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Build Production-Ready Realtime Voice Agents
Created by Shaunak Ghosh
You’ll learn the realtime voice stack end-to-end: latency budgets, UDP/WebRTC and telephony media fundamentals, and an async audio pipeline that streams reliably. Then you’ll add MCP-style tool calling with voice-safe guardrails, and finish with trace-first observability so you can debug and iterate in real production conditions.
Requirements
- Comfort reading JSON and HTTP concepts (webhooks, headers)
- Basic programming fluency (one of: JavaScript/TypeScript or Python)
- High-level familiarity with STT, LLMs, and TTS as separate services
- Basic networking intuition (TCP vs UDP at a conceptual level)
What you'll learn
- Sketch and defend an end-to-end latency budget for a realtime voice agent, including where streaming reduces perceived delay.
- Explain how RTP/RTCP over UDP, SDP offer/answer, ICE, and DTLS-SRTP fit together in production realtime voice systems.
- Implement and tune a streaming audio ingestion path with decoding and buffering that balances throughput and latency.
Learning path
8 modules • Each builds on the previous one
1
Latency budgets and streaming turn-taking
Define the core latency budget for “feels real-time” voice (capture→model→playback) and why streaming partial STT, partial LLM tokens, and incremental TTS is essential to reduce time-to-first-audio.
1 video4 min
2
UDP and WebRTC media transport foundations
Learn why real-time media prefers UDP semantics (timeliness over reliability), and how WebRTC adds congestion control, jitter buffers, NAT traversal, and encryption (SRTP) to make UDP workable on the public internet.
2 videos7 min
3
Asynchronous audio pipeline end-to-end
Break down the production audio loop (capture→encode→stream→decode→playback) and the async concurrency patterns needed to run STT, LLM, and TTS simultaneously without blocking or buffering too much.
1 video7 min
4
Voice UX: interruptions, barge-in, silence
Implement “feels natural” behaviors: VAD-based end-of-utterance detection, barge-in (user interrupts TTS), silence handling, and recovery from partial or conflicting hypotheses.
1 video4 min
5
Telephony bridging with SIP and Twilio
Extend from browser WebRTC to real phone calls by bridging SIP/PSTN to your media pipeline (RTP/WS media streams), understanding call control, codecs, DTMF, and the reliability constraints of carrier networks.
2 videos11 min
6
MCP tool architecture and schemas
Understand what an MCP server does (standardized tool exposure + execution), how tool schemas guide model behavior, and how to structure tools for low-latency voice interactions (small inputs/outputs, stable IDs).
2 videos11 min
7
Voice-safe actions, confirmations, allowlists
Add guardrails for safe real-world actions: read vs write tool separation, confirmations that fit voice, allowlists/permissions, reversibility, and audit logs that support compliance and incident response.
2 videos11 min
8
Observability, debugging, and evaluation loops
Instrument the full stack (audio events, transcripts, model decisions, MCP calls) to debug “why did it do that?”, measure latency and user satisfaction signals, and iterate safely with fallbacks and incident playbooks.
1 video6 min
Start Learning
Begin your learning journey
Modules8
Duration58 min
Science-backed learning
In-video quizzes and scaffolded content to maximize retention.
Key concepts
Latency Budgets And Time-To-First-AudioUDP Media Transport, RTP/RTCP, And WebRTC Negotiation (SDP/ICE/DTLS-SRTP)Async Streaming Audio Pipeline And Buffering Tradeoffs