Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
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Implement real-time streaming in LangGraph with stream modes for node-level updates, token-by-token LLM output, custom event streams, and practical patterns for responsive agent UIs.
Implement robust safety guardrails for Claude-powered agents including content filtering, input validation, output screening, refusal handling, and multi-layer safety architecture.
Use Claude's Batch API to process thousands of agent tasks at 50% reduced cost. Learn how to create batches, poll for completion, retrieve results, and design batch-friendly agent workflows.
Learn how to model AI agent workflows as finite state machines with explicit states, transitions, and guards — providing predictable behavior, easy debugging, and reliable persistence for long-running tasks.
Learn how to version and migrate AI agent workflows safely. Covers versioning strategies, backward compatibility patterns, migration techniques, and rollback procedures for zero-downtime updates.
Learn how to design and run A/B tests for AI prompts in production. Covers experiment design, deterministic traffic splitting, metric collection, and statistical analysis for prompt optimization.
Learn systematic techniques for diagnosing why an LLM produces incorrect or surprising outputs, including prompt debugging, temperature tuning, few-shot correction, and structured output analysis.
Master LLM cost management — understand API pricing models, input vs output token economics, prompt caching, model routing, and practical strategies to reduce your AI spend by 80% or more.
Learn how to measure AI agent conversation quality using automated scoring rubrics, LLM-as-judge patterns, and human correlation validation to ensure your agent produces coherent and helpful responses.
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