Strip Ghostty down to a dumb container and send every iTerm2-style shortcut straight to Herdr, no prefix key required.

AI agents churn out massive PRs, accelerating output but compounding cognitive debt. Here's the visualization skill I built to rebuild my mental models.

In production inference deployments, demand fluctuates over time, requiring inference replicas to scale elastically. However, cold-starting inference workloads on Kubernetes can take several minutes.

How and why members of the Claude Code team use HTML instead of Markdown to produce richer, more readable, and easily shareable outputs.

Plus updates from Anthropic's Code w/ Claude conference

Eighteen months ago, our lab introduced DistServe with a simple bet: split LLM inference into prefill and decode, and scale them independently on separate compute pools. Today, almost every production...

Public repository for Agent Skills. Contribute to anthropics/skills development by creating an account on GitHub.

I gave a talk last night at Claude Code Anonymous in San Francisco, the unofficial meetup for coding agent enthusiasts. I decided to talk about a dichotomy I’ve been struggling …

Learn how to configure OpenClaw to use Azure AI Foundry models, giving you a self-hosted AI assistant accessible from Telegram and other chat apps.

Learn how to use Apple's container CLI tool to run Linux containers as lightweight VMs on macOS with sub-second startup times

Search for books, get book details and reviews, discover personalized recommendations, and manage reading lists on Goodreads — all through browser automation.

Learn how to deploy and configure Kimi K2.5 on Azure AI Foundry with this step-by-step guide.

There’s a jargon-filled headline for you! Everyone’s building sandboxes for running untrusted code right now, and Pydantic’s latest attempt, Monty, provides a custom Python-like language (a subset of ...

Handy is a cross platform, open-source, speech-to-text application for your computer

Learn how to execute Docker commands on a remote machine from your local terminal using SSH and Docker contexts

Learn how to use Claude Code CLI with GitHub Models by proxying requests through litellm-proxy

YouTube video by CNCF [Cloud Native Computing Foundation]

YouTube video by CNCF [Cloud Native Computing Foundation]

Today, we are unveiling the next Fairwater site of Azure AI datacenters in Atlanta, Georgia. This purpose-built datacenter is connected to our first Fairwater site in Wisconsin, prior generations of A...

Plus what happens if AI labs train for pelicans riding bicycles?

Explore developer resources, tutorials, API docs, and dynamic examples to get the most out of OpenAI's platform.

Microsoft unveiled its second Fairwater AI datacenter in Atlanta as part of a new AI superfactory working across states in nearly real time.

YouTube video by Dwarkesh Patel

YouTube video by CNCF [Cloud Native Computing Foundation]

View more about this event at KubeCon + CloudNativeCon North America 2025

Ray Direct Transport enables fast and direct GPU transfers in Ray via RDMA-backed transports. Using RDT, we can achieve up to 1000x faster GPU-GPU transfers than Ray’s native object store with a few l...

Plus Living dangerously with Claude, and prompt injection risks for ChatGPT Atlas

Today's LLM inference systems treat individual engines and queries independently for simplicity, but this causes significant resource inefficiencies. While there are proposals to avoid redundant compu...

If you’re an application developer or a cluster administrator, you’ve likely seen how non-uniform memory access (NUMA) can impact system performance. When an application is not fully NUMA-aware…

View more about this event at KubeCon + CloudNativeCon North America 2025

SemiAnalysis recently launched InferenceMAX v1, a new open source initiative that provides a comprehensive methodology to evaluate inference hardware performance. Published results demonstrate that…

YouTube video by Anand Tyagi

YouTube video by @Scale

As AI models grow larger and more sophisticated, inference, the process by which a model generates responses, is becoming a major challenge. Large language models (LLMs) like GPT-OSS and DeepSeek-R1…

Large Language Model (LLM) inference faces a fundamental challenge: the same hardware that excels at processing input prompts struggles with generating responses, and vice versa. Disaggregated serving...

Deploying large language models (LLMs) at scale presents a dual challenge: ensuring fast responsiveness during high demand, while managing the costs of GPUs. Organizations often face a trade-off…

YouTube video by EO

YouTube video by USENIX

YouTube video by USENIX

YouTube video by CNCF [Cloud Native Computing Foundation]

YouTube video by CNCF [Cloud Native Computing Foundation]

YouTube video by Harvard Business Review