mattikl

I've lived all my life in Finland, even though all through my early adulthood I was planning to move to some place much warmer. But later (especially now with children for whom the snow is so exciting) I've come to like the four seasons and the balance it gives.

That article was a strange read from my perspective, because here the infrastructure is built for winters as well. I don't remember school ever being canceled due to winter conditions, traffic is only a mess after a snowstorm.

Don't be afraid to go deep in simple sounding topics. The modern world is so full of learning material that there's the temptation to ingest as much of it as possible, but true learning happens when you give yourself time with one topic at a time. And I'd say this is more important than even, because generative AI is becoming great at precisely generating things, not so in understanding complex topics.

That said, learning the fundamental topics can limit your thinking first if they feel difficult, so it's an interesting question how to keep the naïve creativity of the beginner that's something that can really help when building with AI because there are less limitations in your thinking based on how things used to be.

That's certainly a more positive way to look at this. Working software has always relied on having people who grok the code, and this happens by spending a lot of time thinking about the code while writing it. And it's undocumented, because the nature of it is something you cannot really document.

If AI is writing all the code, how do we keep the quality good? It's so obvious with the current GenAI tools that they're getting great at producing code, but they don't really understand the code.

We don't really know how this story unfolds, so it's good to keep a positive mindset.

When social media emerged, I remember how excited I was how it could connect like-minded people around the world. Now in 2025, the leader of the biggest platforms is talking about making people less lonely by connecting them to AI chatbots instead of making people find one another. That just feels like a huge lost potential.

I've noticed for a long time that if I have participated in writing the code under review, I'm able to provide much more insight. I think what you're suggesting starts from thinking the code as "our code" instead of my code vs. your code, which so easily happens with pull requests. And learning to work iteratively instead of trying to be too perfect from the start, which goes well with methodologies like TDD.

On average, music is big for people during the teenage years, then other things in life take over and that same music continues the biggest music for them.

This is very different if music is a lifelong hobby for you. I'm in my forties and some of the artists I most listen to today I discovered during recent years. Still I find articles like this interesting because I can learn something about a larger demographic while being different myself.

That's interesting. I think it's usually pretty siloed so that people in sports, music or academia/tech are so focused mastering their own field and hang out with likeminded people. Maybe you get combination of two, but three sounds pretty uncommon.

I was just wondering the other day, are any of the top college athletes majoring in something demanding (in a way that it requires one to spend countless of hours learning new mental models) like CS or physics? As a European, my exposure to college sports is pretty limited, but I've never seen a major like that listed.

An interesting read. I was secretly hoping it would have delved more into the psychology of how we perceive that chance, what kind of biases we have. I feel we have a tendency of saying "it never fails" on probabilities which turn out to be much bigger than one in a million.

Thanks for wording this so well. I notice it when a coworker asks for help, I usually have little idea how to help them when looking at the problem together, unless it's something obvious. But when I look at the code by myself, my mind is somehow free to explore it in "the natural way", and the answers may come quickly.

It's so easy to lose focus when reading code just for learning. Writing about that code is a good way to keep the focus and dig deeper.

Direct reading effectively makes the data store an API, i.e. the API you provide is SQL SELECT over multiple tables instead of HTTP GET resource.

This pretty much freezes the database schema, the team owning it can no longer change it, because they don't know how the users use it. It also limits the possibilities to provide optimizations on the data (like caching).

I've also lost interest many times during my 25 years of coding, but now I feel excited as ever again.

One of key realizations has been that I'm more interested in people than machines (even though I feel the same fascination figuring out how something works). In the end, software is almost always for people to use. Things like programming language design easily get regarded as highly technical, but it's so much about creating abstractions for humans to create abstractions for humans.

Another one has been learning how software fits the bigger picture. In order for a company to succeed with software, things starting from vision, strategy, execution need to be in line. What I'm trying to say that it's important to notice when the development of software gets blamed for problems elsewhere. Otherwise our view of the development itself gets murkier.

Finally, learning new languages is something that's keeping it fresh for me. Making the effort to dig deeper and learn something complex I didn't know well before.