#Software-Development
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The End of Programming as We Know It
The article argues that AI will not replace programmers, but it will change programming into higher-level work, while creating new demand, new skills, and new roles around AI systems.
10 hot programming trends — and 10 going cold
The article pairs rising and fading programming approaches, arguing that cost, safety, privacy, and workflow are shifting interest from clouds, C/C++, REST, and SPAs toward Rust, Wasm, GraphQL, static site generators, and more.
If You Want to Get in the Tech Space: Become A Software Developer
The article argues that software development remains in demand despite AI tools and layoffs, and says the path in starts with computer science knowledge and practical projects.
Become a Better Programmer: 7 Habits to Grow
The article says better programming comes from strong basics, deliberate problem-solving, clean code, debugging, documentation, networking, and building real projects.
From Chaos to Efficiency: How to Minimize Distractions in Software Development
The page argues that software developers need time management, focus blocks, clear boundaries, automation, and regular adjustment to reduce interruptions, protect quality, and limit task buildup.
Why We've Tried to Replace Developers Every Decade
The article traces fifty years of attempts to make software creation simple enough to need fewer developers, and argues that the real limit is the complexity of the work, not the tool.
The Art of Finishing | ByteDrum
The post argues that unfinished projects keep offering possibility, but finishing builds skill, reduces mental clutter, and brings feedback, satisfaction, and professional value.
What I believe about the future of software development
Thorsten Ball argues that models will shift software work from coding and review to system design, product judgment, and token-driven workflows, while many current tools, roles, and habits fade.
3 software development principles I wish I knew earlier in my career
The article presents YAGNI, KISS, and DRY as practical principles that shape how software is written and shipped, helping code stay focused, readable, and easier to maintain.
Software Developer vs. Software Engineer: Important Differences to Consider
The page says both jobs are in high demand, but software engineers work more broadly, collaborate more, and usually earn more, while software developers focus more on building and testing applications.
Code Review: A New Developer’s Guide
The article explains how new developers can write clearer pull requests, test code like users, and give feedback carefully so code review helps the team improve software and grow together.
You Can Grow Your Developer Intuition
The page argues that software development depends on intuition as much as analysis, and that developers can strengthen it through code review, pattern recognition, practice, and reflection.
AI Coding Degrades: Silent Failures Emerge
The author says AI coding assistants have plateaued in 2025 and now fail more quietly, often producing code that runs but gives wrong results. He links this to training on user-accepted outputs.
Why Scrum is Stressing You Out
The post argues that Scrum sprints create constant medium-level stress, reduce autonomy, leave little room for preparation, and often turn into a hybrid process that adds a looming release deadline.
Changed my mind: AI is actually good for coding
The author says AI coding tools help with repetitive work, are most useful in the hands of experienced developers, and are already creating real business and training concerns.
How I use AI agents to write code
The author says AI agents are useful when paired with project guidance, tests, plan mode, and repeated review loops, even if they still make common mistakes and feel frustrating.
A high-velocity style of software development
The article argues for coding as a fast, iterative experiment: write code early, keep mock data nearby, restart often, favor consistency, and use composable functions and clean workspaces to shorten feedback loops.
LLMs bring new nature of abstraction
The article argues that LLMs change software development as much as the move from assembler to high-level languages, but also add non-determinism, so programming becomes a different kind of interaction with the machine.
The myth of software time estimations
The article argues that software time estimates are unreliable because development is inherently unpredictable, and says teams should avoid deadlines in favor of difficulty estimates and Kanban.
What the Team Behind Cursor Knows About the Future of Code
Cursor’s team argues that code work is shifting from typing in an IDE to directing and reviewing AI agents, with planning, model choice, and long-running workflows becoming central.
The most valuable skill in 2026 isn't writing code. It is deleting it.
The text argues that AI makes creation cheap but maintenance costly, so senior engineering is shifting toward removing code, shrinking complexity, and curating systems instead of adding more.
The obligation of a software developer
The text argues that software quality depends on technical choices and attitude: seeking the best solution, testing the code, knowing how to say no, respecting the team, doing constructive code review, and mentoring colleagues.
How Do You Know A Developer Is Doing A Good Job?
The text argues that developer evaluation is hard because the value of a single developer is difficult to measure directly. It says managers end up making subjective judgments, and that easy quantitative metrics often reward the wrong behavior.
3 Harmful Beliefs That Destroy Software Developers Careers
The text points to three beliefs that hurt the careers of developers: trying to learn all languages, confusing long hours with productivity, and ignoring networking.
Part 2: Design Principles in Software Development
A page presents five software design principles, explaining how abstractions, separation of responsibilities, and reducing duplication help keep code cleaner, easier to maintain, and easier to extend.
You Will Suck at Blogging, but That's OK!
The author says beginners should expect to write badly at first, because improvement comes from practice. He uses coding and blogging experiences to show that repetition matters more than perfection.
The 66% Problem
The text argues that AI assistants write code that is “almost right,” but hard to debug, creating new bugs and a deceptive sense of productivity.
Why AI Can't Replace Developers: The Real Limits of AI in Coding
The text argues that AI helps with repetitive and simple tasks, but fails at context, reasoning and debugging complex problems; therefore, it should be treated as an assistant.
The Remote Developer's Toolkit: 10 Must-Have Apps and Software for Working from Home
The page lists ten tools for remote developers, from note-taking and launching apps to pair programming, whiteboarding, cloud dev environments, and async video updates.
Lessons learned in 35 years of making software
Jim Grey says 35 years in software taught him lessons about simplicity, frequent delivery, visibility, networking, willingness to learn, and focusing on relationships and power.
One Div Zero
A humorous yak-shaving creed casts the programmer and the yak as mutual obstacles to shipping, where effort shifts from useful work to endlessly removing the hair that keeps release blocked.
Why you can't be a good .NET developer
The post argues that developers leave .NET to escape teams and shops that choose tools and practices for the least capable members, which blocks progress and pushes people elsewhere.
After two years of vibecoding, I'm back to writing by hand
Mo Bitar traces two years of AI coding through excitement, spec docs, and what he calls slop, and explains why he went back to writing most of his code by hand.
Code is cheap. Show me the talk.
Kailash Nadh argues LLMs made code abundant and cheap, so accountability, provenance, and the ability to think and articulate now matter more than the code itself.
Probabilistic engineering and the 24-7 employee
Software is shifting from deterministic code to probabilistic engineering, where generation is cheap, validation is scarce, and teams must reorganize around agent fleets, selection, and review.
Accept Data In, Be Strict Going Out
00:30:38 — Accept Data In, Be Strict Going Out
Patterns and Principles Over Syntax Details
00:09:46 — Patterns and Principles Over Syntax Details
Great Developers Build Sustainable Readable Systems
00:11:28 — Great Developers Build Sustainable Readable Systems
Code Is Communication: Humans First, Machines Second
00:08:48 — Code Is Communication: Humans First, Machines Second
Knowledge creates technical debt
Technical debt can arise when new knowledge makes an older code path look inferior. The post frames fixing it as using that knowledge well, not just paying off a liability.