Understanding Flows
A flow is a graph-based structure that defines how an agent executes tasks. It consists of:
Nodes – Actions the agent performs (e.g., retrieving data, sending emails).
Branches – Decision points determining the next step based on conditions.
Exit Conditions – Predefined endpoints where the flow stops execution.
By combining these elements, you can create intelligent automation processes that adapt dynamically to input data and real-time conditions.
Designing Effective Flows
1️⃣ Start with a Clear Execution Path
Each flow should begin with a defined entry point, ensuring the agent follows a structured path. The starting node determines how the process unfolds based on query type, triggers, or predefined logic.
📌 Example: A Customer Support Agent begins by classifying the inquiry type before branching into specific resolution paths.
2️⃣ Implement Branching for Decision-Making
Branches allow the agent to follow multiple paths based on specific conditions.
Conditional Paths – Determine the next step based on predefined criteria (e.g., checking if an order exists before processing a return).
Fallback Paths – Ensure alternative actions exist in case a condition is not met (e.g., escalate to a human agent if information is missing).
💡 Example: A Product Return Request can follow different paths based on order verification status.
3️⃣ Set Up Exit Conditions
Flows should have clear exit points to avoid unnecessary looping or stalled execution. Common exit conditions include:
Successful Task Completion – The workflow completes as intended (e.g., an email is sent successfully).
Manual Review Required – The flow pauses when human intervention is needed.
Error Handling – The system detects an issue and stops execution.
Structuring Flows for Scalability
4️⃣ Modularize Flows for Reusability
To improve efficiency, break down complex workflows into reusable sub-flows. Instead of duplicating logic, create independent modules that can be linked across multiple flows.
📌 Example: An "Email Categorization" sub-flow can be used in both an Email Triage Agent and a Customer Support Agent.
5️⃣ Optimize Flow Execution Order
Ensure steps are arranged logically to prevent redundant processing. The sequence of execution should:
Minimize Data Fetching Delays – Retrieve necessary information early in the process.
Prioritize Critical Actions – Execute essential steps first to maintain efficiency.
Reduce Unnecessary Computation – Avoid processing data that might not be needed.
💡 Example: A Lead Qualification Flow should first verify a lead’s engagement before processing contact details.
Enhancing Flow Accuracy
6️⃣ Use AI and Data-Driven Decisioning
Flows can leverage AI-powered tools to make decisions dynamically. Instead of rigid rules, AI can classify data, assess sentiment, or extract key insights.
AI Classifiers – Determine categories based on text analysis.Prioritize Critical Actions – Execute essential steps first to maintain efficiency.
Sentiment Analysis – Assess the tone of a customer query to prioritise urgency.
Data Matching – Compare incoming requests against stored records.
📌 Example: An agent handling support tickets can prioritise negative sentiment emails for faster resolution.
7️⃣ Implement Fail-Safe Mechanisms
To prevent execution failures, include contingency paths that handle:
Missing Data – Prompt users to provide missing inputs before proceeding.Sentiment Analysis – Assess the tone of a customer query to prioritise urgency.
API Failures – Retry failed integrations or switch to alternative methods.
Escalation Triggers – Route issues to human agents when AI confidence is low.
💡 Example: If an order number is missing, prompt the user before continuing the refund process.
Testing & Refining Flows
8️⃣ Continuous Testing & Optimization
Flows should be regularly tested to identify bottlenecks and improve performance.
📌 Best Practices for Testing
Run simulated scenarios with sample inputs.
Monitor real-time execution and task logs.
Identify and eliminate redundant steps.
Iterate Based on Performance Metrics – Use analytics to refine flow logic and enhance accuracy.
User Feedback Integration – Adjust flows based on observed user behavior and feedback.
📌 Example: If users frequently abandon a request mid-process, streamline steps to reduce friction.