Operating Model

Team Topology

Group	Ownership
Executive sponsor	Business priority, funding, and scale decisions
Delivery lead	Roadmap, stakeholder alignment, dependency management
AI platform owner	Shared tooling, access, deployment patterns, observability
Product/workflow owner	Workflow definition, acceptance criteria, user adoption
Engineering pod	Implementation, integrations, test harnesses, runbooks
Risk and governance partner	Data handling, human-review boundaries, audit evidence

Delivery Flow

1. Intake: identify workflow, pain, volume, risk, and current baseline.
2. Triage: score for value, feasibility, data readiness, and safety.
3. Pilot: build the smallest version that can produce measurable workflow output.
4. Evaluate: compare quality, cycle time, rework, user trust, and unsafe-action attempts.
5. Harden: add monitoring, runbooks, access controls, and rollback.
6. Scale: onboard the next team only after the first workflow has operational ownership.

Platform Decision Matrix

Criterion	Why it matters	Decision signal
Data residency	TELUS/client data may have strict handling needs	Region controls and auditability
Tool integration	Agents need safe access to systems of work	Permission model and connector maturity
Evaluation support	Quality must be measurable over time	Trace, eval, and feedback-loop support
Observability	Delivery leaders need operational signal	Logs, metrics, failed-action visibility
Cost control	Scale can become expensive quickly	Token, compute, and workflow-level cost reporting
Human review	Risky actions need approvals	Native approval gates or easy workflow integration