Skills for programmers that are so much more important than any language, library, or framework
The traits of a proficient programmer
Bridging the gap between competence and proficiency
Small Programming Tricks
A lot of effective engineering comes from the accumulation of small nuggets of knowledge.
How To Think Like A Programmer
How AI Impacts Skill Formation
AI assistance produces significant productivity gains across professional domains, particularly for novice workers. Yet how this assistance affects the development of skills required to effectively supervise AI remains unclear. Novice workers who rely heavily on AI to complete unfamiliar tasks may compromise their own skill acquisition in the process. We conduct randomized experiments to study how developers gained mastery of a new asynchronous programming library with and without the assistance of AI. We find that AI use impairs conceptual understanding, code reading, and debugging abilities, without delivering significant efficiency gains on average. Participants who fully delegated coding tasks showed some productivity improvements, but at the cost of learning the library. We identify six distinct AI interaction patterns, three of which involve cognitive engagement and preserve learning outcomes even when participants receive AI assistance. Our findings suggest that AI-enhanced productivity is not a shortcut to competence and AI assistance should be carefully adopted into workflows to preserve skill formation -- particularly in safety-critical domains.
How AI Impacts Skill Formation
AI assistance produces significant productivity gains across professional domains, particularly for novice workers. Yet how this assistance affects the development of skills required to effectively supervise AI remains unclear. Novice workers who rely heavily on AI to complete unfamiliar tasks may compromise their own skill acquisition in the process. We conduct randomized experiments to study how developers gained mastery of a new asynchronous programming library with and without the assistance of AI. We find that AI use impairs conceptual understanding, code reading, and debugging abilities, without delivering significant efficiency gains on average. Participants who fully delegated coding tasks showed some productivity improvements, but at the cost of learning the library. We identify six distinct AI interaction patterns, three of which involve cognitive engagement and preserve learning outcomes even when participants receive AI assistance. Our findings suggest that AI-enhanced productivity is not a shortcut to competence and AI assistance should be carefully adopted into workflows to preserve skill formation -- particularly in safety-critical domains.
Becoming a dramatically better programmer - Henry @ RC S1
In our first week, we were told that the RC faculty wanted to do one thing above else – to remove any obstacles in the way of us becoming dramatically better programmers.
“I am not a programmer” | Teleogistic
Spend a few minutes in a place where software users interact with software developers – support forums, dev trackers, face-to-face team meetings – and you’re bound to hear this phrase used (or one of its relatives: I am not [a geek|a developer|a coder|tech-savvy], etc). It’s a statement of fact, and a useful statement at that, since the kind of help offered to a “programmer” is obviously quite different from what’s offered to someone who’s not.
Less is more, more or less
In the age of AI, knowing what not to build might be the most important skill of all.
Learnable Programming
Here's a trick question: How do we get people to understand programming?
Programming principles for self taught front-end developers
The majority of us are a bunch of self taught people with rather spotty knowledge and that's fine! Kilian (also self taught) is here to share some of the computer science fundamentals you probably are missing with the aim to improve your code in the long term.
Learning to code is overrated: An accomplished programmer would rather his kids learn to read and reason
Mayor de Blasio is winning widespread praise for his recent promise that, within 10 years, all of New York City’s public schoolchildren will take computer science classes. But as a career programmer who founded two successful software…
The peril of laziness lost | The Observation Deck
In his classic Programming Perl — affectionately known to a generation of technologists as "the Camel Book" — Larry Wall famously wrote of the three virtues of a programmer as laziness, impatience, and hubris: If we’re going to talk about good software design, we have to talk about Laziness, Impatience, and Hubris, the basis of good software design. We’ve all fallen into the trap of using cut-and-paste when we should have defined a higher-level abstraction, if only just a loop or subroutine. To be sure, some folks have gone to the opposite extreme of defining ever-growing mounds of higher level abstractions when they should have used cut-and-paste. Generally, though, most of us need to think about using more abstraction rather than less.
”The distinction between programmer and user is reinforced and maintained by a tech industry that benefits from a population rendered computationally passive. If we accept and adopt the role of less agency, we then make it harder for ourselves to come into more agency.”
always-already-programming.md
gist.github.com