The open-source framework for AI SRE agents, and the training and evaluation environment they need to improve. Connect the 60+ tools you already run, define your own workflows, and answer production questions on your own infrastructure.
Source: github.com
A deliberately simple watermark model shows how much room a text watermark has: the entropy available at each token, how a small bias becomes detectable, and why length matters.
Read More![AI Agents List [2026] | Frameworks, Agentic Harnesses & Useful Repos](https://images.unsplash.com/photo-1697577418970-95d99b5a55cf?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3w5ODE4OTh8MHwxfHNlYXJjaHw4fHxhaSUyMGFnZW50fGVufDB8MHx8fDE3OTA0NDU0OTV8MA&ixlib=rb-4.1.0&q=80&w=400)
The original was basically my own notepad that I decided to post before losing another version somewhere on my desktop lol. This one keeps that idea, with a much bigger list and a bit more organisation. There are frameworks for building your own agents, coding tools you can actually open and use, research agents, browser automation, voice agents, and a dedicated section for agentic harnesses. Also included the useful boring stuff: testing, tracing, permissions and checking whether a project is still maintained.
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In this post, we share how Claude made the open-source models that scientists use to predict and design biomolecules faster and more memory-efficient. Claude, working within Claude Science, optimized more than 30 of these models in just under four weeks, speeding them up roughly 4x on average. It also created a low-memory mode that enables the accurate prediction of biomolecular systems larger than 10,000 tokens (amino acids, nucleotides, and atoms from small molecules and ions) on a single NVIDIA GPU node. We are open-sourcing all of the optimized code and announcing a protein design competition co-sponsored with Adaptyv Bio, backed by up to $1 million in Claude credits and wet lab validation for over 5,000 designs.
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