Test User-Agent Collaboration

Worker Agents are designed for autonomous operation, but their true power emerges when they can intelligently engage human expertise for complex scenarios. Let's start by watching a real collaboration session where a user investigates and resolves payment reconciliation discrepancies with a Worker Agent:

Effective user-agent collaboration depends on three key elements:

Comprehensive Document Lifecycle Context - End-to-end processing insights, including extraction, validation, decision points, and metrics, to ensure transparent collaboration triggers.
Sophisticated Engagement Patterns - Clear identification of when and why human expertise is needed, with detailed analysis of discrepancies and business implications for rapid decision-making.
Dynamic, Multi-Dimensional Analysis - Rich capabilities for investigating issues at any level, from high-level summaries to transaction details, with clear audit trails for accountability.

Try It Yourself: Investigate Payment Discrepancies

Watch how an experienced user investigates discrepancies, then try it yourself using the Payment Remittance Agent in Studio's Work Room with the VerticalAG work item.

Notice how the agent provides rich context with each response - identifying patterns, suggesting implications, and offering relevant next steps. This demonstrates key collaboration patterns: starting with broad analysis, drilling into specifics, and taking concrete actions based on findings.

Understanding Collaboration Patterns

Context Preparation

The agent maintains comprehensive context across all processing phases:

Document extraction metrics that capture field accuracy, table structure validation, and data quality indicators, providing clear evidence of potential extraction issues or anomalies.
Detailed transformation logs that track all data standardization, enrichment, and computation steps, enabling precise identification of where discrepancies may have originated.
Complete validation history including rule evaluations, threshold checks, and pattern analysis results that clearly show which business rules were violated and why.

Engagement Triggers

The agent initiates collaboration based on sophisticated analysis:

Multi-level threshold analysis that considers both individual transaction limits and aggregate impact across facilities or service types, ensuring appropriate escalation of significant issues.
Pattern detection algorithms that identify unusual trends or anomalies across historical data, helping distinguish routine discrepancies from potentially systematic issues.
Complex business rule evaluations that consider multiple factors including facility type, service category, and historical patterns to determine when human expertise is truly needed.

Interaction Flow

The agent supports dynamic investigation through:

Contextual question handling that understands the user's investigation path and automatically provides relevant supporting data and insights for each query.
Flexible analysis capabilities that allow users to explore data through multiple dimensions, from high-level facility summaries to detailed transaction records.
Progressive disclosure of information that starts with key findings and allows users to drill deeper into specific areas of interest while maintaining overall context.

Resolution Tracking

The agent maintains detailed resolution records including:

Complete decision logs that capture not just what actions were taken but why they were necessary and how they align with business rules and historical patterns.
Impact analysis of all resolution actions, including both immediate effects and potential downstream implications for related processes or reconciliations.
Comprehensive audit trails that document the entire collaboration process from initial trigger through final resolution, supporting future analysis and process improvement.

Designing for Collaboration

Best Practices for Agent Design

Effective collaboration requires agents to build rich context during autonomous processing, enabling them to provide immediate, comprehensive support when human expertise is needed. This investment in context management is crucial for efficient problem resolution.

1. Context Design

Implement comprehensive event tracking that captures the complete processing lifecycle, from initial document ingestion through final reconciliation, including detailed metrics about extraction accuracy, transformation decisions, and validation outcomes.
Design hierarchical context management that organizes information at multiple levels (document, facility, invoice) while maintaining clear relationships between these levels, enabling efficient navigation of complex data structures.
Create intelligent context summarization that automatically highlights key patterns, anomalies, and potential issues while maintaining access to supporting details for deep investigation.

2. Interaction Design

Build sophisticated natural language understanding that can interpret user intent across a range of investigation patterns, from specific queries about individual invoices to broad pattern analysis across facilities.
Implement context-aware response generation that considers both the current question and the overall investigation path, providing relevant insights and suggesting productive next steps.
Design progressive disclosure patterns that present information in digestible chunks while maintaining clear paths to deeper analysis when needed.

3. Resolution Design

Create structured resolution workflows that guide users through complex decisions while maintaining flexibility for unique scenarios, ensuring thorough problem resolution while supporting efficient processing.
Implement comprehensive resolution documentation that captures the complete context, analysis, and reasoning behind each decision, supporting future audits and process improvements.
Design impact analysis capabilities that help users understand both immediate effects and potential downstream implications of their resolution decisions.

Next Steps

Having explored how to design and test worker agents for effective collaboration:

Review the Agent Architecture for implementing these patterns

Test Worker Agent Business Processing Train Document Intelligence