Machines

It's been just over two years and two months since ChatGPT launched, and in that time we've seen Large Language Models (LLMs) blossom from a novel concept into one of the most craven cons of the 21st century — a cynical bubble inflated by OpenAI CEO Sam Altman built to sell into an economy run by people that have no concept of labor other than their desperation to exploit or replace it. I realize that Large Language Models like GPT-4o — the model that powers ChatGPT and a bunch of other apps —

Digital agency CEO Josh Gross explains how AI tools like ChatGPT are killing traditional SEO and what agencies need to do to adapt and thrive in 2025.

My kid likes listening to podcasts sometimes and it’s cool with me! Story Pirates, for example, rules. She must have typed in “Bluey” at some point into the podcast app we use and…

Sergey Filimonov's blog

Peter Naur's 1985 theory of programming explains why experience matters more in the age of AI-generated code

Developers behind GitHub Copilot discuss what it was like to work with OpenAI’s large language model and how it informed the development of Copilot as we know it today.

Explaining Neuron Behavior at Scale + Neuron Viewer

AI is changing how content gets discovered. Now, SEO ranking ≠ LLM visibility. No one has all the answers, but here's how we're adapting our approach to SEO for LLMs and AI search.

Our exclusive industry report is out!

Explore the mathematical and cognitive limits that stop large language models from achieving true human-like engineering intelligence

Introducing agent mode for GitHub Copilot in VS Code, announcing the general availability of Copilot Edits, and providing a first look at our SWE agent.

The battle for brand agents and ultimately platform-level agents to become the default, and a new era of luxury software is upon us.

There's this restaurant in Tokyo that doesn't have a kitchen.

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.