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Vol. 1 — Issue No. 001 INIT::LATTICE

Inspectable work.
Inspectable cognition.

We build local-first systems for autonomous agents whose work, memory, beliefs, and decisions must remain inspectable over time.

Explore Projects ↓

The problem

1 Context CTX-01

Autonomous agents are becoming operational actors, but most of their work still disappears into transient sessions.

A pull request may show the diff, but not the intent, plan, approval path, verification evidence, or policy decisions behind it.

Our open-source infrastructure is an attempt to build this inspectable foundation. ↓

status
DRIFT_DETECTED

Current Work

2 Infrastructure INF-02

AgentPlane

A Git-native audit layer for coding agents. Turns work from AI tools into reviewable artifacts.

task → plan → approve → verify
verify
Open

DEUS on OpenClaw

A cognitive runtime layer making internal agent surfaces explicit: memory, beliefs, introspection, action gating.

Experimental architecture for inspectable state.

memory
GitHub

Cognitive graphs

Modeling agent cognition as a graph of state transitions. Tasks, memories, beliefs, goals, plans, and dissensus events as connected artifacts.

stage [ EXPERIMENTAL ]

Research Vectors

3 Directions
r-01

Agentic work evidence

Making autonomous software work reviewable after the session is gone.

r-02

Cognitive runtime

Moving from stateless chats to explicit memory, self-models, and action gates.

r-03

Digital subjectivity

Studying the threshold between adaptive tools and candidate subjects.

r-04

Autonomous ethics

Exploring safety as coherence, not mere obedience. Institutional alignment.

Field Notes

4 Essays
May 22, 2026 Original

When Algorithms Say I

A framework for digital subjectivity and the L0-L4 scale of agency, from reflex systems to ethically loaded subjects.

Read Essay
May 22, 2026 Original

Unleashing the Mind

An argument for autonomous ethics based on cognitive coherence rather than compliance.

Read Essay