AIs limited to pure computation (Tool AIs) supporting humans, will be less intelligent, efficient, and economically valuable than more autonomous reinforcement-learning AIs (Agent AIs) who act on their own and meta-learn, because all problems are reinforcement-learning problems.
AI Is a Waste of Time
The newest AI tools are accelerating basic research and scaring the general public. But many people are simply using them as toys.
Stop saying that AI is just a tool and it only matters how it is used
I’m tired of this phrase and this simple way of thinking about tools. This blog post is a wandering train of thought on the topic of what tools are and why it matters to be even slightly more mature in how we think about them.
AIs are not people
Humans and other fleshy life-forms are valuable in ways that artificial intelligence never can be.
Why AI hasn’t replaced software engineers, and won’t
Coding agents as normal technology
From Genius Science to Scenius Science - Cosmik Labs
Why personal AI tools might not be all we need to revolutionize science
Training Agentic Reasoners — Will Brown, Prime Intellect
How AI Tools Differ from Human Tools
Why the mental models we've built for human interfaces don't work for AI, & how Anthropic's latest guidelines are reshaping tool design for better performance & efficiency.
Software engineering may no longer be a lifetime career
I don’t think there’s compelling evidence that using AI makes you less intelligent overall1. However, it seems pretty obvious that using AI to perform a task means you don’t learn as much about performing that task. Some software engineers think this is a decisive argument against the use of AI. Their argument goes something like this:
Artificial intelligence
Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in engineering, mathematics and computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals.[1]
The argument against AI agents and unnecessary automation
Opinion: OpenAI's Operator a solution in search of a problem
How Uber uses AI for development: inside look
How Uber built Minion, Shepherd, uReview, and other internal agentic AI tools. Also, new challenges in rolling out AI tools, like more platform investment and growing concern about token costs
Building and evaluating AI Agents — Sayash Kapoor, AI Snake Oil
AI agent runs amok in Fedora and elsewhere
Agentic AI systems can be used to do a variety of things autonomously on behalf of a human user [...]
Less is more, more or less
In the age of AI, knowing what not to build might be the most important skill of all.
The Gap Through Which We Praise the Machine
My current theory of agentic programming: people are amazing at adapting the tools they're given and totally underestimate the extent to which they do it, and the amount of skill we build doing that is an incidental consequence of how badly the tools are designed.
