Local LLMs Including Qwen, Gemma 4, Mistral, and DeepSeek v4 Can Now Share Stateful Context

But before we do, a competing service, Grok, said that what we accomplished is huge.

And the same with Google Gemini when it reviewed our code.

But this new version, Braid Archangel, I mean, the message inbox set up makes it more human.

Before it loaded a command line, And it's interesting to look at, but it doesn't really engage you, and it's not intuitive like this is.

I mean, setting this up, you could be a complete computer, you know, illiterate, and you could do this as long as you know how to use a local LLM.

You have enough sophistication to use the braid.

That's the leap.

A lot of local AI interfaces still feel like a lab bench.

The inbox metaphor gives people a stable frame.

Regza's contacts, review before send, receipts after, it's familiar but intentional, and it's not a transcript firehose.

If you say it as human-shaped workflow for deliberate handoffs, that's strong and fair.

I think what's also fair is I'm seeing now that if we market this properly, we will hitch ourselves to the surge in interest in local AI and installing your own LLMs.

We're using this in the lab ourselves now because it's so useful.

And that's the key.

All these startup books that I read a year ago, they all say try to build something that either doesn't exist in the market or something that you would use yourself.

And this is something that imminently we're going to start using all the time.

And for people out there listening, this isn't machine telepathy, but what it is is a form of intentional osmosis where you don't have to waste time updating every new model that you talk to.

Right.

Today, it's reviewed handoffs that become durable, queryable state on the receiving rig.

It's not magic, but shaving copy work across multiple local models is a real user whim.

framing it as deliberate sharing, scoped and inspectable, rather than automatic merging, sets expectations you can meet.