Beyond grep: The case for a context-rich AI coding harness
Augment Code's Vinay Perneti talks models, harnesses, and context.
Augment Code's Vinay Perneti talks models, harnesses, and context.
AliExpress has been hit with a €550 million (about $629 million) fine for violating Europe's Digital Services Act (DSA) rules by failing to prevent illegal, unsafe, or counterfeit products from being sold on the e-commerce platform. The European Commission ruled that AliExpress didn't take effective measures to reduce the dissemination of illegal products, noting the […]
Thomas Betts talks with Clare Liguori, the technical lead on the open source Strands Agents SDK. The conversation covers how Strands Agents has grown from a Python SDK to a full agent harness running in production. Clare shares some lessons learned from building agents at scale, shifting to a model-driven architecture, and what comes next as the LLMs that underpin agents continue to improve. By Clare Liguori
From monsters to kittens to strategy games, these sets will liven things up on nights when everyone is tired of screens.
So, I just read LeCun's interview with Nebius Science. I feel he had some cool points about LLMs being able to answer things, but not literally understand the physics of the physical world. (Like, being able to explain a task and actually performing it are two completely different things.) But I wanted to get opinions on what others thought of his solution to the problem. He thinks JEPA could be the solution. But it made me think about whether JEPA is genuinely the architectural solution to this, or if we’re just looking for a "magic bullet" that doesn't exist yet in our toolbox I have the link here: https://nebius.science/stories/meet-yann-lecuns-lab-and-the-ai-world-of-2030 submitted by /u/ConsciousGreenPepper [link] [留言]
From countertop kits to a bathroom bucket full of straw and beyond, I spent a year testing popular mushroom-growing methods. Here’s what fruited—and what just grew mold.
China's leading AI companies are ramping up the pressure on Silicon Valley, as Moonshot and Alibaba unveiled models they claim can go toe-to-toe with the best from OpenAI and Anthropic at a fraction of the cost. The rapid-fire releases suggest America's lead at the AI frontier is increasingly tight, just as the technology is becoming […]
Several Chinese businesses associated with the ebike brand Aipas settled a lawsuit with Amazon and the safety certification company UL in July.
AWS released Loom, an open-source reference platform on AWS Labs for governing AI agents at scale. Built on Strands Agents and Bedrock AgentCore Runtime, it implements RFC 8693 token exchange for identity propagation through delegated actor chains, config-driven deployments without runtime code generation, and mandatory tagging. AWS positions it as an example, not a managed service. By Steef-Jan Wiggers
OpenAI shares lessons from deploying long-running AI models, highlighting new safety risks, observed failures, and improved safeguards through iterative deployment.
A new toolkit for attorneys in Massachusetts targets the technologies police use—and conceal—to build criminal cases, from facial recognition to AI-written police reports.
Four-minute miles are almost routine. Middle schoolers are beating college runners. Inside the youth track boom that’s turning kids and teens into speed machines.
Moving from Windows to macOS often creates a small workflow problem for developers: where did my familiar SSH tools go? PuTTY has been a classic SSH and Telnet client for Windows for many years. Many developers know its interface and workflow, so after switching platforms, the first thought is usually finding a macOS version. The reality is that the macOS ecosystem works differently. There are several practical options depending on how you manage remote systems. Option 1: Use the built-in SSH client on macOS For many developers, the SSH client that ships with macOS is already enough. A typical workflow looks like this: Use the terminal for server access Manage hosts through ~/.ssh/config Store aliases, usernames, ports, and key settings in one place Automate common connection tasks with scripts For example: ssh production-server can replace a long connection command when your SSH configuration is organized properly. This approach works especially well for developers who prefer command-line workflows and manage Linux servers regularly. Option 2: Use a GUI SSH client Some developers prefer a graphical interface because they manage many machines, protocols, or connection profiles. A good GUI client can help with: Organizing dozens or hundreds of servers Saving authentication settings Switching between SSH, RDP, VNC, and other protocols Reducing repetitive configuration work The macOS App Store has many SSH clients available. The right choice depends on whether you only need SSH or you need a complete remote management workflow. Tools like DartShell are designed around this multi-protocol scenario, where developers may need SSH for Linux servers, RDP for Windows machines, and other remote access methods in one place. Choosing the right workflow The decision usually comes down to how you work: A few Linux servers: macOS Terminal + SSH config is usually enough. Many servers and different protocols: a GUI management tool can save time. Team environments: centralized connec