Show HN: ChatGPT UI for rabbit holes

Original Article ↗ Hacker News Discussion ↗

Overall reception

  • Many commenters find the UI fresh, fun, and “more than a gimmick,” praising how easy it is to fall into “rabbit holes” similar to Wikipedia or TVTropes.
  • Several say they could see themselves using it regularly for learning and research, calling it addictive and “infinite hyperlinks.”
  • Others see it as an important UX experiment in how humans might better interact with LLMs.

UX & interaction model

  • Core idea: branching, column-based “cards” where clicking highlighted terms spawns new panels, preserving context.
  • Strong comparisons to:
    • Wikipedia rabbit holes.
    • Obsidian / personal wikis.
    • Andy Matuschak’s “stacked notes” / Miller columns.
    • Mind maps and git-like branch graphs.
  • Many ask for:
    • Tree / map / zoomed-out view of all branches.
    • Parallel branches instead of replacing columns.
    • Back/forward navigation and keyboard-only usage.
    • Ability to resize tiles and keep multiple branches visible.
    • Highlight-to-delve or manual link creation for arbitrary text.

Visual design & usability

  • UI praised as “crisp,” “snappy,” and uncluttered; speed is widely noted.
  • Critiques include:
    • Link styling is too subtle; requests to use classic blue/purple link colors.
    • Confusion that suggestions are just examples and any topic can be entered.
    • Mixed opinions on onboarding: some want a guided walkthrough; others fear it would be annoying.

Accuracy, learning, and limitations

  • Some users happily use it to summarize books, explore technical topics, or learn domains quickly, accepting that truth might be imperfect.
  • Others are wary: LLM hallucinations make it risky as a primary learning or discovery tool versus Wikipedia, which is seen as more reliable.
  • There are examples of clearly hallucinated facts; one person concludes LLMs are better at “doing” than “thinking” for you.

Technical/model questions & sustainability

  • Users speculate about API usage, caching, and which LLM is behind it; reports mention OpenAI 4o, Anthropic, and possibly Groq, but this is unclear.
  • Many request:
    • Ability to use their own API keys or local/OpenAI-compatible endpoints (e.g., Ollama).
    • Open sourcing the code or exposing the UI as a reusable component.
  • Concerns about API cost and rate limits; some sessions reportedly stopped answering.