Personas¶
Purpose¶
This document defines the primary user personas for the future DecisionGraph platform.
These personas should shape API design, operator tooling, approval workflows, and product prioritization.
Persona 1 - Platform and Agent Engineer¶
Who They Are¶
An engineer building AI agents, automated workflows, or decisioning services that need structured event capture and trustworthy operational behavior.
Core Goals¶
- instrument automated decisions without excessive friction
- query and replay decisions later
- integrate with a stable API and SDK surface
- keep production behavior observable and debuggable
Pain Points¶
- ad hoc logging is not enough for real decision auditing
- once decisions are live, debugging becomes slow and fragmented
- approval and exception handling often become custom side systems
What They Need From DecisionGraph¶
- clean ingestion APIs
- stable event contracts
- deterministic replay guarantees
- health and projection visibility
- Python support during the transition
Persona 2 - Decision Operations Lead¶
Who They Are¶
A product, operations, or platform owner responsible for keeping automated decision systems safe and effective in production.
Core Goals¶
- know whether decision systems are healthy right now
- investigate incidents quickly
- monitor queues, lag, and workflow bottlenecks
- coordinate human review where needed
Pain Points¶
- there is no single place to see system health and trace detail together
- handoffs between engineering, operations, and reviewers are messy
- operational visibility is often weaker than business expectations
What They Need From DecisionGraph¶
- live health dashboards
- trace explorer and replay tools
- exception and approval views
- action-oriented alerts and workflow state visibility
Persona 3 - Compliance and Risk Investigator¶
Who They Are¶
A reviewer responsible for auditability, policy compliance, incident reconstruction, or post hoc evidence gathering.
Core Goals¶
- understand exactly what happened
- prove who approved or overrode a decision
- compare similar historical decisions
- export evidence for audits, incidents, or internal review
Pain Points¶
- conventional logs are noisy and incomplete
- incident reconstruction takes too long
- policy rationale and precedent history are hard to retrieve
What They Need From DecisionGraph¶
- immutable trace history
- replay and digest verification
- precedent and graph exploration
- clear evidence exports
Persona 4 - Human Reviewer and Approver¶
Who They Are¶
A finance, risk, legal, trust, or operations reviewer who approves exceptions or intervenes in high-stakes automated decisions.
Core Goals¶
- review only the context that matters
- approve or reject quickly but responsibly
- understand the policy basis and relevant precedents
- keep a clear audit trail of human intervention
Pain Points¶
- most approval tools do not show enough context
- reviewers are forced to piece together information from multiple systems
- the audit trail for overrides is often weak
What They Need From DecisionGraph¶
- focused approval inbox and review screens
- supporting trace and precedent context
- explicit decision capture and reasoning fields
- escalation and SLA support over time
Secondary Persona - Reliability and Platform Operator¶
Who They Are¶
An engineer responsible for uptime, recovery, replay safety, and operational resilience.
What They Need¶
- projection lag visibility
- replay controls
- failure telemetry
- runtime and tenant status views
Priority Order¶
Primary priority order for v1:
- platform and agent engineer
- decision operations lead
- compliance and risk investigator
- human reviewer and approver
This ordering keeps the product grounded in real integration and runtime value while still building toward high-trust operational workflows.