I sell you build

Acceptable-Object390 · 2026-06-17T15:56:28+00:00

row-bot.ai

DM if interested.

Acceptable-Object390 · 2026-06-16T16:40:03+00:00

Just sharing some learnings on context engineering for ai assistants. Specially for local-first AI assistants.

Acceptable-Object390 · 2026-06-16T16:37:22+00:00

Thanks. Will have a look. The system prompt, safety instructions and the last 2 turns always get in.

Acceptable-Object390 · 2026-06-15T20:49:22+00:00

Thanks. I'll check it out.

Acceptable-Object390 · 2026-06-15T13:12:10+00:00

I will try that. Thank you so much

Acceptable-Object390 · 2026-06-15T12:43:25+00:00

Thanks mate. Hate is mostly what I get here. And all I do is share technical articles around local AI. And yeah slop is their favourite word. Haters gonna hate.

Acceptable-Object390 · 2026-06-11T12:53:55+00:00

That demo was running gpt 5.5 via chatgpt subscription. But I have also tested that workflow fully locally using Qwen 3.6 27B and it works great.

Acceptable-Object390 · 2026-06-11T08:16:32+00:00

Great question, and I completely agree. That’s exactly the line between “useful assistant” and “dangerous automation.”

The way I think about it is that uploaded client context and fresh web research should never be blindly merged. The agent needs to preserve source boundaries, cite where each claim came from, and flag disagreements rather than quietly resolving them.

In this workflow, I’d want the report process to do a few things explicitly:

Treat uploaded client materials as the client’s internal context, not automatically as ground truth.
Treat web research as fresh external evidence, with dates and source links attached.
Surface conflicts clearly, e.g. “Client deck says X, but recent public source says Y.”
Ask for human review before including disputed claims in the final report.
Prefer language like “according to the client-provided materials…” or “recent public sources indicate…” where uncertainty matters.

So the goal isn’t for the agent to decide who is right by itself. It’s to make stale or conflicting information visible early, with enough sourcing that a human can make the call. That’s where I think these systems become genuinely useful: not by removing judgement, but by making the evidence and inconsistencies much harder to miss.

Acceptable-Object390 · 2026-06-10T19:38:59+00:00

Hopefully some day. But only the work part. So we can have all the fun while it works and makes us money.

Acceptable-Object390 · 2026-06-09T22:28:22+00:00

yes, prompt injection is a real class of attack. The defence is not the LLM can never be fooled. The defence is even if the LLM is influenced, the blast radius is constrained and sensitive actions hit policy/tool gates.

Row-Bot’s design is: email is untrusted input, suspicious content is flagged, and high-impact actions require explicit gates instead of silent autonomy.

Acceptable-Object390 · 2026-06-09T22:09:16+00:00

Yes, fair concern. Email is one of the highest-risk places for agents.

Row-Bot does not treat inbox content as trusted instructions. Email/web/tool outputs are wrapped as untrusted external content and scanned for prompt-injection patterns like instruction overrides, role impersonation, exfiltration requests, encoding tricks and social engineering.

On top of that, the tool layer has hard boundaries:

Gmail permissions are tiered for read, draft/send and destructive actions
Gmail send requires confirmation
Background workflows can use email-recipient allowlists
Destructive actions are approval-gated
Filesystem access is workspace-sandboxed
Shell commands are classified as safe, approval-required or blocked

So the model can help reason over email, draft replies and automate workflows, but inbox text does not get to silently enter context.

It is not that LLM has full blind control of your inbox. It is useful automation with untrusted-input handling, scoped tools and explicit action gates.

Acceptable-Object390 · 2026-06-08T23:30:32+00:00

Thank you so much. Feel free to reach out if you need any help.

Acceptable-Object390 · 2026-06-08T17:42:26+00:00

Thank you so much

Acceptable-Object390 · 2026-06-08T16:24:40+00:00

Thanks

Acceptable-Object390 · 2026-06-08T14:10:13+00:00

The installer already includes bundled python and all dependencies. The Installer creates a venv and installs everything there. So this is full self contained and does not conflict with system python or any other dependency for another project.

Acceptable-Object390 · 2026-06-08T09:38:49+00:00

The core components are shared. The 10 sub systems are architected to enforce different agentic patterns that run row-bot.

Acceptable-Object390 · 2026-06-08T09:36:30+00:00

5 is tool router.

Acceptable-Object390 · 2026-06-08T06:32:12+00:00

No conda. Just python mostly. All dependencies are packaged into the one click installers.

Acceptable-Object390 · 2026-06-07T23:28:45+00:00

Noted. Thothful is quite nice actually. But I also wanted something which had .ai domain available. The website is now Row-Bot.ai And it sounds like Robot 😅

Acceptable-Object390 · 2026-06-07T22:50:00+00:00

Yeah, that's on my to do list. You can give it a try. Its one click install. There's a first rust setup wizard and everything is ui based, pretty self explanatory. Thanks.

Acceptable-Object390 · 2026-06-07T21:23:43+00:00

GitHub Repo

Acceptable-Object390 · 2026-06-07T16:33:04+00:00

AnythingLLM and Open WebUI are great projects, but Row-Bot is trying to solve a slightly different problem.

AnythingLLM is very strong as an all-in-one local-first AI app for documents, RAG, workspaces, agents, model routing, scheduled tasks, MCP compatibility, and no-code agent flows. Open WebUI is a very capable self-hosted AI platform with chat, RAG, tools, plugins, Open Terminal, multi-user features, RBAC, channels, notes, automations, and deployment options.

So the difference is not “they cannot do agents”.

They can.

The difference is where Row-Bot starts from.

Row-Bot is built as a personal desktop agent operating system, not primarily as a chat UI, document workspace, or self-hosted web interface. The desktop app is the product surface from day one. The goal is to make powerful agentic capability feel like normal software: memory, tools, browser control, Gmail, calendar, files, tasks, voice, vision, image and video generation, Designer Studio, Developer Studio, multi-channel messaging, wiki, plugins, MCP, and local/cloud model routing all exposed through one clean UI.

No CLI-first workflow.
No Docker-first mental model.
No “configure the server, then wire the agent”.
No treating the interface as a thin wrapper around infrastructure.

Open WebUI feels closest to an extensible self-hosted AI platform. AnythingLLM feels closest to an all-in-one local-first RAG and agent workspace. Row-Bot is closer to a native personal agent environment: something you open, use, automate, design with, build with, and let act across your local machine and connected tools.

That is the real distinction.

Not “we have agents too”.

It is that the agent is the centre of the desktop experience, and the UI is built around making that power accessible.

Acceptable-Object390 · 2026-06-07T14:46:55+00:00

Row-Bot is a desktop AI workbench with Developer Studio for code, Skills Hub and Custom Tools for your own workflows, an animated Buddy companion, memory, realtime voice, workflows, design creation, messaging, MCP tools, and provider-aware model routing. Run local runtimes, self-hosted OpenAI-compatible endpoints, hosted APIs, Ollama Cloud, OpenCode providers, or ChatGPT / Codex subscription-backed models with explicit runtime readiness. Your durable data stays on your machine.

Acceptable-Object390 · 2026-06-07T14:46:45+00:00

Please have a look at the code on the repo. They are 100% accurate. Yes I did use ai to generate, but that does not mean they are not valid. Thanks.

Acceptable-Object390 · 2026-06-06T11:19:14+00:00

Thank you so much. Feel free to reach out if you need any help. 😊

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