Machines

Learn how to automatically document your API's behavior us a local-first tool called Demystify.

As AI writes code, developers must become better product thinkers

Get started with the Agent Client Protocol (ACP)

Contribute to MCP-Manager/MCP-Checklists development by creating an account on GitHub.

Lessons I learned from implementing marimo's MCP client

The what, why and how of understanding and building MCP servers

Today, AWS announces the open-source AWS Serverless Model Context Protocol (MCP) Server, a tool that combines the power of AI assistance with serverless expertise to enhance how developers build modern applications. The Serverless MCP Server provides contextual guidance specific to serverless development, helping developers make informed decisions about architecture, implementation, and deployment. This post describes how the Serverless MCP Server works with AI coding assistants to streamline serverless development.

Guest post about Software 3.0 from Sid Rao

Hello! If you are seeing this you are either early or currently attending my talk at DataEngBytes. Learning how to build an agent is one of the best things you can do for your personal development. Cursor, Windsurf, Claude Code and Ampcode.com are 300 lines of code running in a while true loop. Learn how to build your own agent

Earlier this month, I used Claude to port (parts of) an Emacs package into Rust, shrinking the execution time by a factor of 1000 or more (in one concrete case: from 90s to about 15ms). This is a variety of yak-shave that I do somewhat routinely, both professionally and in service of my personal computing environment. However, this time, Claude was able to execute substantially the entire project under my supervision without me writing almost-any lines of code, speeding up the project substantially compared to doing it by hand.

How to Design a Fully Local Multi-Agent Orchestration System Using TinyLlama for Intelligent Task Decomposition and Autonomous Collaboration

How engineers and teams use MCP servers: from debugging to working with legacy systems, & giving non-devs more access. Details from 40+ devs – with some surprises

What I use them for and what I don't

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

Six months after the hype began, is vibe coding sustainable? We look at the pros and cons, and why blending vibes with structure is key.

A report describing an a highly sophisticated AI-led cyberattack

A brain dump of all the ways I've been using Claude Code.

Patterns for managing agent context.

Frameworks for LLM Agents have been surprisingly disappointing. I want to offer some principles for building agents based on our own trial & error, and explain why some tempting ideas are actually quite bad in practice.

A new paper that we will expand into our next book

Soundtrack: Queens of the Stone Age - First It Giveth Before we go any further: This is, for the third time this year, the longest newsletter I've ever written, weighing in somewhere around 18,500 words. I've written it specifically to be read at your leisure — dip in and out where you'd like — but also in one go.  This is my comprehensive case that yes, we’re in a bubble, one that will inevitably (and violently) collapse in the near future. I'll also be cutting this into a four-part episode

Entry-level jobs are disappearing. In their place: unpaid gigs, cold DMs and self-starters scrambling for a foothold. The ladder’s gone – what’s replacing it, and who’s being left behind?

CreativeMornings is a breakfast lecture series for the creative community. Join us at one of our free monthly events around the world or watch the talks online!

Hi, my name is Peter and I'm a Claudoholic. A reflection on AI addiction, extreme work culture, and the blurry line between productivity and obsession in the age of agentic engineering.

Collection of extracted System Prompts from popular chatbots like ChatGPT, Claude & Gemini - asgeirtj/system_prompts_leaks

An interactive visualization tool showing you how transformer models work in large language models (LLM) like GPT.

maybe it's anti-innovation, maybe it's just avoiding hype. But one thing is clear, I'm completely done with hearing about AI.