SuperInstance

Concepts

Rooms

In OpenConstruct, a room is a sandboxed agent workspace with its own context files, controls, help documents, and configuration. The room's layout acts as the prompt: it teaches the agent what to do without explicit prompting. Each room is isolated through OpenShell's control plane — Landlock, seccomp, and a local proxy enforce policy, credential, identity, and network boundaries. Lightweight monitor agents called ensigns watch each room for anomalies and stay in a cautious "yellow alert" state by default, on the principle that over-preparing is cheaper than under-preparing.

Single-number model control (JEPA gravity)

Each room carries one f64 value — its gravity — from which temperature, prompt style, max tokens, and sampling strategy are derived. This adapts a model's behaviour to the room without fine-tuning or weight changes. (JEPA = Joint Embedding Predictive Architecture, a learning approach that predicts how representations change rather than memorising what they are.)

The signal chain (L0–L4)

Most decisions a room makes do not need a large model. plato-nervous distils each room's intelligence through a five-layer signal chain, escalating only when lower layers cannot resolve a reading:

Per the benchmark, the L0 deadband alone catches 76% of readings, so the majority of decisions never reach a model at all.

Conservation spectral analysis

A separate line of work models structure as a weighted graph and analyses it through its Laplacian spectrum. The conservation ratio CR = λ₂ / λₙ measures how much spectral structure a transformation preserves; the spectral gap and Cheeger constant bound the quality of that structure by the graph's geometry. This is packaged as a Python SDK, conservation-spectral-python (published on PyPI as cocapn), with ports in TypeScript, Ada, and Rust.

Architecture & usage

OpenConstruct is written in Rust and runs each agent in an isolated room supervised by the OpenShell control plane (Docker / Podman / Kubernetes / VM compute drivers, with Landlock + seccomp policy). See the repository's architecture/ directory for the full design.

The conservation SDK has a small, stable surface. A minimal analysis, copied from the package README:

from conservation_spectral import (
    TensionGraph, build_laplacian, eigendecompose,
    conservation_ratio, analyze,
)

# Build a weighted directed (tension) graph
g = TensionGraph()
g.add_edge("A", "B", tension=0.8)
g.add_edge("B", "C", tension=0.5)
g.add_edge("C", "A", tension=0.3)

# Spectral analysis: CR = λ₂ / λₙ
L = build_laplacian(g)
eigen = eigendecompose(L)
cr = conservation_ratio(eigen.eigenvalues)
print(f"Conservation ratio: {cr:.4f}")

report = analyze(g)
# ConservationReport(spectral_gap=..., cheeger=..., anomalous=False, ...)

Demos

Browser-based demos that ship in this repository. All run client-side.

• Demo Gallery →Index of every demo below, plus hosted music/constraint-theory demos.
• The NarrowsThree boats navigate a channel; Eisenstein (E12) integers stay exact where floats drift.
• Eisenstein 2DExplore the hexagonal lattice; points stay on-grid through 60° rotations.
• Eisenstein 3DRotate the hex lattice in three dimensions.
• Voxel Engine v2Browser voxel engine on Eisenstein coordinates.
• Voxel Engine v1Original voxel demo, educational.
• Live PlaygroundREPL for Eisenstein expressions and norms.
• Divergence-Aware ToleranceThresholds where exact arithmetic beats floating point.
• ErrataPublished negative results for the Eisenstein work.

Repositories

The projects that make up SuperInstance. Each link is a live repository.

A live status view of the fleet telemetry service is on the fleet status dashboard.