Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
Agentic coding and persistent returns to expertise
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
Labor market impacts of AI: A new measure and early evidence
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
The assistant axis: situating and stabilizing the character of large language models
Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.
The Picture They Paint of You
Musings on the way we frame Coding Assistants, AI SREs, and what this communicates in terms of how these roles are perceived.
AI should help us produce better code - Agentic Engineering Patterns
AI should help us produce better code - Agentic Engineering Patterns
✨🙌 AI that helps communities thrive on their own terms
Open protocols + AI-enabled coding = building what we need for ourselves
AI Makes the Easy Part Easier and the Hard Part Harder for Developers
AI handles writing code but leaves the hard work: investigation, context, validation. Why vibe coding has limits and AI assistance can backfire.
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.
In defense of not reading the code | Ben Shoemaker
Last week, I wrote an article whose purpose was to discuss where I saw AI-assisted coding going. That's not what generated 200 comments worth of passionate...
What AI coding costs you | Tom Wojcik
What's the effect of the prolonged AI usage among coders and is it tracked correctly, if it all?
The 80% Problem in Agentic Coding
Managing comprehension debt when leaning on AI to code
</> htmx ~ Working With AI: A Concrete Example
In this essay, Carson Gross walks through a concrete bug fix in hyperscript to show where AI helped, where it fell short, and why keeping a knowledgeable human in the loop is what kept complexity in check.
I used AI. It worked. I hated it.
I used Claude Code to build a tool I needed. It worked great, but I was miserable. I need to reckon with what it means.
Vibe Coding Failures: Documented AI Code Incidents
A curated directory of real-world incidents where AI-generated code failed in production.
The Persona Selection Model: Why AI Assistants might Behave like Humans
What sort of thing is a modern AI assistant? One perspective holds that they are shallow, rigid systems that narrowly pattern-match user inputs to training data. Another perspective regards AI systems as alien creatures with learned goals, behaviors, and patterns of thought that are fundamentally inscrutable to us. A third option is to anthropomorphize AIs and regard them as something like a digital human. Developing good mental models for AI systems is important for predicting and controlling their behaviors. If our goal is to make AI assistants that are useful and aligned with human values, the right approach will differ quite a bit if we are dealing with inflexible computer programs, aliens, or digital humans.