Intent
What outcome is the system actually meant to produce?
A public architecture institution
Intentarium turns ambiguous situations into explicit systems of authority, trust, evidence, and execution—for humans and intelligent agents.
The thesis
Greater agency does not require less structure. It requires better structure.
The core method
Before automating a system, make its operating logic visible. The same eight questions reveal hidden assumptions in technical platforms, organizations, creative work, and personal systems.
What outcome is the system actually meant to produce?
Which people, teams, services, and agents participate?
Who may decide, approve, execute, override, or stop?
What must never occur, regardless of efficiency?
What current evidence permits an actor to proceed?
How will the system prove what happened and why?
What happens when authority or confidence is insufficient?
How does the system detect failure and adapt?
The Pattern Commons
Twelve initial hypotheses about autonomy without chaos. Their maturity is visible by design: no claim becomes established merely because it sounds convincing.
Convert repeated individual rescue work into observable ownership, safe defaults, runbooks, automation, and learning loops.
Establish one authoritative representation of intent before automating projections, decisions, or execution from it.
Design who may enter, what they perceive, and what effects they may cause as separate policy surfaces joined by explicit contracts.
Assign decision rights, access, and escalation paths wherever a person or team is held responsible for an outcome.
Preserve consequential decisions with context, authority, evidence, alternatives, and revision history instead of leaving them in conversation.
Carry the approved outcome, constraints, authority, and rollback semantics into every executable representation and resulting action.
One canon, many interfaces
Every public object begins in version control and generates both human and machine representations. The site can disappear and the knowledge remains portable, inspectable, and attributable.
For people
Browse patterns, see their maturity and relationships, understand the Agency Map, and track what changes.
For machines
Retrieve JSON objects, a pattern graph, the Agency Map schema, identity metadata, source commits, and the public corpus without invoking a model.