4 posts tagged with "development"

Introduction​

I came back to my AI assistant's terminal and could not find its answer. Notifications had pushed it out of view. The assistant had done the work. I still had to find it.

This was happening often enough that I told it: "the moment I cycle back, I never see your response". I move between messages, browser tabs, pull requests and terminal sessions. An answer that needs me to watch a pane at the right moment does not fit that loop.

The same assistant also watched incoming events, answered one-off questions, read logs, supervised workers and learned from my corrections. Every new responsibility brought tools and instructions. Its role file more than tripled in length in a little over a month. I had hired an assistant and given it my entire inbox.

Hence a wealth of information creates a poverty of attention.

Herbert A. Simon, Designing Organizations for an Information-Rich World, 1971

Introduction​

RSI stands for Recursive Self-Improvement: an AI system that improves itself, then uses the improved version to improve itself again. It is one of the milestones AI is expected to reach one day. In 1965, the mathematician I. J. Good put it like this:

Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an 'intelligence explosion,' and the intelligence of man would be left far behind.

I. J. Good, Speculations Concerning the First Ultraintelligent Machine, 1965

Introduction​

Every codebase eventually needs the same change in many places: a library swap, an API that changed shape, a convention the team agreed on last week. You know the usual options. Find and replace sees only text. Doing it by hand works for ten places and falls apart at three hundred. An AI assistant will happily make all three hundred edits, and then someone has to review each one.

In this blog, we will look at three tools that read code at three different levels. grep reads text. ast-grep reads structure, the syntax tree your editor already builds. A small local model, asked through classif, reads meaning. They are separate tools, each takes the part of the job it can see, and the interesting part is where each one stops.

Introduction​

In this blog, we will look at how programs make decisions about text, and how that changed once small language models started running on our own machines. Along the way, I will introduce classif, a small command-line tool I built that lets a shell script ask a local model a question and act on the answer.