Machines

Lessons from an 8-agent pipeline that builds production-quality React design system components from a Figma file — contracts, halting, and trade-offs.

Copilot can research a repository, create an implementation plan, and make code changes on a branch. You can review the diff, iterate, and create a pull request when you're ready.

The world's 1st Gasket Mount low-profile keyboard offers smoothest typing experience ever, excelled with Full POM switch, All Aluminum design, Hot Swap, RGB and more.

Use the right tool for the job.

Context-Bench is a new benchmark for AI models, assessing their context-engineering skills in managing information and reasoning across multi-step tasks.

Discover how to benchmark AI skills across Claude models. Learn if your skill enhances or worsens performance. Start optimizing today!

There is a photograph of a coral reef on the wall of my dentist’s office.

How many times does Sal Khan get to fail?

GitHub introduces remote control for Copilot CLI, allowing users to manage terminal sessions from web or mobile, reflecting a shift in AI coding agent usage.

Pair Opus as an advisor with Sonnet or Haiku as an executor, and get Opus-level intelligence in your agents at a fraction of the cost.

We built an agentic security investigation service to help us research alerts as part of our mission to keep Slack secure and protect our customers. Our service deploys teams of AI agents that collaboratively perform security investigations. AI agents free human analysts from tedious data gathering tasks. Over just the first quarter of their deployment, our agents have performed over 7,500 investigations, issuing over 500,000 tool calls. Our agents are enabling us to gain unprecedented real-time insight into Slack’s infrastructure in a way we could never do with human labor alone.

Excerpt In complex, long-running agentic systems, maintaining alignment and coherent reasoning between agents requires careful design. In this second article of our series, we explore these challenges and the mechanisms we built to keep teams of agents working productively over long time spans. We present a range of complementary techniques that balance the conflicting requirements…

Behind the vague "AI will change everything" hype, something very interesting and concrete is happening with agents: They're doing real work. Researching tools, comparing vendors, spinning up infrastructure. And they're starting to have budgets.

For eight years, I’ve wanted a high-quality set of devtools for working with SQLite. Given how important SQLite is to the industry1, I’ve long been puzzled that no one has invested in building a really good developer experience for it2. A couple of weeks ago, after ~250 hours of effort over three months3 on evenings, weekends, and vacation days, I finally released syntaqlite (GitHub), fulfilling this long-held wish. And I believe the main reason this happened was because of AI coding agents4. Of course, there’s no shortage of posts claiming that AI one-shot their project or pushing back and declaring that AI is all slop. I’m going to take a very different approach and, instead, systematically break down my experience building syntaqlite with AI, both where it helped and where it was detrimental. I’ll do this while contextualizing the project and my background so you can independently assess how generalizable this experience was. And whenever I make a claim, I’ll try to back it up with evidence from my project journal, coding transcripts, or commit history5.

Running OpenCode with Gemma 4 26B on macOS via llama.cpp - fixing tool calling - opencode-gemma4-ollama-macos.md

Learn how to make a minimum viable OpenClaw agent, giving you a starting point to evolve it into something truly useful.

The next era of product development is built on context and agency. Here's how Linear is evolving. And what we're launching today.

Universal CLAUDE.md - cut Claude output tokens by 63%. Drop-in. No code changes. - drona23/claude-token-efficient

I'm the same person who posted the original PSA about two cache bugs this week. Since then I continued digging - total of 6 days (since 26th of...

...

Despite the fears, AI is creating jobs faster than ever. And as we see scale and productivity grow, salaries will go up and jobs get better.

The commerce renaissance is here. Explore 150+ product updates across AI, retail, and more.

Analyzing the system of record and software debate

Ne plus se limiter à des interfaces textuelles ou à des images pour interagir avec l'intelligence artificielle ? Les Agents Drive Interface sont là pour une intégration native des LLMs dans nos applications !

Stop wasting tokens on AI summaries. Learn how to architect a strategic 'Shaper' agent using Gemini to reclaim 32 hours of founder liquidity per month.

Build a financial assistant with MCP, EODHD, and Python so LLMs narrate real market data instead of inventing metrics.

An eight-month study found that these tools made productivity surge—as well as cognitive fatigue, unsustainable hours, and other problems.

1 skill, 17 commands, and curated anti-patterns for impeccable frontend design. Works with Cursor, Claude Code, Gemini CLI, and Codex CLI.