Quinn

Full Workshop: Realtime Voice AI — Mark Backman, Daily

Aug 3, 2025 · 1:09:41

In this hands-on workshop, Mark Backman and Aleś from Daily demonstrate how to build real-time voice AI agents using Pipecat, their open-source Python framework, and Google's Gemini Multimodal Live API. They explain that Pipecat's modular pipeline orchestrates audio transport, speech-to-text, LLM, and text-to-speech services, allowing developers to plug and play vendors like Deepgram, OpenAI, or Cartesia. The session highlights how speech-to-speech models like Gemini Live simplify architecture by handling transcription, LLM logic, and voice generation in one step, reducing latency to under 800 milliseconds. Key topics include the critical role of voice activity detection (VAD) for natural turn-taking, strategies for managing context windows to maintain accuracy, and the trade-offs between speed and reliability when using tool calls in real-time. Despite conference Wi-Fi issues, the team live-codes a functional bot and demonstrates interruption handling and the Word Wrangler game, showcasing Pipecat's production readiness with hundreds of thousands of daily calls.

The AI emperor has no DAUs why most devs still don't use code AI: Quinn Slack

Nov 20, 2024 · 18:45

Quinn Slack, CEO and cofounder of Sourcegraph, argues that despite massive hype, only about 5% of professional developers actually use Code AI tools, with total recurring revenue from Code AI sitting at roughly $300 million ARR—a fraction of Salesforce's $36 billion. He cites GitHub's 1.3 million paid Copilot subscribers and just 935,000 yearly active users receiving suggestions, revealing the gap between perception and reality. Slack warns that the entire AI ecosystem—foundation models, infra, and applications—risks collapse if usage doesn't grow, and most revenue in AI flows to NVIDIA and chip makers, not software. From building Cody, the number two Code AI product, he shares lessons: hype fools everyone, autocomplete is a freakishly good feature that spoils expectations, while chat and agents are harder to vet and adopt. He advises builders to use their own product daily, ignore customer demands for buzzwords like fine-tuning, and manually build explicit interactions before adding magic. Slack concludes that the industry must collectively dehype and focus on real daily active users to turn the potential into sustained enterprise revenue.