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.

What if your AI budget went to the engineers who use it best? Blanket usage caps are a hiring freeze in disguise. Introducing efficiency-based auto-approvals for your most productive engineers, plus Devin Coach to help everyone get there. devin.ai/blog/efficiency-bas…

a brand new model paradigm! introducing 𝚌𝚕𝚊𝚒𝚛𝚒𝚌: a system one model for extracting, computing, estimating, and predicting values from unstructured inputs. blog.cloudflare.com/clairic-…

Today, we're launching Sazabi version 1.0. The reality of shipping software as a team in the age of AI is actually crazy. Agents merging their own PRs. Hundreds of deployments per day. A codebase that is constantly changing. Junior developers with 10x or 100x leverage. 😵‍💫 I spent the last year building a safety harness for teams that ship with AI. It's called @sazabi. The premise is simple: 1. You send us logs. 2. We detect anomalies, investigate them, and send you back rich, actionable alerts about real problems in your app. Sazabi helps you find issues before your users notice. No monitors or noisy alerts. Just pure signal. And today we're making it available for anyone to use.

“Junior let’s break out roach into its own repo” Memory means I don’t even have to explain what roach is, where it is Yall are sleepin on ergonomics still

Today at Google Cloud’s Gemini at Work event, we announced Gemini, a new single universal agent for work that has all of your business context and can be used for everything from knowledge work to answering questions, and content creation to coding, all from a single prompt box. It’s built around core architectural principles: ☑️ Unified Agent: Gemini can answer questions, do knowledge work and generate code from a single prompt box. ☑️Access: Gemini is web-based and can be accessed from any device and integrated into third-party applications. It can also operate without a dedicated user interface. ☑️Persistent Execution: It runs in the cloud, which means it maintains a single set of memories, context and one personalization graph no matter where you access it. ☑️Multi-Agent Orchestration: Gemini can create sub-agents to tackle multi-step tasks and can also act as a coworker agent with a defined role and its own dedicated identity ☑️Context: Gemini knows your tools, data, and work history and learns how you work the more you use it. ☑️Model Choice Flexibility: It orchestrates across multiple models to deliver optimal quality and lower your costs.

🤖 How well do agents learn from experience? We study agents that amortize experience into reusable artifacts and introduce Agent Plasticity to measure how efficiently they improve on held-out environments. Top performer ≠ most efficient learner.