The 100m / 10k analogy is fantastic, but the reality is even worse.
Let’s say you expect a candidate to stay for average five years. That’s about 1200 working days. If you get to interview them for 1 day, then that day is 8.3m to the 10k. You get to watch them run for 8.3m and decide how well they can run the 10k.
Came here to say this!
So many ways to parse it. But the key issue was not knowing that “pregnancy-test frogs” was the central concept. Without that, the headline is so confusing… at some point I had to consider whether “frogs” was being used as a verb
Too much developers relying on bloatware, not enough “implement it yourself” because in reality every hash map doves a unique problem that a Palin hash map is not necessarily suited for. Embrace NIH
You need at least one or two somewhat disagreeable folks in a team. Because without this, groupthink emerges, teams have too much inertia, they follow the assumed norm instead of challenging it for something better, they don’t debate the options enough. That disagreeable energy, in the right dose, leads to better decisions. If you don’t have it naturally, you can encourage someone to “play devil’s advocate” in decision discussions (or do it yourself) and you’ll find sometimes the devil’s advocate is actually right.
Agree - but The Goal (Eliyahu Goldratt) is a rare exception to this. It’s written as a novel but actually contains valuable and counterintuitive lessons about optimizing for efficiency in a complex delivery process. Worth every page
Agree, it's not testing. The problem is here: "In a typical testing workflow, you write some basic tests to check the core functionality. When a bug inevitably shows up—usually after deployment—you go back and add more tests to cover it. This process is reactive, time-consuming, and frankly, a bit tedious."
This is exactly the problem that TDD solves. One of the most compelling reasons for test-first is because "Running the code in your head" does not actually work well in practice, leading to the above-cited issues. This is just another variant of "Running the code in your head" except an LLM is doing it. Strong TDD practices (don't write any code without a test to support it) will close those gaps. It may feel tedious at first but the safety it creates will leave you never wanting to go back.
Where this could be safe and useful: Find gaps in the test-set. Places where the code was never written because there wasn't a test to drive it out. This is one of the hardest parts of TDD, and where LLMs could really help.
I don’t think there’s zero demand recommendation apps, a lot of founders choose this because it’s a problem they want to solve for themselves, and there are a few success stories out there. It’s just that it’s a super-hard problem