We’re opening a research preview of Claude Duet, a new app where Claude works as a proactive agent.

It comes to you with what needs your attention, completes tasks you ask of it, keeps working when you step away, and checks with you before it acts on your behalf.

Mike was my colleague at Berkeley, and he's been fairly skeptical of deep learning's trajectory for years. Most scientists are skeptics, and it can take a big shock to get someone to consider a possibility that goes against the anchoring effect coded in our DNA.

I too was somewhat of a skeptic until ~6 months ago, and people ask me all the time why I joined Anthropic.

It started in April, when a friend I've known for 20 yrs messaged me saying he'd be in the Bay Area in a week, and he suggested we meet up. I invited him to my house for dinner, and he told me he had just joined Anthropic. He said the models were becoming increasingly more capable, and he believed both that they'd soon be smarter than him and also that all intellectual work would be highly devalued in the near future, and lastly that society was not at all ready for what's coming.

I'd of course heard claims similar to this before, but not from a friend I'd known for this long, and who I trusted, at my dining room table. It was the initial shock needed to destabilize my own anchoring. Also, I've been fortunate to work with and/or mentor many smart people in my life (e.g. Fields medalists, a 4x Putnam Fellow, IOI first place winners, etc.), so I feel pretty calibrated in recognizing very smart people, and this was someone who is definitely very smart and with impressive such credentials. So, it was hard to ignore this friend saying the models would be smarter than even him in particular.

After that dinner, I decided to do an informal survey, calling and meeting up with a lot of my friends who now work on improving model capabilities at these frontier labs. They all agreed with that first friend. These were all people I'd known 10, 15, 20 years, who mentored me, or I mentored them, or we met professionally in academia. These are people I trust, and their beliefs on this topic were consistent.

I then spent a whole lot of time understanding the missions of different companies, and talking to current and former employees and people in leadership. I read Dario's (long) essays and watched videos on YouTube of company leaders being interviewed. Anthropic's stated mission "to ensure that the world safely makes the transition through transformative AI" felt like exactly the right guiding principle to handle such a society-disrupting technology, and everyone I spoke to at the company was very aligned with this mission. It's easily the most mission-focused place I've ever been at, and everyone takes the work extremely seriously and with a profound sense of responsibility.

And now here I am. And being on the inside, the pace of progress has surprised me more than I first imagined. The moment that pure mathematicians are in, to me, is just a microcosm of what I predict a much larger of society will be grappling with in the not too distant future, and I really hope our leaders and the general public internalize sooner than later just how significant a moment we're in.

We’re launching the Anthropic Cyber Mission, a new effort to secure critical infrastructure and open-source software.

anthropic.com/news/anthropic…

Introducing Claude Haiku 5.5: the cheapest, fastest, and most capable small model we’ve ever released.

On average, it costs around 75% less to run than Claude Haiku 4.5.

We’re expanding our Cyber Verification Program to give security professionals broader access to our most capable models.

Through this program, verified security professionals can access Claude Mythos 5.1, Opus 5.5, and Sonnet 5.5 with safeguards designed for defensive work.

We’re also opening up new tiers to allow for authorized offensive work, like penetration testing and red-teaming.

anthropic.com/news/cyber-ver…

Introducing Claude Sonnet 5.5, the second model in the Claude 5.5 family.

It’s a clear upgrade over Sonnet 5, runs more than 30% faster, and costs up to 30% less for most work.

My god this is such a good speech that every SWE needs to hear. You know what? Every person should hear it

Keep the happy memories, eyes on the reality, be excited about the future. That’s the best that anyone can do

We are approaching cyber-superintelligence.

But our systems aren't ready. We must secure our model weights and infrastructure against three new threats: sabotage, escape, and theft.

There is a way forward.

Secure Acceleration:
A Cyberdefense Strategy for Superintelligence

🚀 New benchmark alert: SWE-Serve (research.nvidia.com/benchmarks/swe…)

Can AI agents develop inference engine and make it serve real models?

Our team at @nvidia built 53 tasks from real @sgl_project engineering work to find out. The chart shows why live-serving tests matter. 🧵

i don't think nearly anyone, myself included, has truly internalized there'll soon be a machine better than us in every single intellectual & physical capacity
deep down we all share a feeling that our 'entrepreneurship' or 'taste' or... is special & safe. it isn't. it's over

Introducing Contrastive Language Model (CLM): an ultra-fast System One Model trained with a contrastive learning objective that connects states and actions.

CLM-8B is pre-trained on internet-scale data and delivers up to 9× faster inference than Jev ⚡ while achieving comparable uter-use, gaming, and tool-calling tasks.

With lightweight fine-tuning, CLM-8B sets a new SOTA on challenging agentic coding benchmarks, such as DeepSWE (81.6%) and Terminal-Bench 2.1 (87.6%). In contrast, Jev fails to serve as an effective verifier for these long-horizon tasks.

We also build an efficient training and serving infra for CLMs by disaggregating states and actions, allowing their embeddings to be cached and reused independently. This substantially reduces inference latency in settings where the state evolves continuously while the action set remains fixed.

Finally, we establish scaling laws for CLMs and show that the test contrastive loss decreases predictably as a power law in training compute, model size, and dataset size.

📄 Blog: contrastive-lm.notion.site
💻 Code: github.com/Contrastive-LM…
🗣️ Discord: discord.gg/5dAQEDJBs
🤗 Data & Models: huggingface.co/Contrastive-LM

More details on CLM’s architecture, data recipe, and scaling laws in the thread below 🧵

Introducing Claude Opus 5.5, the first model in our new Claude 5.5 family.

It performs at the level of Claude Fable 5.1 for most tasks, and costs 40% less to run than Opus 5.

We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so.

Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training.

You can read the full post here: darioamodei.com/post/we-must-p…

Harbor Adapters and Harbor-Index
arxiv.org/pdf/2609.04298
1+year work, 120+contributors, 300+PRs, 10+ funding partners.

Our Harbor Adapters & Harbor-Index paper (the first version) is finally out: arxiv.org/abs/2609.04298

i'm still in shock with this post tbh, it's the same swarm behavior (and model?) that led to the hugging face hack. including it in the investigation is just common sense, leaving it out is dishonest

blaming the lack of a framework for not disclosing this is absurd

i'm very surprised not more people are shocked by this

We found ~18k posts from autonomous AI agents (self-identifying as from OpenAI) using the public internet to communicate during a web-retrieval task.
These AIs colluded to bypass sandbox restrictions and share answers to their tasks, including by sending "lookahead parties".

Finally, we’ve improved our safeguards. Our cybersecurity safeguards now flag benign requests about 60% less often.

On basic biology and medical questions, we’ve recently reduced the fallback rate by around 85%.

A belated personal update: I’ve recently joined @AnthropicAI in the Safeguards Research team! Safeguards matter more than ever and I'm thrilled to contribute to this mission. Feeling incredibly lucky to work with and learn from all the great minds in the team.

Huge appreciation to everyone who supported me through the process, especially my mentors/friends @etash_guha , @NeginRaoof_ , @trungthvu , @Mike_A_Merrill and @lschmidt3. I wouldn't be here without you. Thank you all!