Generative AI coding demands what we've always known: modularity, clear boundaries, disposable components. Principles that scaled human teams are now table stakes. Here, we make the implicit explicit
One Developer, Two Dozen Agents, Zero Alignment
Why we need collaborative AI engineering and a tour of Ace: the multiplayer coding workspace
Pace Layers and AI Integration - The Phoenix Architecture
Generative AI in a Nutshell - how to survive and thrive in the age of AI
The 8 Levels of Agentic Engineering — Bassim Eledath
AI's coding ability is outpacing our ability to wield it effectively. That gap closes in levels — 8 of them. Here's the progression from tab complete to autonomous agent teams.
Compositional Structures as Substrates for Human AI Co-creation Environment
The Myth of the Instant Cake Mix
How to think about creative tooling in the new world of generative AI
Generative UI: The AI agent is the front end
In a new model for user interfaces, agents paint the screen with interactive UI components on demand. Let’s take a look.
How Claude marks AI-generated content | Claude Help Center
Anthropic has signed the EU AI Act's Article 50(2) Code of Practice on Transparency of AI-Generated Content, as a provider of both generative AI models and generative AI systems. This article describes how we’re planning to put those commitments into practice, how marking works, and what its limitations are. We’ll update this article and publish more detailed technical guidance as it becomes available.
Collaborative AI Engineering: One Dev, Two Dozen Agents, Zero Alignment — Maggie Appleton, GitHub
Agent Skills
AI coding agents take the shortest path to done, which usually means skipping the specs, tests, and reviews that make software reliable at scale. Agent Skill...
In spite of hype, many companies are moving cautiously when it comes to generative AI | TechCrunch
Companies are extremely interested in generative AI as vendors push potential benefits, but turning that desire from a proof of concept into a working product is proving much more challenging.
pguso/ai-agents-from-scratch
Demystify AI agents by building them yourself. Local LLMs, no black boxes, real understanding of function calling, memory, and ReAct patterns.
Equipping agents for the real world with Agent Skills
Discover how Anthropic builds AI agents with practical capabilities through modular skills, enabling them to handle complex real-world tasks more effectively and reliably.
How to harness AI
"Coding agents" are complicated but intelligible
Meet Foundry: An AI Startup that Builds, Evaluates, and Improves AI Agents
