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.
We learn to speak before we learn to read.
Voice is the most natural interface we have.
We just raised a $100M to make building voice AI as easy as a web app.
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.
https://t.co/T6NuISyRqb
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!
https://t.co/dzZEmP1hOV
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.
Introducing Interact AI: a new interface for the web.
Add it to your website, and it talks to every visitor, answers questions, and shows your product.
Try it now -> https://t.co/qdfaFGI9a9
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.
"Any feature we release, a competitor could release within two weeks."
@MatanSF (@FactoryAI) on why the moat isn't software anymore. @dsa (@livekit) on building the framework for voice, video, and physical AI. @gsivulka (@HebbiaAI) on what it takes to win in vertical AI.
They join @jason on This Week in AI, Episode 11:
00:00 Intro & AGI debate
03:30 Factory: autonomy for software engineering
04:29 LiveKit: open source to ChatGPT voice
10:31 Hebbia: AI for capital markets
13:21 SpaceX-Cursor $60 billion deal breakdown
26:28 Moats in the age of vibe coding
38:10 Deterministic agents vs. open chaos
45:56 DeepSeek V4
01:05:23 OpenAI's spend problem
01:12:08 P-doom scores
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.
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)
We launched livekit-wakeword, an open-source library that lets you train a custom wake word model from scratch with a single command.
It handles synthetic data generation, augmentation, training, and ONNX export all in one shot.
10k stars on livekit/agents
We released version 1.0 a year ago. Today, our customers are building agents for healthcare, finance, insurance, education, robotics, and more.
It’s been amazing to see our community grow over the past year. Thank you to everyone building with us.
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.