Michael Parenti’s Post

🚨 Many developers learn frameworks… but forget the fundamentals. I recently watched the video #10BasicComputerConceptsYouNeedtoKnow, and it reminded me of something important: Technologies change constantly. But the fundamentals of computer science remain the same. When you truly understand the concepts behind the tools, it becomes much easier to learn any new language or framework. Some core pillars every developer should understand: • Algorithms – how we logically solve problems • Data Structures – organizing data efficiently • Complexity (Big-O) – understanding the cost of solutions • Recursion – breaking complex problems into smaller ones • Abstraction – managing complexity in large systems • Concurrency & Parallelism – running multiple tasks efficiently • Memory & Storage – how data is managed and accessed • Networking – how systems communicate • Distributed Systems – the backbone of modern applications • Security – protecting systems and data 💡 Frameworks come and go. But developers who understand fundamentals can: • learn new technologies faster • solve more complex problems • write more efficient code • make better architectural decisions 📌 Curious to hear from other engineers: Which of these concepts has had the biggest impact on your day-to-day work as a developer? #softwareengineering #programming #computerscience #backend #technology

One mistake many developers make is chasing tools instead of learning fundamentals. Every year there is a new framework. A new library. A new tool promising to solve everything. Many developers keep jumping from one tool to another. But great engineers focus on core fundamentals: • Data structures and algorithms • System design • Networking basics • Databases and query optimization Tools change quickly. The fundamentals behind them stay the same for decades. How to avoid this mistake: • Learn concepts before learning frameworks • Understand how things work under the hood • Choose tools based on problems, not trends Good developers know many tools. Great developers know why and when to use them. #SoftwareEngineering #Programming #Developers #TechCareers #SystemDesign #Coding #BackendDevelopment #SoftwareDevelopment

Many developers eventually reach a point where they feel like they’ve hit a ceiling with a programming language. You know the syntax, the common patterns, and you can build applications without constantly checking documentation. It’s a good place to be — but it can also feel like growth has stopped. In reality, this is usually where the most interesting learning begins. Instead of focusing only on the language itself, it helps to expand in several directions: • Deepen your fundamentals. Study algorithms, data structures, memory management, and complexity. These concepts improve how you write code in any language. • Understand how things work under the hood. Explore compilers, runtimes, networking, databases, and operating systems. This knowledge changes the way you design software. • Learn system design. Think about scalability, reliability, distributed systems, and architecture decisions. • Read other people’s code. Open source projects are a great way to see how experienced engineers structure real systems. • Explore adjacent tools and ecosystems. Frameworks, testing strategies, performance optimization, CI/CD, and observability. • Teach or share knowledge. Writing posts, mentoring, or explaining concepts often reveals gaps in your own understanding. A programming language is just a tool. Mastery comes from understanding the broader engineering landscape around it. Often the “ceiling” is simply the point where learning shifts from syntax to systems thinking. Curious — have you ever felt like you hit a plateau in a language? What helped you move forward? #programming #softwareengineering #developers #coding #techcareers #learning #systemdesign #algorithms #opensource #careergrowth

Most bugs aren’t caused by bad code; they’re caused by unread documentation. Developers often say, “I’ll figure it out as I go,” but this leads to spending hours debugging something explained in the first 10 lines of the README. For instance, I once spent an hour debugging a CORS issue. The solution? A single line in the documentation: enable credentials in the middleware. Documentation isn’t a chore; it’s the quickest way to understand a library. Good documentation provides guidance on how to use the library effectively, what not to do in production, and the trade-offs the authors considered. Instead of guessing or fighting the framework, you align with it. Reading the documentation for 30 minutes often saves 3 days of debugging. It’s not slower; it’s a shortcut. What’s one library whose documentation genuinely improved your engineering skills? #SoftwareEngineering #Documentation #Coding #DevLife #TechHumour #DeveloperLife #AI #Engineering #Productivity #LLM #TechHumour

Most bugs aren’t technical problems. They’re thinking problems. After working on real projects, I noticed something: The issue usually isn’t: • the framework • the language • the database It’s unclear thinking. When requirements are vague → bugs appear. When edge cases aren’t discussed → production breaks. When assumptions aren’t written → teams misalign. The biggest upgrade in my coding wasn’t learning a new stack. It was learning to ask better questions: → What happens if this fails? → What’s the worst-case scenario? → Who depends on this? → How will this behave at scale? Clean thinking produces clean code. The best engineers I’ve seen don’t type faster. They think deeper. What question do you always ask before writing code? #SoftwareEngineering#Coding#Developers#SystemDesign#BuildInPublic

