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Introducing RL with Neural Feedback (RLNF). We have found reliable ways to train AI models to respond to human preferences purely from brain signals. The example below is a picture of a face that self-transforms into a more attractive version for the subject as they are looking at it.

Introducing Cartesia Managed Agents: our end-to-end voice agent platform for enterprise. #1 on @ArtificialAnlys Speech Agent Arena and @ServiceNow EVA-Bench, built by co-designing our voice models and harness as one system. Check it out → cartesia.ai/blog/managed-age…

Today we're launching @tryAlanAI so developers can stop babysitting their coding agents. We kept running into the same problem ourselves. Even as agents got better at writing code, we were becoming glorified button-pushers for our own AI: starting every run, feeding them context, unblocking failures, and checking their work. We built Alan to change that.

Today, we’re introducing the next chapter of Concurrence and the world’s greatest leap toward Superintelligent Care. When I was 13 I lost my mom to cancer that should’ve been caught earlier. We’re building a system that sees every patient’s future in time to change the outcome

Last month, 52% of the pull requests our team merged were automated through SuperPlane. Today, we’re launching @superplanehq 1.0: an open source software factory for engineering teams. We built it because using a coding agent can feel like becoming its assistant. Starting sessions. Checking its work. Chasing failing CI. SuperPlane takes on that coordination: - Scans your backlog and proactively picks up tickets suited to automation. - Runs a coding agent and verifies the result. Works through CI failures and review feedback. - Your team reviews the evidence and decides what ships. The setup, instructions, and standards are shared across the team. When someone improves the process, everyone benefits. Choose your agents and models. Run it on your own infrastructure. We spent more than a decade building CI/CD at Semaphore. We’ve seen how much teams can accomplish when routine work runs reliably in the background. Now we’re bringing that approach to coding agents. Here’s how it works:

Your personal website is the new resume

When I was 13, I lost my mom to breast cancer. I still wonder if it could have been prevented. When she found the lump, she did everything right. She went to her primary care doctor, and he told her it was nothing. My mom wasn’t convinced, so she went to a women’s health specialist for a second opinion and was told the same thing. A year passed before she saw a third doctor who was shocked that nothing had been done and ordered tests the same day. By the time she was diagnosed, the cancer had already spread. For the next three years, she went through chemo, surgery, and radiation. Specialist after specialist, asking the same questions again and again. After she passed away, there were two thoughts I couldn’t out of my head: (1) Somewhere, a doctor must have seen a case like my mom’s and caught it early. (2) Nothing that doctor learned had any way to reach her. Healthcare runs in my family. All four of my sisters are nurses or pharmacists, and my fiancée spent the pandemic working in a multi-organ transplant recovery ward. I’ve seen how hard clinicians work, and how much of that work requires understanding the patient and recognizing patterns from past cases. That’s why a doctor can practice for 30 years and get better every year, while a hospital can treat millions of patients without getting much better at treating the next one. What’s missing in healthcare is the infrastructure for it to learn from its own experience. If we don’t examine the cause and outcome of every interaction, how do we get better at knowing which signs to watch for? I spent years at Google and Upwork building AI from human expertise, then eventually left big tech to work on the one problem I couldn’t stop thinking about. I started a company called Concurrence (@concurrencehq) and raised $24M to build data and AI systems that enable healthcare orgs to learn from every patient they treat. Nothing learned is lost, and it reaches the next patient who needs it. We’ve already supported care for over 10 million patients worldwide. My mom deserved a doctor who had seen her case a thousand times. Every patient does.

I asked Claude to build an office for the @tavus PALs... I was not expecting it to build THAT kind of office

Today, @agentmail has processed over 1 Billion emails. A year ago, we processed under 20 million. So we figured it was time for AgentMail to grow up a little too :)

What is AI really capable of in bio? To separate hype from reality, we spent 3 months working firsthand with @AnthropicAI's internal research model to see if it could create an experimental scorpion antivenom. Introducing Citrini Therapeutics. citriniresearch.com/p/citrin…

you don't need to be chronically online to grow on tech twitter.

you don't need to be chronically online to grow on tech twitter.

Today we're introducing Okara CMO v4. Drop in your website and it deploys a team of self-learning agents to help you get traffic and users. Try it now at okara.ai

We raised $9M to give your agents the internet. Led by @generalcatalyst, with @orangecollectv and Robinhood Ventures. Search, scrape, crawl, monitor with one API trusted by 800+ customers. We’re making it ridiculously easy to build with web data.