By VM Vaughn I’m 56 years old and learning to code. Why? Because I love it. And I’ve got a knack for it. That doesn’t mean it’s easy. It’s hard. And that’s OK. I love losing myself in an algorithm challenge. I love squeezing in a few extra minutes te...
I Started Programming When I Was 7. I'm 50 Now, and the Thing I Loved Has Changed | James Randall
I still love developing but the shifts that AI have brought are tectonic and are forcing me to re-evaluate my own relationship to building things
Learn to code. Or don't.
Reasons to learn to code: * You have an offer for a job that involves coding, or could benefit from it * Existing tools don’t serve your needs well, or at all * You enjoy it “Learn to code” is the common refrain for what to do when you’re poor. It’
Teach Yourself Programming in Ten Years
The conclusion is that either people are in a big rush to learn about programming, or that programming is somehow fabulously easier to learn than anything else. Felleisen et al. give a nod to this trend in their book How to Design Programs, when they say "Bad programming is easy. Idiots can learn it in 21 days, even if they are dummies." The Abtruse Goose comic also had their take.
Programming as Theory Building: Why Senior Developers Are More Valuable Than Ever
Peter Naur's 1985 theory of programming explains why experience matters more in the age of AI-generated code
Thoughts on thinking
I have been stuck. Every time I sit down to write a blog post, code a feature, or start a project, I come to the same realization: in the context of AI, what I’m doing is a waste of time. It’s horrifying. The fun has been sucked out of the process...
Older Adults Learning Computer Programming: Motivations, Frustrations, and Design Opportunities
Online videos are a promising medium for older adults to learn. Yet, few studies have investigated what, how, and why they learn through online videos. In this study, we investigated older adults’ motivation, watching patterns, and difficulties in using ...
Reflections on a decade of coding
I've been programming professionally for about 12 years. Here are some of the things I worked on in the last 2 years.
Stuck in the middle: Being an engineer & artist in the AI era | Annie Sexton | Offprint
I'm an AI skeptic, through and through. But I also voluntarily use AI nearly every day. So naturally, you might be asking: what the heck?
We asked 15,000 people who they are, and how they’re learning to code
More than 15,000 people responded to the 2016 New Coder Survey, granting researchers an unprecedented glimpse into how adults are learning to code. We’ve released the entire dataset of participants’ individual responses to all 48 questions — under th...
How I’d start my engineering career today
If you could start your engineering career over today, here’s what actually matters now that AI has made most coding skills nearly worthless.
Stop saying learning to code is easy.
(The photo above was taken at the Microsoft NYC office of three amazing young ...
A quote from Andrew Quinn
One could say in the first quarter-century of my life, that while I was always fascinated by programming, I could never overcome the guilt of not really knowing whether the …
On the Value of Doing a PhD in the Age of AI
Many students who are just now embarking on a PhD in AI are understandably anxious. It feels like our field is zooming forward ever faster. Our clever methods are often surpassed before they are published. Our deep insights seem less critical to frontier lab progress. AI is automating aspects of the research process that used to require years of specialized training.
The Friction I Don't Want to Lose
I love learning. And while the friction of solving new problems is increasingly traded for speed, the experience gained by overcoming that friction is as important as ever.
Arvind Narayanan (@aisnakeoil)
There’s a big, under-appreciated reason why people may have very different experiences and opinions about using AI for work — are they using it for tasks they’re already an expert at, or tasks they can’t do themselves? The former leads to a growth cycle and the latter leads to a dependence spiral. When I use AI to do something I’m an expert at, like coding, I treat it as a tool. I can build quickly, maintaining an understanding of the code, knowing that if necessary, I can fix the code myself. It feels empowering. It frees up my time to think about the complex, judgment-oriented parts of software engineering that I can’t or won’t delegate to AI. That means my own skills improve rapidly, and I get to climb the ladder of complexity and develop higher-level skills, much more so than when I write the code myself. I feel in control. I can lock in and achieve a flow state — when AI is working, I’m reviewing, building understanding, and planning the next steps. I never get the feeling that the tool is about to replace me. This is the growth cycle. (Of course, the growth cycle is not automatic. I still need to exercise agency to use AI responsibly. But it’s the same challenge with any productivity-enhancing technology, and those who’ve navigated such transitions before are well-equipped to navigate it with AI as well.) On the other hand, if I use it for tasks I don’t understand and haven’t learned to perform myself, I have no choice but to treat it as a superintelligence. If something breaks, the best I can do is ask AI to fix it and hope for the best. I generally can’t evaluate the quality of the output myself. The only way to find out if it's any good is if and when the work is ultimately reviewed by an actual expert. The experience is confusing, unsettling and disempowering. And forget about flow state. By over-relying on AI, I risk losing whatever skill I had at the task in the first place, even if it boosts productivity in the short term. This is the dependence spiral. It’s no wonder that entry-level workers and students preparing to enter the workforce find themselves in a bind. To compete with the AI-enabled productivity of more seasoned workers, they must adopt AI themselves, but doing so risks the dependence spiral. I have some thoughts on solutions that I will share in later posts, but I think having a clear diagnosis of the problem is a useful first step.