Most bugs aren’t caused by bad code. They’re caused by unread documentation. Developers love to say: “I’ll figure it out as I go.” Until we spend 3 hours debugging something explained in the first 10 lines of the README. I once spent an hour debugging a CORS issue. The fix? One line in the docs: enable credentials in the middleware. Docs aren’t a chore. They’re the fastest path to understanding. Good documentation tells you: - How the library is meant to be used - What not to do in production - The trade-offs the authors already faced So instead of guessing… or fighting the framework… You align with it. 30 minutes reading docs often saves 3 days of debugging. It’s not slower, It’s the shortcut. What’s one library whose documentation genuinely made you a better engineer? #SoftwareEngineering #Documentation #Coding #DevLife #TechHumour #DeveloperLife #AI #Engineering #Productivity #LLM #TechHumor

Frameworks vs Fundamentals — What Makes a Strong Developer? 💻🧠 Modern development is full of powerful frameworks that help build applications faster. But behind every great developer is a strong understanding of core fundamentals like algorithms, data structures, and system design. Frameworks help you build quickly, while fundamentals help you solve complex problems. The best developers know when to rely on tools and when to rely on deep understanding. #Programming #SoftwareDevelopment #DeveloperMindset #Coding #TechCareers #LearnToCode #LinkedInInsights 🚀

The best engineers of each generation shared one trait: they refused to stay at the level they had already mastered. There’s a pattern running through the entire history of software. We keep building layers that let humans think less about how — and more about what. Assembly → C → Python → Rails → Cloud. At every step, the same fear surfaced: “Are we making engineers obsolete?” And every time, the answer turned out to be the same. No. We’re changing what engineers are responsible for. When C replaced assembly, the cognitive load shifted from registers to algorithms. When cloud replaced on-prem infrastructure, the challenge moved from provisioning servers to designing distributed systems. Interestingly, the total complexity engineers managed didn’t decrease. It increased. Because abstraction unlocks the ability to build systems that previously weren’t feasible. Agentic coding follows the exact same pattern. Tools are building a new layer on top of the programming language itself. Natural language becomes a valid programming interface. You describe the behavior of a system. The agent handles large parts of the implementation. Today, that interface is imperfect. Outputs require verification. Context gets lost. Edge cases get missed. Critics see this and conclude the paradigm is fundamentally broken. But early C compilers were notoriously unreliable. Immature tooling has never been a reliable signal that a direction is wrong — only that it’s early. The more interesting question is this: What does the abstraction demand from the humans above it? Agentic coding doesn’t reduce the need for engineering judgment. It raises the stakes for it. When a feature can be scaffolded in minutes instead of days, the bottleneck moves elsewhere: • requirements • system design • deciding what’s worth building at all Engineers who optimized purely for implementation fluency may struggle — knowing syntax cold, writing boilerplate fast. The ones who will thrive are those who can: • define problems precisely • reason about systems end-to-end • recognize when generated output is subtly wrong In other words, the engineers who can think clearly about systems. This is, in many ways, a return to what engineering was always meant to be. The future isn’t less human. It’s more human — just operating at a higher level of abstraction, where the interesting problems actually live 🚀

Stop chasing every new programming language. Every few months, a new framework trends. A new syntax appears. A new “must-learn” stack dominates timelines. Many developers respond by jumping again, switching focus before mastering what they already started. This creates familiarity without competence. Depth beats novelty. A developer who deeply understands one language, its memory model, performance characteristics, ecosystem, architectural patterns, and tooling, can solve complex problems efficiently. That same developer can transition to new technologies faster because the fundamentals are solid. Companies do not hire engineers for the number of languages listed on a résumé. They hire for problem-solving ability, system thinking, and the capacity to deliver reliable solutions. Five shallow languages do not equal one mastered stack. Instead of asking, “What new language should I learn?” Ask, “Have I fully understood the one I already use?” Mastery compounds. Novelty distracts. #codinghq #tech #tip

It’s not every programming language you hear about you will go and learn. Nope, try to master 1 first then you can go for the others, but you must try to master 1 first. Read the post to learn more about this topic