Tagged: agentic-engineering

New term added to my vocab that I'm going to use a lot: "feedback loopable".

Lewis Metcalf:

Agents are most powerful when they can validate their work against reality. When they have feedback loops. The problem is, some work is hard to organize in a way that an agent can easily get feedback. The software we build and the tools we use are built for humans. Humans with eyeballs and hands and fingers.

This article is about how to make those problems easier for agents. It's a way to create an environment for your agents so that they can solve problems on their own, and so that you (the human) can intuitively guide them without getting in the way.

This process of building something for humans using methods built for agents is what I call: making it feedback loopable.

Nice and clever use of uv’s run inline dependency management and Claude Project Custom Instructions to create Python scripts that are easy to run without any setup, even while depending on Python’s rich set of libraries.

I’ve used this workflow for a few scripts in the last couple of weeks, and it works remarkably well.

You can then go a step further — add uv into the shebang line for a Python script to make it a self-contained executable.

It is not the end of programming. It is the end of programming as we know it today. That is not new. The first programmers connected physical circuits to perform each calculation. They were succeeded by programmers writing machine instructions as binary code to be input one bit at a time by flipping switches on the front of a computer. Assembly language programming then put an end to that. It lets a programmer use a human-like language to tell the computer to move data to locations in memory and perform calculations on it. Then, development of even higher-level compiled languages like Fortran, COBOL, and their successors C, C++, and Java meant that most programmers no longer wrote assembly code. Instead, they could express their wishes to the computer using higher level abstractions.

Eventually, interpreted languages, which are much easier to debug, became the norm.

BASIC, one of the first of these to hit the big time, was at first seen as a toy, but soon proved to be the wave of the future. Programming became accessible to kids and garage entrepreneurs, not just the back office priesthood at large companies and government agencies.

The above is the central thesis of the article, and I strongly agree with it. The article also explores many more angles on the impact of AI coding, mostly through quoting and referencing others; I agree with some of these perspectives, whilst not so much with others. Nevertheless, it’s quite thought-provoking.