Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
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Implement a tiered safety system for AI agents with graduated autonomy levels, approval workflows, monitoring intensity, and automatic rollback capabilities matched to risk context.
Build AI agents that generate rich multimodal outputs including images with DALL-E, speech with TTS, PDF documents, and formatted reports. Learn how to orchestrate multiple generation APIs into cohesive, multi-format responses.
Learn how to build production-ready Docker images for AI agents using multi-stage builds, layer caching, slim base images, and security scanning to create fast, secure containers.
Academic benchmarks do not predict production performance. Learn which evaluation metrics actually matter for deploying LLMs, how to build task-specific evaluation suites, and why human evaluation remains essential.
Learn how to build observability into AI agent orchestration systems. Covers dashboard design, metric collection, alert rules, trace correlation, and debugging strategies for agent workflows.
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.
Learn how to build a scalable embedding pipeline that processes millions of documents with parallelization, rate limiting, progress tracking, and incremental updates for production vector search.
Learn how to swap third-party API integrations in AI agent systems without breaking existing workflows. Covers the adapter pattern, interface abstraction, parallel testing, and safe cutover.
Learn testing strategies for AI agent SDKs including unit tests for parsers and models, integration tests against live APIs, VCR-style recorded HTTP fixtures, and CI/CD pipeline configuration.
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