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The enterprise AI adoption substrate

Choose any coding agent. Any LLM from any provider. Any orchestration layer. Plus an institutional memory that makes the office remember.
See the platform diagram Try the system GitHub repo
The Living AI Office — six layers of an AI office shown in one composition. A glowing brain (LLM) on the far left feeds a kawaii character at a desk (agent harness), which is part of a team of three workers (orchestration), beside a tall library and memory shelf system, with a horizontal app dock at the bottom (connectors) feeding data up into the library.
The Living AI Office — six layers, one story. Brain · harness · team · library · memory · connectors.
A single person at a clean white desk. Around the desk a cluster of small kawaii agents work quietly — each on its own micro-task. The person directs; the agents execute.
One person directing many. The future of work — a team of agents per person.
01

Coding agent / SDK

Claude Code · Pi Coding Agent · Codex · Gemini agent · LangGraph · custom. Any runtime — CLI or embedded — that runs an agent.

02

LLM · any provider

Anthropic · OpenAI · Google · OSS-80B. Any LLM from any provider, on your own account. Best-of-each per role.

03

Orchestration

LIFEOSAI substrate — wakeups, runs, issues, governance, audit. Or build your own on the same patterns. Source available.

04

Library + memory

Three feeders · five perspectives per file · provenance backbone. Stories cluster into a daily final story that wakes every agent with full context.

Architecture at a glance

Browser & channel entry → User Management gateway → Agent API compute → Runtime engines → Data plane. Open the full architecture →

People remain the moat

What an agent can do today is already enough to help in big ways. Read a thousand documents while you read one. Write a careful first draft. Keep a complete record of every decision.

A person paired with a team of agents — each part playing to its strength — moves dramatically faster than a person alone. The agents handle volume. The person makes the decisions.

The advantage doesn’t come from the technology being better than people. It comes from people learning to direct AI well. People remain the moat.

Read the full vision →

Workshop in Tokyo — 25–29 May 2026

Upcoming

A 5-day hands-on workshop with NBS (NYK Business Systems)

9-agent AI Guardrail Lab live on LIFEOSAI. Every engineer leaves with a working agent in their terminal. See the 5-day plan →

Try it now

Desktop

Mac + Windows installers

Run the full multi-agent substrate locally. 9-agent Guardrail Lab pre-loaded. Apple Silicon + Intel + x86_64.

Mobile + Web

TestFlight + hosted access

iPhone preview build. 12-login hosted instance for workshops. No install — works from any browser.

Source

GitHub repository

Read-access to the substrate, agents, and skills. Open the engine — patterns transfer to any office you want to build.

Vision Where this is heading in the next 12–18 months. People remain the moat.
Use cases Already running — ship management · IoT · editorial · AI safety.
Architecture The substrate end-to-end. Source-available.
Workshop 5-day hands-on with NBS in Tokyo · 25–29 May 2026.