Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
From the blog
Build an analytics system for agent marketplace publishers that tracks usage patterns, revenue metrics, user satisfaction, and optimization opportunities. Learn metrics collection, dashboard design, and actionable insights generation.
A comprehensive comparison of four fundamental agent architectures — single agent, pipeline, router, and swarm — with diagrams, code examples, and guidance on when to use each pattern.
Create configuration snapshots for reproducible AI agent testing. Learn snapshot creation, test isolation, seeded randomness, and techniques for achieving deterministic test results.
Design and implement a no-code agent builder that lets non-technical users create, configure, and test AI agents through visual flows, prompt editors, tool configuration panels, and a live testing sandbox.
Implement plan-based feature gating for AI agent tools and capabilities. Learn to build dynamic tool lists, enforce tier restrictions, and surface upgrade prompts when users hit limits.
Master capacity planning for AI agent systems by learning demand forecasting, resource modeling, headroom calculation, and scaling trigger design to keep your agents performant under growing workloads.
Design a certification program that ensures third-party AI agents meet quality, safety, and reliability standards before appearing in your marketplace. Covers certification criteria, automated testing, badge systems, and ongoing compliance monitoring.
Explore the four major patterns for inter-agent communication — handoff-based messaging, event-driven systems, shared memory via RunContext, and the blackboard pattern — with implementation examples using the OpenAI Agents SDK.
Build conversation analytics for AI agents that measure success rates, identify drop-off points, track user satisfaction, and surface patterns that drive product and prompt improvements.
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