Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
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Learn how to build regression test suites for AI agent prompts, implement prompt versioning, generate diff reports, and integrate prompt testing into CI pipelines.
Learn how to horizontally scale AI agent systems to handle thousands of concurrent sessions using stateless design, session affinity, load balancing, and auto-scaling strategies that maintain conversation coherence under heavy load.
Implement comprehensive timeout strategies for AI agent pipelines including cascading timeouts, deadline propagation, and proper cleanup of abandoned requests to prevent resource leaks.
Mayo Clinic's year-long pilot shows AI agents handling patient intake, preliminary diagnosis, and insurance pre-authorization dramatically cut wait times while maintaining diagnostic accuracy.
Build conversational AI agents that detect off-topic messages, deflect gracefully without being rude, and use engagement hooks to guide users back to productive conversations.
Learn how to write effective JSON Schema tool definitions that help LLMs understand parameters, constraints, and expected inputs. Covers parameter types, descriptions, required vs optional fields, nested objects, and enums.
Implement memory decay functions that let AI agents naturally forget stale information while preserving important memories, using importance scoring, refresh-on-access, and automated cleanup.
Learn how Constitutional AI prompting uses explicit principles and critique-revision loops to make LLMs self-correct harmful or low-quality outputs without human feedback.
Voice AI agents from companies like CallSphere, Bland AI, Retell AI and Vapi now handle over 1B calls per month globally, with 85% resolution rates transforming the contact center industry.
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