Today is a day I’ll never forget. I grew up in Cupertino. My dad was a tech founder in the 80s/90s. I was in YC S07. LiveKit is my 5th company. The first 4 didn’t work out. I’ve had a lot of advantages — it still took 20 years to get here. Founders: keep taking shots.

"If you had a great tutor, you wouldn't sit down and say please write my paper for me." - @stevenbjohnson The first generation raised on ChatGPT booed AI at graduation. Three founders unpack why, plus Apple's brand new Siri, NotebookLM's biggest update, and whether anyone "wins" the agent race. This week @Jason covered these topics and more with: • Jeffrey Quesnelle (@theemozilla) building Hermes Agent at Nous Research @NousResearch • Steven Johnson (@stevenbjohnson) Editorial Director of NotebookLM @NotebookLM and @GoogleLabs • Russ d'Sa (@dsa) building the voice infra behind ChatGPT, Tesla & Grok at LiveKit @livekit 7 moments worth your time: 1:40 Hermes Agent and the open source race 7:32 Why AI got booed at graduation 10:48 LiveKit powering ChatGPT, Tesla, Grok 27:50 The massive Siri update 52:49 "Functional AGI, unevenly distributed" 57:24 Brittle to brilliant: agents that now just work 1:02:00 Tokenmaxxing and the $1M a year engineer

Operating a robot over the internet means camera frames and joint state arrive at different times, so your observations drift and training data gets misaligned. LiveKit Portal fuses them back together with the same code, whether the robot's in the next room or another continent.

Introducing the LiveKit C SDK. Realtime audio, video, and data tracks for C apps, with the same low-latency transport our other clients use. Built for the C stacks behind robotics, autonomous vehicles, and high-performance media pipelines. livekit.com/blog/livekit-cpp…

we won the embodied ai hackathon at @southpkcommons last week this is how we did it 🧵

Your outbound phone agent has 1-2 seconds to figure out if it's talking to a person, a voicemail, or an IVR. We shipped Answering Machine Detection (AMD) in LiveKit Agents to do that for you so your agent knows when to keep talking, leave a message, use the keypad, or hang up.

💫 @livekit inside

The co-founder of a $1B VoiceAI infra company says you can't test agents the same way you test traditional software. According to @dsa, you have to test these things almost like you test human beings. Like college degrees, resumes, job interviews, reference checks, etc. What you're really trying to do is build statistical confidence that the person you're hiring can do the task with 99% precision/confidence. Have to test agents the same way by running thousands of end-to-end simulations. Permute accent, language, system prompt, instructions, etc, and see how it performs against the success criteria spit out by your observability stack. This way, you're building confidence, deploying it, and observing which bugs/issues require tweaking. Take those back and make changes to the agent code. Test again, run simulations, and make sure there's no regression. Then deploy again, scale, and observe. That's how the loop goes.

Thanks for having me on, @jason!

We shipped structured data collection for voice agents. Use data collection mode in Agent Builder, or Tasks and TaskGroups in our Agents SDKs. Every session ends with a clean JSON payload for your CRM, form, or database. Great for lead qualification, patient intake, and surveys.

We published a guide on how to do parallel processing inside an agent session, with policy violation checks and guardrails as the example. Check out the demo and read the full post for all of the code you need to apply this pattern to your voice agents.

Excited for this!

xAI STT is live. You can now run a complete cascaded voice agent pipeline on xAI (STT Grok TTS) through LiveKit Inference with one API key, giving you more control, full visibility, and easy component swaps.

We did it! We built the fastest interactive avatar model Introducing LemonSlice-2.1 𝘍𝘭𝘢𝘴𝘩 ⚡ Here’s how we did it using @modal and @livekit 👇 (note: it was not easy)

hey kitt

thank you to everyone building on @livekit!

We shipped Agent Console, a realtime debugging surface for voice agents. Talk to your agent and see the entire pipeline live, from audio and latency to tool calls, transcripts, and participant state. Available now in the LiveKit Cloud dashboard.

Today @livekit launched Data Tracks. Physical AI and robotics applications need low-latency, realtime transport for data beyond just audio and video. Data tracks let you transmit binary frames from any source: IMUs, LiDAR, RGBD cameras, control systems with no codec overhead and the same low-latency semantics as media. They support full end-to-end encryption and every frame includes a timestamp, so you can easily align data from different sensors. Excited to see what folks build with this! youtube.com/watch?v=Ju9Jz0oA…

The cloud was not built for AI agents. Recently at @daytonaio Compute Conference, @dsa, co-founder & CEO of @livekit, sat down with @mattturck, VC at @FirstMarkCap to break down why stateful, long-running agent sessions cannot be deployed and scaled the same way as traditional web applications.

Gemini 3.1 Flash Live just dropped and it's available with LiveKit today. This is the first Gemini 3 native audio model on the Live API. Better instruction following, improved tool calling, reduced speaker drift, and support for 70 languages. Audio in, audio out. No text conversion in between.