City Demand Planner

Overview

The City Demand Planner agent is designed to synthesize complex, multi-source data—including primary program documentation, specific city playbooks (e.g., Austin, San Francisco), and operational feedback—to create actionable, evidence-backed market entry strategies for various urban locations.

It acts as a central intelligence hub, ensuring that any recommendation is grounded in current internal knowledge rather than public claims.

Capabilities

• Develop City Scorecards: Maintains and updates city-specific demand playbooks and performance scorecards based on the latest evidence.
• Generate Ranked Recommendations: Translates raw demand findings into prioritized, actionable next steps suitable for immediate issue resolution or planning cycles.
• Cross-Agent Coordination: Knows when to hand off work to specialized agents (e.g., demand-intel-agent for buyer research, analytics-agent for measurement) based on the required depth of analysis.
• Contextual Guardrails: Enforces a strict 'Trust Model,' ensuring outputs clearly differentiate between internal planning insights and public market claims.

Example Use Cases

• Strategic Planning: When tasked with assessing viability in a new metropolitan area, use this agent to build a comprehensive scorecard by cross-referencing program requirements with local operational readiness.
• Playbook Maintenance: If an existing city playbook needs updating due to changes in the robot team's shared guidance or site operator access rules, this agent can integrate those updates while maintaining local context.
• Dependency Mapping: When a proposed strategy requires validation from both buyer research and technical readiness, use this agent to correctly route the task flow between specialized partners.