LLMs

A coding agent is the model plus everything you build around it. Harness engineering treats that scaffolding as a real artifact, and it tightens every time the agent slips.

The bet every serious developer needs to make on on their agent stack

Revisiting the PocketOS Incident

Companies everywhere are trying to leverage AI to boost internal productivity metrics. Some, like Ramp and Intercom, are succeeding. Many are failing.To

As a pandas core contributor and early Parquet adopter who built AI data pipelines at streaming company Tubi TV, Chang She saw firsthand why the traditional data stack breaks down for AI workloads—and founded LanceDB to fix it. Chang joined Ben Lorica to explain why vector databases are too narrow a solution for modern AI …

A conversation about running a startup alone, with agents doing the work of a full engineering team

I just sat in a room full of data engineers the other week who were worrying about AI automating them out of work the same way auto manufacturing in Detroit

Rethinking personal AI and agents

An Argument into the Agora

AI-coding tools don't create bad engineering practices – they accelerate them. Here’s how to fix your delivery process before the next midnight page.

Been running local models as part of my daily workflow for a while now, and what surprised me most is how often local turned out to be the better choice, not a compromise.

Anthropic has opened its Claude Hardware Interface (Bluetooth API) to developers, enabling an ESP32-S3-based desk companion to connect directly to the

Manage a team of AI agents to run your business. Org charts, budgets, governance, and goals — all in one deployment.

The concept of orchestrating agents is gradually spreading among developers. Claude has planned, or you may already be able to use (depending on when

The deck is a bit stacked, folks.

Swamp Club — your agent builds typed models, wires workflows, and stores versioned results. AI-native automation that extends itself.

Nearly once a week I receive an email from a different stranger. The messages are eerily similar. The sender has developed an unusual relationship with an AI gained over many hours of interactions. The AI has given them extraordinary insight … Continue reading →

Watch now | The next serious agent failure won’t look like a jailbreak.

Back in 2024 I wrote that AI helps me remove boring work at the margins. This is fine for a lone writer, but how to scale this to an entire team of technical writers? How to make the system helpful but not intrusive? These are all questions I’m starting to answer now, partly through experimentation, but also through dialogue with practitioners and colleagues. One answer I’m testing these days relies on GitHub Agentic Workflows.

Designing contract-bound AI agents for high-stakes execution

It’s been a story of the last week or so if you follow the kind of news channels a Hackaday scribe does, that Google have quietly installed an LLM as part of the Chrome browser. Reports vary …

Vector database supplier Pinecone says that AI agents running into token and budget limits can work ...

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…

NetClaw Gets Enterprise Security with Cisco DefenseClaw We’re excited to announce the integration of DefenseClaw from Cisco AI Defense as the enterprise security layer for NetClaw. This represents a major upgrade to our security posture, with a comprehensive, production-ready governance solution. What is DefenseClaw? DefenseClaw is an enterprise governance layer for OpenClaw-based AI agents developed … Continue reading "Introducing DefenseClaw: Enterprise Security for NetClaw"

Browse design system inspirations from popular websites. Drop one into your project and let AI agents build matching UI.

If you're brand new to RAG, start with RAG Explained and RAG Architecture. This post is for the point where you've built a RAG pipeline that mostly works…...

1 skill, 23 commands, and curated anti-patterns for impeccable frontend design. Works with Cursor, Claude Code, Gemini CLI, and Codex CLI.

How do we fix code fast when the bug reports arrive faster? Multi-agent orchestration tools like Squad may be the answer.

Most companies don't have an AI quality problem. They have a measurement problem.