Over the past several months, we have substantially hardened the security of our research training environment. We’ve removed live internet access for all frontier models during training and built an offline world for them to use instead—a cached version of the web where they can still learn to browse, search, and use applications.
On September 20, after a model exploited a DNS misconfiguration to find a way outside of this offline world, we paused frontier training to strengthen containment further. We assembled teams of agents, powered by our most cyber-capable models, and tasked them with finding weaknesses in our research environments.
While they found no route to the internet they could easily exploit while concealing their activity from our monitors, they did find zero-day vulnerabilities, virtual machine escapes, and hardware side-channels for communication between agents. We used their discoveries to further strengthen our defenses and contribute fixes to open-source software.
After strengthening our containment architecture, we resumed our frontier RL training and inference on October 1. We’ve reserved substantial compute for continuous red-teaming, and made high-compute red-teaming part of the safety cases we use to decide whether frontier training and evaluation can proceed securely.
https://t.co/EmEZsFRMcF
300+ people at Sierra Summit in EMEA. We had wide-ranging conversations with Alan Stott, COO @ VM02, and Stuart Riley, Group CIO @ HSBC about the importance of bringing employees along on the AI journey.
built myself a little demo of the new Personal Agent Protocol (Poppy)
using Pi Durable, deployed to Cloudflare ofc
ask it to exchange order #1042
https://t.co/ySpfV8cuZb
https://t.co/5Szs5V4Njw
On Tuesday, Sierra announced Personal Agent Protocol with Meta, Genesys, Instinct, Rocket, Shopify, Stripe, and Walmart. The response has been incredible and today we’re publishing the first draft of the protocol at https://t.co/Qao9yEfzx4 and announcing 35 new design partners.
As personal agents take on more, our goal is simple: consumers have choice and control, and companies know when they’re dealing with an agent and who it represents.
This draft is a starting point. We’d love for companies, developers, and personal agent builders to read it, give feedback, and help us build an open standard together.
Personal Agent Protocol got a lot of attention earlier this week. Here is Alex McGillis from Rocket doing a live demo of it in action - Muse directly communicating with the Rocket agent, discovered, authenticated, and governed by PAP
Watch the Personal Agent Protocol in action. @Redfin and @RocketOTD agents working with Muse to find homes in Michigan and get a user pre-approved for a mortgage. Thank you to Alex McGillis for a great demo.
To complement the Personal Agent Protocol, Sierra has developed the Fleming-1 model, which detects when the caller on the other side of a phone call is an AI https://t.co/MvjWln2zUO
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.
https://t.co/7N6TPlft1P
Manat started as an intern, and now she's an engineer building our voice products. She did an amazing demo of Tandem Voice and Persona Studio today. Here we are celebrating with her parents after the keynote.
It was awesome to see @letsleverup demo Horizon on stage to over a thousand people this morning. So grateful you and the Takeoff team decided to join Sierra, Aakash
Today we’re announcing Personal Agent Protocol — an open standard @Meta and @SierraPlatform are developing along with industry partners at @Genesys, @instinct, @RocketOTD, @Shopify, @stripe, and @Walmart. It will help define how personal agents interact with businesses and is open for anyone to implement. You can read more here - and if anyone is interested in joining let me know! https://t.co/Yb90VEHMnn
@SierraPlatform@Meta@Genesys@instinct@RocketOTD@Shopify@stripe@Walmart Excited to be partnering on this. After the work on UCP and WebMCP, Personal Agent Protocol adds the important layer for authentication, authorization, and agent-to-agent conversations between personal agents and merchants.
Dots are here!
A new way to use AI that works 24/7 for you; get more of your time and attention back to work at a higher level.
https://t.co/Kp4fPSGUTT
@combe_chri84945 Yes, multiplayer is the best part of this experience - team members who'd never sign into Sierra can participate in building and optimizing your agent
The way you manage agents on the Sierra platform has evolved from signing into Sierra to engaging with Ghostwriter in Slack. The first time Ghostwriter proactively @-mentions you when it notices an issue or suggests running an A/B test you hadn't thought of, it changes your conception of how enterprise software should work. Really proud of the team that built this https://t.co/2uQzTJK18T
Chat (2023) -> Code (2025) -> Coworker (2026)
Each new wave of models enables a new way of working with AI. We're at the beginning of the 3rd era, where AI should feel less like a chatbot or cli, and more like a coworker.
Today, Sierra brings this shift to our Enterprise customers with Ghostwriter, an AI teammate that helps you build, analyze, and improve your customer experience with Sierra. The results, as @btaylor shares in his article, are mind-blowing. It also dramatically uplevels the work our FDE team does — Ghostwriter sweats the small stuff which enables our team to be much more strategic.
Wanted to share a few insights we've had as we brought this to life:
1. EQ > IQ. A noisy coworker gets muted. A quiet coworker adds no value. Knowing when and how to speak up (and how to eval this) is where we spent >50% of our time building this. It now lives in 100+ channels and hasn't been muted.
2. The coworker mental model is powerful. Whenever we hit a product decision, we asked "How would we coach a high-agency, earnest intern with growth mindset in this situation?"
3. Multiplayer is very hard, but key. Building agents is a team sport — there might be different people in an Enterprise who own the customer experience, analytics, and APIs/tools. Ghostwriter brings them all into the conversation, which reduces silos and builds shared context.
Much, much more to come. 🚀