The Reality Check: When "Just Build Things" Meets Actual Building
You've heard it everywhere—from senior developers on YouTube to Reddit threads with thousands of upvotes. "Just build projects!" they say. "That's how you really learn." It sounds so simple, so obvious. As a third-year computer science student in 2026, I took this advice to heart. After finishing a Python course, I decided to build my first non-tutorial project: a web scraper that would collect apartment listings and notify me when something matched my filters. Seemed reasonable enough. I had no idea what I was about to walk into.
Those first two hours? Pure frustration. And that's when I understood why "just build things" is often terrible advice for beginners. It's not that building projects is bad—it's essential. But the advice misses all the crucial context about how to build, what to build, and when you're ready to build independently. This article explores what that Reddit discussion revealed about the gap between tutorial completion and independent development, and how to bridge it effectively.
The Tutorial-to-Project Chasm: Why You're More Lost Than You Expected
Here's the uncomfortable truth most tutorials don't mention: following instructions and creating something from scratch are fundamentally different skills. When you're working through a tutorial, you're essentially tracing over someone else's drawing. You learn the motions, but not the decision-making process behind each stroke.
Take my apartment scraper idea. In a tutorial, I'd be told exactly which libraries to use—probably BeautifulSoup or Scrapy. I'd get step-by-step instructions on parsing HTML, handling pagination, and storing data. But on my own? I spent the first hour just trying to figure out which scraping approach made sense for my specific use case. Should I use requests + BeautifulSoup? Selenium for JavaScript-heavy sites? Maybe Puppeteer? Each choice had implications I didn't understand.
And that's the core issue. Tutorials teach you implementation but rarely teach you evaluation. They don't show you how to research options, compare trade-offs, or make architectural decisions. When you're suddenly responsible for all those decisions yourself, it feels like you've been thrown into deep water after only learning to swim in a wading pool.
The Hidden Complexity of "Simple" Projects
What seems simple on the surface often hides layers of complexity that tutorials conveniently avoid. My "simple" apartment scraper quickly revealed at least five major challenges I hadn't anticipated:
First, websites actively try to prevent scraping. I hit rate limits within minutes. Then I encountered CAPTCHAs. Then I discovered that the site loaded content dynamically with JavaScript—my basic requests weren't getting the actual listings. Each of these problems required research, experimentation, and often learning entirely new concepts.
Second, data structure decisions matter more than I realized. Should I store everything in a CSV file? A SQLite database? Maybe JSON files? Each choice had implications for how I'd query the data later, and I didn't have enough experience to anticipate my future needs.
Third, error handling is everything. In tutorials, everything works perfectly. In reality, network requests fail, websites change their structure, data formats are inconsistent. Writing code that handles these failures gracefully is a skill of its own—one I hadn't practiced at all.
Fourth, scheduling and automation presented another hurdle. Should this run continuously? How often? Where would it run? My laptop couldn't stay on 24/7, so I needed to learn about cloud services, cron jobs, or serverless functions.
Fifth, and most importantly, I had no idea how to break this project down into manageable pieces. I was staring at a mountain with no visible path up.
The Missing Middle: What Comes After Tutorials but Before Full Projects
The Reddit discussion revealed a crucial insight: there's a missing step between tutorials and independent projects. Most learners jump directly from one to the other, and that's why they struggle so much. Here's what should come in between:
Modified Tutorials: Instead of building something completely new, take an existing tutorial project and modify it significantly. Change the data source, add features, or combine two tutorial projects. This gives you practice modifying existing code before creating from scratch.
Micro-Projects: Build something so small it can be completed in 2-3 hours maximum. The goal isn't to create something useful, but to practice the complete development cycle on a tiny scale. Think "command-line calculator" not "full web application."
Code-Alongs with Variations: Follow a tutorial, but deliberately choose different tools or approaches than the instructor. Compare your results. This builds decision-making skills in a controlled environment.
Debugging Practice: Intentionally break working code from tutorials and practice fixing it. This develops problem-solving skills that are crucial for independent work.
The key is gradual progression, not sudden leaps. You wouldn't expect someone to run a marathon after learning to walk—why do we expect programmers to build complete applications after following a few tutorials?
The Planning Gap: Why "Just Start Coding" Is Terrible Advice
Another critical insight from the discussion: beginners don't know how to plan software projects. When experienced developers say "just build things," they're skipping over years of accumulated planning skills they take for granted.
