Expert Beginner Recap In my last post I introduced the term “Expert Beginner” to describe someone who has capped out in their learning at some sort of local maximum, convinced that the local is global. Expert Beginners are developers who do not understand enough of the big picture to understand that they aren’t actually experts....
How Developers Stop Learning: Rise of the Expert Beginner - DaedTech
In this post, I describe the phenomenon of the so-called expert beginner -- someone with mediocre skill who thinks he's an expert.
Motivating Adult Learners by Introducing Programming Concepts with Scratch
Novice programmers usually fail to combine abstract concepts and knowledge into program design, even though they know the syntax and semantics of individual statement. Adult novice programmers with little computer background knowledge might face more ...
Eight Habits of Expert Software Designers: An Illustrated Guide
The best designers employ specific habits, learned practices, and observed principles when they work. Here are a few of them.
The traits of a proficient programmer
Bridging the gap between competence and proficiency
Local-First Software: Origins And Evolution
Developer interest in local-first software is continuing to grow rapidly in 2024. At the same time, it’s also apparent that developers currently have different views on what they consider to be ‘local-first software’, ranging from narrower to broader definitions. This prompted us to take a closer look at the origins and evolution of local-first.
Expert Generalists
Being an Expert Generalist should be treated as a first-class skill, one that can be assessed and taught.
Leveling Up: Career Advancement for Software Developers | Peter Lyons
Staff Engineer, Back End
The Applied Machine Learning Collective of the Rockies
We're building a hands-on, community-led space where AI/ML practitioners actually grow together. A modern guild where newcomers learn from journeymen, journeymen sharpen their skills alongside experts, and everyone works on real problems that matter.
The Local Relational Technologist
Who can we rely on for meaningful software in our communities?
Redefining the Software Engineering Profession for AI
"How do you train someone to verify work in fields they haven’t mastered, when the AI itself prevents them from developing mastery?"
How Do Individual Contributors Get Stuck? A Primer
Technology, startups, programming, technical management and software architecture
My 4-Stage System for Learning Anything New - Forte Labs
Discover the systematic approach that turns curiosity into expertise through immersion, building, mentorship, and community.
Habits of High-Functioning Teams
I often struggle to explain what it means to be part of a high-functioning software team. Sure, there are mountains of literature, and an entire genre of LinkedIn thought leadership that professes all kinds of guidelines and heuristics about what makes teams work, but in my experience, it’s hard to internalize these ideas and follow someone else’s model if you’ve never seen what good looks like.
Software Developers Should Have Sysadmin Experience
The differences between system administrators and software developers as well as why all software developers should have some amount of sysadmin experience.
AI Skills with Matt Pocock
What do professional software developers need to know to succeed in an age of Artificial Intelligence?
Generative AI is showing early evidence of productivity gains for software developers, but concerns persist regarding workforce disruption and deskilling. We describe our research with 21 developers at the cutting edge of using AI, summarizing 12 of their work goals we uncovered, together with 75 associated tasks and the skills & knowledge for each, illustrating how developers use AI at work. From all of these, we distilled our findings in the form of 5 insights. We found that the skills & knowledge to be a successful AI-enhanced developer are organized into four domains (using Generative AI effectively, core software engineering, adjacent engineering, and adjacent non-engineering) deployed at critical junctures throughout a 6-step task workflow. In order to "future proof" developers for this age of AI, on-the-job learning initiatives and computer science degree programs will need to target both "soft" skills and the technical skills & knowledge in all four domains to reskill, upskill and safeguard against deskilling.
