segmenta

Just did - asked Claude Opus 4.8 in Claude Desktop to generate an image of a horse. It drew an SVG by hand in code and said (verbatim): "I drew it by hand in code, not with an AI image generator. There's no diffusion/photo image model wired into this session."

On the labs: agreed that end users don't care about the model - only that the job gets done well, which is our argument too. At any point some model is best at a given job, so any single lab is behind for a portion of time on a portion of tasks.

Thanks for trying it out and reporting this.

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.

Makes a ton of sense, and the framing is correct - it's easy to build for the ecosystem you live in. We plan to add M365 (Outlook) soon. And noted on "Continue with Microsoft" at sign-in.

I think we agree on the diagnosis: generating code was never the whole bottleneck. Where we differ is the conclusion. Work is implementation plus verification (specing, testing, checking it actually solves the problem). Pre-AI, implementation was so slow that verification hid inside its schedule - you verified while the next thing was being built. AI collapsed implementation time, so verification is now the exposed bottleneck - and the cheapest way teams absorb that today is more human hours. So: output per person is up, hours up too, and the delivered-value gain is real but smaller than the raw output gain suggests. Which I think explains both our observations.

You can use both private LLM instances or hosted ones. On private we support Ollama, LM Studio and any OpenAI compatible API.

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.

That's fair - "your data lives on your machine as plain files" is the concrete claim, and something we should lead with. Will take a look at how Apple frames it, thanks.

vLLM works today - it exposes an OpenAI-compatible endpoint, and you can point Rowboat at a custom base URL in model settings.

Thank you! And would love to share notes. The tiny-models-only discipline is interesting; we do special handling just to keep local models from being overwhelmed, so I'd like to hear how far you've pushed it. You can find me on Discord, if you want to chat on anything.

Thanks for the concrete list! I understand where you are coming from.

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).

Yes - the files on disk are the source of truth. If you edit a note directly in the vault, Rowboat picks it up.

Yes! You can use local models through Ollama and LM Studio. We do some special handling when you use local models, such as suppressing background agents when you chat, so the model is not overwhelmed.

Local-first for us means: your data such as emails, notes, meetings, the knowledge graph - lives on your machine as plain Markdown, readable and deletable, and the app doesn't require our servers to run. You can also go fully local for the LLM with Ollama or LM Studio. We do special handling there, like suppressing background agents during chat, so local models aren't overwhelmed. That's the core of the product.

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.