the point of that section is that attackers and security researchers will use / are using loops, and you as the maintainer are not able to opt out of others doing this. an unwilling participant.
My favorite part of Ruby is the testability. You can test anything, easily, without having to make interfaces and other design decisions specifically around tests.
Testing anything in Ruby is dead simple, and agents are very good at writing the tests.
The REPL is also a big win for agents. Reproducing a bug, or exploring how to build a feature, agents can get a lot of mileage out of a rails console.
A lot of the developer ergonomics are just as helpful to agents.
half the time you’re going to discover the right decision / path while you’re coding.
focus time went from hammering code to figuring out how to solve the problem. PRs are now how we exchange ideas. meetings are still productivity theater.
The author effectively argues deep thinking is dead, that people are no longer going to take the time to understand the problem and solution space before they solve it.
I think that’s untrue, I think it’s /more/ important than before. I think you’re going to have significantly more leverage with these tools if you’re capable of thinking.
If you’re not, you’re just going to produce garbage extremely fast.
The use of these tools does not preclude you from being the potter at the clay wheel.
People talk about writing the code itself and being intimate with it and knowing how every nook and cranny works. This is gone. It’s more akin to on call where you’re trudging over code and understanding it as you go.
Good code is easy to understand in this scenario; you get a clear view of intent, and the right details are hidden from you to keep from overwhelming you with detail.
We’re going to spend a lot more time reading code than before, better make it a very good experience.
> This post brings up a lot of (imo true) points that I honestly can't share with the ai-lovers at work because they will just get in a huff. But the OP is right - we automate stuff we don't value doing, and the people automating all their code-gen have made a very clear statement about what they want to be doing - they want _results_ and don't actually care about the code (which includes ideas like testing, maintainability, consistent structure, etc).
I havent run into this type yet, thankfully. As an AI lover, the architecture of the code is more important than before.
* It’s harder to understand code you didn’t write line by line, readability is more important than it was before.
* Code is being produced faster and with lower bars; code collapsing under its own shitty weight becomes more of a problem than it was before.
* Tests/compiler feedback helps AI self correct its code without you having to intervene; this is, again, more important than it was before.
All the problems I liked thinking about before AI are how I spend my time. Do I remember specific ActiveRecord syntax anymore? No. But that was always a Google search away. Do I care about what those ORM calls actually generate SQL wise and do with the planner? Yes, and in fact it’s easier to get at that information now.
I keep seeing “Claude image understanding is poor” being repeated, but I’ve experienced the opposite.
I was running some sentiment analysis experiments; describe the subject and the subjects emotional state kind of thing. It picked up on a lot of little detail; the brand name of my guitar amplifier in the background, what my t shirt said and that I must enjoy craft beer and or running (it was a craft beer 5k kind of thing), and picked up on my movement through multiple frames. This was a video slicing a frame every 500ms, it noticed me flexing, giving the finger, appearing happy, angry, etc.
I was really surprised how much it picked up on, and how well it connected those dots together.