Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
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Create an AI agent that manages last-mile delivery operations including customer notifications, delivery window management, rescheduling requests, and proof of delivery capture with photo and signature.
Learn how to minimize the delay between a user request and the first visible response from your AI agent by optimizing connections, DNS caching, request pipelining, and warm pool strategies.
Master prompt compression, context pruning, conversation summarization, and selective history techniques to cut LLM costs and latency while preserving response quality in your AI agents.
Learn when and how to run multiple LLM completions in parallel, including fan-out patterns, cost-speed tradeoffs, result selection strategies, and timeout handling for production AI agents.
Build intelligent caching layers for your AI agents using exact-match caches, semantic similarity caches, and time-based invalidation strategies to reduce costs and latency without serving stale responses.
Learn how to minimize tool call overhead in AI agents through batch execution, parallel tool calls, result prefetching, connection pooling, and smart retry strategies for external APIs.
Design AI agents that handle long conversations gracefully by using streaming processing, incremental state management, garbage collection strategies, and memory limits to prevent out-of-memory crashes.
Optimize the database layer that powers your AI agent's knowledge retrieval with query profiling, index design, materialized views, and query caching strategies that cut latency from seconds to milliseconds.
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