idoco
Joined 13 years ago
Joined 13 years ago
I actually first heard about it from the Acquired podcast, which is another great example of that same trend.
Only about 5% of the world’s population are native English speakers, but more than twice that number use it daily. For many, AI rewriting isn’t about losing personal style—it’s about making sure they can communicate clearly in a language that isn’t their first.
It’s fair to dislike how AI flattens unique voices, but for a huge part of the world, it’s not erasing personality—it’s making participation possible.
Keeping a human in the loop is essential, in my experience. The AI does the heavy lifting, but we make sure the tests are genuinely useful. That balance helps avoid the trap of churning out “dumb” tests that might look impressive but don’t add real value.
There’s a huge difference between using an LLM to crank out test code and having a product that can actually support complex, evolving setups long-term. A lot of tools work great in demos but don’t hold up for these real-world testing needs.
And yeah, this is even trickier for higher-level tests. Without careful design, it’s way too easy to end up with “dumb” tests that add little real value.
We used to place a can of spam on the tank's gearbox before a long drive, and by the time we reached our destination, the spam was heated up and ready to eat.
DIY only make sense at a very small scale or very large scale, everything in between is usually best offloaded to those which do it as their core competency.