We looked into the specific issue you mentioned. Collapsing replies does exist in the product, but we found it doesn't work for emails sent from Outlook (our guess on why you might have faced this). We are fixing this in the next release, shipping this week. Hope you give it a try.

In hosted, we support: OpenAI, Anthropic, Gemini, OpenRouter, Vercel AI Gateway.

No native Amazon Bedrock support, but you could use OpenRouter or LiteLLM with the Bedrock key and point Rowboat to that today.

Will go through these and see what we could support. If you drop your stack into a GitHub issue, that's the best place for us to work through it (and for others to +1).

Some third-party APIs we couldn't avoid (search has to be an API call). For TTS/STT we deliberately chose cloud quality over local support for now - if there's demand, we'll support local.

On PostHog: usage metadata only, never content. Anonymous install ID unless you sign in to Rowboat; email and plan attached after. Everything sent is cataloged in apps/x/ANALYTICS.md. We shipped v1 with no analytics and were flying little blind on whether anyone used it. If you build without the PostHog env vars, it no-ops entirely.

In addition, we have a caffeinate mode (in new release) that keeps your machine awake so the connection doesn't drop. We are also working on a mobile app.

1. True - no OS-level container today. The constraint is approval gating: consequential actions surface as a permission ask before they run (a separate supervisor LLM flags anything outside your intent). 2. True today. We'd deprioritized generic IMAP (drafts-on-thread is unreliable cross-provider), but you're the third person in this thread to raise it, so we'll scope it properly.

3/4/5. Today: Deepgram for STT, ElevenLabs for TTS, Exa for search.

At least for search we supported more providers earlier (e.g. Brave) and found the assistant's skills degrade when they can't lean on provider-specific capabilities, like Exa's granular search. So we trimmed and went deep on a few.

Feel free to raise a GitHub issue with what you want us to support and we'll do our best.

On somebody needs to care enough: I meant that AI agents by design have no intrinsic motivations, so (stating the obvious) they do not really care if the product works or actually solves the user's problem. This puts the onus on the human to care for the problem to really solve it, vs just building something. With increased AI output there are too many things to care about which the AI won't, and I believe that's why people might be working more and not less

This is a great idea. Almost like an interview mode where the assistant asks pointed questions (using your capsule spec as a guideline) and writes the answers back into the graph.

And thanks for the production context - this is not something we would have come up with. So really helpful data point.

We're exploring a company brain - team-level context rather than just individual, and the context capsule seems like a great way to distill the individual knowledge graph into team level useful context!

Thanks for the Granola script. Yep, I never imagined markdown would be the killer format.

What they do have is funding and distribution, but that's the same advantage every incumbent has against every startup.

The single biggest advantage we have is that the labs are tied to their ecosystems. Claude still doesn't have image generation; Gemini-flash-lite is the best cheap model, but Gemini's apps can't use the latest models from Anthropic or OpenAI. We can always use the best tool for each job.