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Hi,

I built TalkBits because most language apps focus on vocabulary or exercises, but not actual conversation. The hard part of learning a language is speaking naturally under pressure.

TalkBits lets you have real-time spoken conversations with an AI that acts like a native speaker. You can choose different scenarios (travel, daily life, work, etc.), speak naturally, and the AI responds with natural speech back.

The goal is to make it feel like talking to a real person rather than doing lessons.

Techwise, it uses realtime speech input, transcription, LLM responses, and tts streaming to keep latency low so the conversation feels fluid.

I’m specially interested in feedback about: – Does it feel natural? – Where does the conversation break immersion? – What would make you use this regularly?

Happy to answer technical questions too.

Thanks

Hi HN — I’m exploring an idea and would love your feedback.

I’m a builder and user of Obsidian, validating a concept called Concerns. Today it’s only a landing page + short survey (no product yet) to test whether this pain is real.

The core idea (2–3 bullets):

- Many of us capture tons of useful info (notes/links/docs), but it rarely becomes shipped work.

- Instead of better “organization” (tags/folders), I’m exploring an “action engine” that:

  1.detects what you’re actively targetting/working on (“active projects”)

  2.surfaces relevant saved material at the right moment

  3.proposes a concrete next action (ideally pushed into your existing task tool)

My own “second brain” became a graveyard of good intentions: the organizing tax was higher than the value I got back. I’m trying to validate whether the real bottleneck is execution, not capture.

Before writing code, I’m trying to pin down two things:

- Project context signals (repo/PRs? issues? tasks? calendar? a “project doc”?)

- How to close the loop: ingest knowledge → rank against active projects → emit a small set of next-actions into an existing todo tool → learn from outcomes (done/ignored/edited) and optionally write back the minimal state. The open question: what’s the cleanest feedback signal without creating noise or privacy risk? (explicit ratings vs completion events vs doc-based write-back)

What I’m asking from you:

1.Where does your “second brain” break down the most?

capture / organization / retrieval / execution (If you can, share a concrete recent example.)

2.What best represents “active project context” for you today?

  task project (Todoist/Things/Reminders)

  issues/boards (GitHub/Linear/Jira)

  a doc/wiki page (Notion/Docs)

  calendar

  "in my head"

Which one would you actually allow a tool to read?

3.What’s your hard “no” for an AI that suggests actions from your notes/links? (pick 1–2)

  privacy/data retention

  noisy suggestions / interruption

  hallucinations / wrong suggestions

  workflow change / migration cost

  pricing

  others