1. I spent a lot of time at scale labeling data myself, never thought it was beneath me. Instead it's how we developed quality criteria, instructions, how we provide partnerships to our customers. My co-founder @flubtitle and I built out new labeling products for LLMs in 2023 (well it's old now) because we did labeling, ran queues (meaning we were running real projects and needed to deliver data). Not because we got a prd from anyone. 2. One of the first things we built at Santori Labs is our voice-first eval/label flow and a roleplay system. I spent hours every week going through data, thinking about what is good vs not. 3. Imagine an engineer who thinks they are too good to do that, but instead they are just here to execute a prd that is given to them. 4. I don't think data is all you should do, but it's still one of the most important things you can do. Labeling is one form, another one is looking at agent traces. If you don't see why that's important, you are stuck in the past. 5. It's painful looking at data. You think you just look at it and you just know if this is good. It's never that. It's always the messy middle of "meh". That's why the design principle for our own data flow is that: data is a focused act, and the product needs to encourage focus

A behind-the-scenes working session with Tarun Sachdeva (@tarunsachdeva) for an upcoming film collaboration. Tarun is the founder of Traces (@tracesdotcom), a platform for sharing the work you do with coding agents. In this conversation with @internetvin, he walks through what a trace actually is, opening with a single session and pulling on it until the whole product unfolds: profiles, teams, the CLI, integrations, and the discover feed. Timestamps 00:00:00 What is a Trace? 00:06:55 Categorization, Status & How the Summary is Built 00:08:30 The Trace as Atomic Unit 00:10:30 What Happens Between Linear and a Code Base 00:12:55 The Middle Made Visible 00:14:00 Andrew Nesbitt & Everyone is a Beginner 00:18:00 Project Baton: The CLI 00:22:40 Publish, Resume & Git for Agents 00:25:00 Single-Player vs Multiplayer 00:30:00 Integrations: GitHub, Hugging Face & Linear 00:33:50 Why Tarun Stopped Using an Issue Tracker 00:35:00 The Discover Tab 00:37:00 JC, Jake & Reading Other People's Traces

The traces git combination works really well now imagine every commit catching the conversations that generated it, stored as a light reference in a git note and auto-shared and updated as your team rolls once setup you'll see the reference on every session on traces....

Announcing Traces for Teams A new way to share coding agent sessions in your team, with a free plan for startups and open source projects and custom plans for larger teams. We've been using this for a few weeks now and it's really improved how we work together.

Agent traces will become the go-to standard artifact for software development

Thanks @joshdzieza and the team at @verge for chatting on the state of data spend in AI!

gpt-oss ultravox, should be an incredible combo for oss voice ai!

We're hosting two Model Context Protocol themed lightning talk nights in March, save the date! March 18 in SF with @CloudflareDev March 27 in NYC with @SignalFire

New month, new @SignalFire AI Lab event! Please join us as we welcome the CEO of @Horizon3ai Snehal Antani, CEO of @robusthq Yaron Singer, and Head of AI of @PaloAltoNtwks Nandan Thor. lu.ma/AISafety