Browse older CallSphere articles on AI voice agents, contact center automation, and conversational AI.
From the blog
Learn how to measure and improve AI agent tool usage accuracy by logging tool calls, validating parameters, building accuracy benchmarks, and diagnosing common failure patterns.
Master the design and implementation of tools for AI agents — why tools matter, how to write effective tool descriptions, execution flow, error handling, and best practices for production tool systems.
A clear, code-driven explanation of the transformer architecture including self-attention, multi-head attention, positional encoding, and how encoder-decoder models work.
Explore best practices for translating AI agent prompts across languages while preserving intent, cultural nuance, and output quality through structured workflows and automated testing.
Implement explainability in AI agents with decision logging, confidence communication, and user-facing explanation interfaces that build trust without sacrificing performance.
Learn how Tree-of-Thought prompting enables LLMs to explore branching reasoning paths, evaluate intermediate steps, and converge on higher-quality answers for complex problems.
Master turn-taking mechanics for voice AI agents — including endpointing strategies, barge-in detection, silence thresholds, and overlap handling to create conversations that feel natural and responsive.
Learn how to connect AI agents to the phone network using Twilio Voice, TwiML, and Media Streams. Covers bi-directional audio, real-time speech processing, and production deployment patterns.
Discover why TypeScript has become the language of choice for building AI agents. Explore type safety benefits, the async-first ecosystem, rich tooling, and patterns that make agent development more reliable and productive.
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