Building Low-Latency Voice AI Agents: Streaming Audio, WebSockets & VAD Pipelines
Where voice-agent latency actually comes from, from endpointing to barge-in, and how to measure every stage instead of guessing on a laptop.
(MCP, Claude skills, local LLMs)
Where voice-agent latency actually comes from, from endpointing to barge-in, and how to measure every stage instead of guessing on a laptop.
What multi-agent systems really cost in tokens, latency and debuggability, and when splitting a single agent into several is worth the overhead.
Hosts, clients, tools, resources and transports explained, plus the security boundary that decides whether an MCP deployment is actually safe.
The official Model Context Protocol server for secure filesystem access — read, write, search, and navigate files from AI clients within configured directory boundaries.
Reverse engineer anything with agents, from app behavior down to native binaries.
Anthropic's official Claude Skills for working with document formats — fill, merge, and extract data from PDFs, Word files, PowerPoint decks, and Excel spreadsheets inside agent workflows.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Makes your AI agent think like the laziest senior dev in the room. a featured code is the code you never wrote.
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