Konxios

Over the past year, AI agents have become incredibly capable. They can write code, browse the web, edit files, automate repetitive work, and increasingly perform tasks that used to require a human sitting behind a keyboard.

That's exciting.

But I also think we're quietly normalizing something that should make all of us uncomfortable.

We're asking people to give these agents unrestricted access to their computers.

That means access to your browser, your SSH keys, your documents, your emails, your passwords, and every other piece of your digital life. The more capable an agent becomes, the more permissions we're encouraged to grant it. Somehow, that has become the default approach.

The problem is that capability and trust are not the same thing.

Just because an AI can access everything doesn't mean it should.

That never sat right with me.

I actually stopped using most AI agents for exactly that reason. Not because I thought they were poorly built or technically unimpressive, they're genuinely amazing, but because I wasn't comfortable giving software with so much autonomy unrestricted access to the same computer that holds my work, my personal data, my finances, and years of accumulated digital history.

Whenever I brought this up, I kept hearing the same advice:

Just buy a separate Mac mini and dedicate it to AI.

I understood the logic, but it felt like an admission that something fundamental was wrong.

Why should we need a second computer just to use AI safely?

That solution works for enthusiasts, but it doesn't scale to millions of people. If AI is truly going to become part of our everyday workflow, it should be designed so that people feel comfortable running it on the computer they already use every day, not because they have no choice, but because the system itself has been built with trust in mind.

That question stayed in my head for months.

Eventually I realized I wasn't going to find the answer by waiting for someone else to build it. So I started building it myself.

That's how Konxios began.

Interestingly, I didn't start with the idea of creating another AI assistant or another coding tool. Those already exist, and many of them are excellent.

Instead, I started with a much simpler question:

How do you build an AI agent that's powerful enough to create software without giving it the keys to your entire computer?

Everything else grew from trying to answer that one question.

The answer I arrived at was isolation.

Instead of allowing an AI agent to operate directly inside macOS with unrestricted access, every capability should run inside an isolated runtime. If the agent needs a terminal, it receives its own Docker sandbox or Apple Virtualization environment. It can execute commands there without having unrestricted access to the rest of my machine.

Browser automation follows the same philosophy.

Rather than driving my personal Chrome or Safari profile, Konxios launches its own browser. That browser only knows about the websites I've intentionally signed into within Konxios itself. It doesn't inherit years of browsing history, saved passwords, banking sessions, or personal cookies. The AI only sees the environment I've explicitly created for it.

That distinction matters.

The goal isn't to make AI less capable.

The goal is to make powerful AI safe enough that people actually want to trust it.

The same philosophy extends to every capability inside Konxios. Reading files, modifying them, executing commands, browser automation, media generation, long-term memory, none of these are assumed. Every capability is permission-based. The user decides what the agent can access instead of the model deciding for them.

While building this security foundation, something unexpected happened.

I realized I didn't actually want another AI assistant.

Assistants answer questions.

Coworkers help you build things.

What I really wanted was an AI coworker that could write production code, build applications, remember previous work, manage projects, automate repetitive workflows, collaborate with specialized agents, and seamlessly switch between local and cloud models depending on the task. I wanted something that felt less like chatting with an LLM and more like working alongside another engineer.

That realization fundamentally changed the direction of the product.

Konxios stopped becoming another chatbot and slowly evolved into what I now think of as an AI Operating System - a workspace where models, agents, projects, tools, workflows, memory, and local execution all work together instead of existing as separate applications.

Looking around today, I see almost every AI company competing on one dimension: making models smarter.

That race absolutely matters.

Smarter models unlock entirely new possibilities.

But I also think we're missing another race that's just as important.

The race to build AI that people genuinely trust.

Because the future won't simply belong to the model with the highest benchmark score. It will belong to the systems that people are comfortable leaving running on their primary laptop while they step away for coffee. The systems that respect boundaries, ask for permission, protect private data, and make users feel like they're still in control.

Capability will attract users.

Trust will keep them.

That's the future I'm trying to build with Konxios.

I'd genuinely love to hear where others stand on this.

Would you let an AI control your primary laptop today?

If your answer is yes, what gives you confidence?

If your answer is no, what's holding you back?

Today is a big milestone for us.

After months of building, countless late nights, and more iterations than I can count, Konxios is officially live on Product Hunt. 🚀

The idea started with a simple frustration:

AI has become incredibly powerful, but actually using it still feels fragmented. Different models, different tools, different workflows, and different context.

So we built Konxios - a privacy-first AI workspace that brings local models, cloud models, agents, workflows, files, and tools together in one place.

This launch isn't the finish line - it's the beginning.

One thing I've learned throughout this journey is that shipping beats waiting for perfection. There are still plenty of features on our roadmap, but getting real feedback from real users is far more valuable than polishing in isolation.

If you're an Indie Hacker, I'd genuinely love your feedback - whether it's on the product, onboarding, positioning, or anything else you think could be improved.

And if you like what we're building, we'd really appreciate your support on Product Hunt today. ❤️

https://www.producthunt.com/products/konxios

Thanks to everyone who's been following the journey so far. On to the next milestone! 🚀

Hey Indie Hackers 👋

I’ve been building something for a while and finally shipped it - it's called Konxios.

It started from a simple frustration: local AI models like Ollama and LMStudio are powerful, but the experience around them is still very “bare bones.” You get a chat window… and that’s it.

I wanted something that felt less like a chatbot and more like a real AI operating system for your desktop.

So I built Konxios.

It’s a Mac desktop app that sits on top of Ollama/LMStudio and turns local models into a full AI assistant with an actual workspace.

Here’s what it includes:

• 30+ built-in tools (web search, file management, notes, browser automation, etc.)

• Persistent memory across conversations and sessions

• Goals → AI can break objectives into tasks and execute them

• Kanban board for tracking todos (To Do / In Progress / Review / Done)

• Workflows for complex automation (n8n-style but agent-driven)

• Agents + org chart (basically AI employees that can collaborate)

• File explorer + VS Code-like editor with diffs

• In-app browser for automation and research

• Voice mode with local STT + TTS

• Privacy-first: runs locally by default, cloud models supported additionally.

The idea is simple:

Ollama/LMStudio is the brain - Konxios is the system around it that makes it useful.

Everything runs locally first. No forced cloud. No subscriptions. You can optionally plug in OpenAI/Anthropic if you want, but it works fully offline.

I built it because I wanted an AI that doesn’t just answer questions, but actually helps me do things - write code, manage tasks, automate workflows, and stay organized.

It’s still early, but I’d love feedback from other builders here.

If you’re into local AI, agents, or building tools around LLMs, would love to hear what you think.