3)
  • AI OS: Multimodal, metadata-rich files that can mutate and change based on context while retaining the original form
  • What’s changing:
    • A “file” becomes a bundle of structured data + intent
    • Content can transform across text, audio, image, summary, plan
    • Format is no longer presentation-specific, but capability-specific
• RAM / Working Memory
  • Traditional OS: Volatile memory
  • AI OS: Context windows
  • What’s changing:
    • Context is abundant but fragile
    • Systems confuse recall with understanding
    • Long-term value comes from promoting context → files → plans
• Device Drivers
  • Traditional OS: Hardware drivers
  • AI OS: Tools, APIs, system actions
  • What’s changing:
    • Models don’t act directly; drivers translate intent into execution
    • Tool reliability becomes system stability
    • Permissions and scope become first-order concerns
• Window Manager / Views
  • Traditional OS: Desktop environment
  • AI OS: Apps as Views
  • What’s changing:
    • MVC decouples: models ≠ views ≠ controllers
    • Apps stop being “systems” and become projections of state
    • The same underlying data can render across many surfaces
• Interface Layer
  • Traditional OS: GUI, input devices
  • AI OS: Dynamic, state-aware interfaces
  • What’s changing:
    • Interfaces respond to what the system knows, not just user input
    • Chat is a bootstrap UI, not the end state
    • IDEs and OSes evolve toward adaptive, context-revealing surfaces
• Interoperability Layer
  • Traditional OS: IPC, system calls
  • AI OS: Interoperability (not integrations)
  • What’s changing:
    • Systems coordinate through shared primitives, not brittle glue code
    • IDEs and OSes become peers in a larger execution environment
    • Data, plans, and actions flow across boundaries by default
• Security & Permissions
  • Traditional OS: Users, roles, sandboxing
  • AI OS: Identity, consent, memory access
  • What’s changing:
    • Personalization requires explicit permission models
    • Memory access becomes as sensitive as file access
    • Without this, intelligence defaults to surveillance
• Logs & Observability
  • Traditional OS: Logs, stack traces, system monitors
  • AI OS: Decision traces, plan diffs, tool histories
  • What’s changing:
    • Trust comes from inspectability, not confidence scores
    • Systems must explain what happened, not just answer
    • Debugging intelligence becomes a core UX problem