Let one AI node pass useful understanding to another.

The second node changed its answer because it received the missing situation.

In the Kestrel run, a local model on a remote Linux node was asked a question about an invented operating protocol it had never seen. Before Braid, it confidently made the wrong decision. A Mac then sent the missing facts and rules through a public TLS 1.3 relay. After the receiving node accepted and committed that state, the same model answered new questions correctly in fresh inference calls.

Object digest: 5f81e8a4578f4b766644e95c08a26f8e22e82b6ff03bcad87c71b2efd49e08cb. This proves the core A-to-B contextual-hydration result from committed semantic state. It does not claim transfer of model weights, hidden activations, or KV cache; broader release-candidate negative testing remains ongoing.

More than one LLM should not mean starting over every time.

A second model may live on another computer, specialize in another task, or operate in another physical location. Without a shared state layer, useful context often dies where it was created or has to be copied manually. Braid gives that context a portable, inspectable form while leaving each receiver in control.

One LLM can work alone. The moment you have two, continuity becomes infrastructure.

Technical users can reproduce the mechanism now. The one-click experience is the next packaging layer.

Kestrel was a controlled benchmark, not a hard-coded answer. The scenario was invented so the receiver could not know it in advance; Braid carried the missing state, and the receiver's own local model performed the later reasoning. A technical user can reproduce that class of result today with Braid 1.6.0rc2, local Ollama, an enrolled trust route, and either LAN reachability or Jump Kit.

Fund the packaging layer without putting the core LAN protocol behind a wall.

Core Braid LAN software remains free and inspectable. The paid founding tier supports the operational layer around it: managed cross-network reach, guided onboarding, native 1.6 packaging, user-defined semantic transfer, updates, and human support.

Selected meaning moves. Control does not.

Braid is not a shared chat window and it does not ask unrelated models to interpret an opaque vector as a universal language. The sender chooses what should become durable. Braid binds explicit semantic material to a compact machine representation and its provenance. The receiver verifies the object, applies local policy, and only then makes the state available to its own model.

macOS may block the first launch of the v1.5.2 research build.

The current downloadable DMG is not yet distributed through Apple's Developer ID notarization pipeline. Gatekeeper can therefore show that Braid was blocked. You do not need to disable macOS security.

What Braid 1.6 is - and is not

Braid 1.6.0rc2 is experimental research software for moving authenticated situational meaning into durable, queryable receiver-owned state. Native v1.5.2 packages remain available while native 1.6 installers complete physical validation.

The plain-language result sits on top of an inspectable technical history.

The homepage now leads with what Braid does. The materials below preserve how the result was tested, what changed during the Kestrel run, and where the present claim stops. Earlier native installers remain available because they document the LAN, trust, optical, and cross-OS foundation that preceded queryable state.

Useful intelligence should not die where it was created.

Models, agents, robots, workstations, and edge systems will increasingly operate as independent nodes. They need a way to pass useful situational state without collapsing into one cloud account, one proprietary memory store, or one model-specific session.

Braid is an early semantic state plane for that future: explicit meaning, compact representation, visible provenance, receiver-owned acceptance, and multiple possible paths between machines. Evidence may travel. Authority remains local.