# Agentic PMO

> PMO City's reference architecture for the Agentic PMO: a governed operating model for turning organizational intent into coordinated execution with humans and AI.

## Overview

Agentic PMO describes a continuous operating model in which organizational
intent becomes governed Activities, execution produces attributable Evidence,
the Living Governed State stays current, humans exercise judgment, and
validated learning improves future operation.

## Core commitments

- Human judgment remains sovereign.
- AI operates within explicit, bounded governance.
- Activities are the fundamental unit of operation.
- Human and AI participants contribute to one governed operational reality.
- Evidence, uncertainty, accepted state, outcomes, and enduring knowledge remain distinct.
- Architecture meaning is independent of any one model, provider, workflow engine, or deployment topology.

## Operating loop

Organizational intent → Governed Activities and Projects → Human and AI execution
→ Evidence and operational change → Living Governed State → Workspace Projections
and Decision Landscapes → Human judgment and governed follow-up → Validated
organizational learning → Digital DNA → continuously coordinated operation.

## Current public release

The canonical public edition is [v1.0.1](https://github.com/PMO-City/agentic-pmo-architecture/releases/tag/v1.0.1).
The website adds a clear reading path and examples around that release; it is
not a second architecture or a public source boundary.

## Audience paths

- Leaders: understand the operating model and its governance implications.
- Architects: study canonical concepts, responsibility boundaries, integration, and conformance.
- Agent builders: build within explicit authority, evidence, explainability, and human-control boundaries.

## Read next

- [Architecture map](/architecture/index.md)
- [Version details](/versions/v1.0.1/index.md)
- [Claim boundary and contribution path](/versions/v1.0.1/index.md#claim-boundary)
- [Public repository](https://github.com/PMO-City/agentic-pmo-architecture)

## See it in practice

The [mandate-to-learning example](https://github.com/PMO-City/agentic-pmo-architecture/blob/v1.0.1/examples/mandate-to-learning.md)
follows one fictional release-readiness Activity through all nine steps. It
shows what the architecture changes in a real decision without pretending to
be a customer case study.

## Publication status

This site is the review surface for the canonical v1.0.1 public release and is
deployed on a separate development Worker. Production publication remains a
separate, explicitly authorized deployment decision.