Here's what planning actually looks like for that apartment scraper:
First, I needed to define success criteria. What exactly should the scraper do? "Find apartments" is too vague. Better: "Check three specific websites every 6 hours, extract price, location, square footage, and contact information, filter based on my criteria, and send an email notification for matches."
Second, research phase. What tools exist for this? What are their limitations? What's the simplest approach that could possibly work? This might mean starting with a single website before adding others, or using a no-code tool initially.
Third, breaking it down. The full project might include: website research, HTML structure analysis, request handling, data parsing, data storage, filtering logic, notification system, error handling, and deployment. Each of these can be tackled separately.
Fourth, prioritizing. What's the minimum viable product? Probably: scrape one site, print results to console. Then add storage. Then add filtering. Then add notifications. Then add more sites. This iterative approach prevents overwhelm.
Without this planning framework—which tutorials never teach—beginners stare at a blank editor with no idea where to begin. They either give up or start coding randomly, which leads to messy, unmaintainable code that eventually collapses under its own weight.
Practical Bridge Projects: What to Build After Tutorials
So what should you build after finishing tutorials? Based on the Reddit discussion and my own experience, here are specific project ideas that bridge the gap effectively:
The Enhanced Tutorial Project: Take the last tutorial you completed and add three meaningful features. If you built a todo app, add user accounts, due dates, and email reminders. You're building on familiar foundation while practicing extension.
The Documentation-Based Project: Choose a library you know from tutorials, read its official documentation, and build something using features the tutorials didn't cover. This practices learning from primary sources rather than filtered tutorials.
The API Integration Project: Find a public API (Twitter, Weather, GitHub, etc.) and build something that uses it. Start by just fetching and displaying data, then add processing, then add a simple interface. APIs provide clear boundaries that make projects more manageable.
The Automation Script: Automate something in your own life that takes 5-10 minutes daily. File organization, data backup, social media posting—anything. These projects have clear, personal value and natural stopping points.
The "Frankenstein" Project: Combine code from 2-3 different tutorials into something new. This teaches you how to integrate disparate pieces—a crucial real-world skill.
Notice what these have in common: they're constrained, they build on existing knowledge, and they have natural progression points. They're not "build whatever you want"—they're structured challenges that develop specific skills.
When to Use Tools vs. Building From Scratch
One of the biggest realizations from my scraper project: sometimes, you shouldn't build it yourself. As beginners, we often think we need to implement everything from scratch to "really learn." But in 2026, that's increasingly unrealistic and inefficient.
For web scraping specifically, platforms like Apify handle the infrastructure headaches—proxy rotation, CAPTCHA solving, browser automation, scheduling. Using such a tool doesn't mean you're cheating; it means you're making an architectural decision to focus on what matters for your project.
The key question: what do you actually need to learn? If your goal is to understand web scraping fundamentals, building from scratch makes sense. If your goal is to get apartment listings, using existing tools might be better. And if you're somewhere in between, you could use a tool like Apify while still writing your own filtering and notification logic.
This applies broadly. Building a full authentication system from scratch teaches you about security, but using OAuth or a service like Auth0 might be better for an actual project. Building a database engine teaches you about data structures, but using PostgreSQL is better for most applications.
The skill isn't building everything—it's knowing what to build and what to use. Tutorials rarely teach this balance.
Common Mistakes and How to Avoid Them
Looking back at my failed scraper attempt and reading hundreds of similar stories on Reddit, certain patterns emerge. Here are the most common mistakes beginners make when transitioning from tutorials to projects, and how to avoid them:
Mistake 1: Scope Creep Before Starting. You begin with "simple scraper" and soon you're planning machine learning to predict rent prices. Solution: Define your MVP (Minimum Viable Product) in writing before writing any code. Be brutally specific about what's included in version 1.
Mistake 2: No Error Handling Plan. You assume everything will work perfectly. Solution: As you plan each component, ask "what could fail here?" and plan for at least the most common failures.
Mistake 3: Research Paralysis. You spend days comparing tools without writing any code. Solution: Set a time limit for research (2-4 hours), then pick the best option and start. You can always change later.
Mistake 4: Ignoring Deployment. You build something that only works on your machine. Solution: Consider deployment from day one. If it needs to run continuously, where will it run? Answer this early.
Mistake 5: Solo Struggle. You hit a wall and spend days stuck instead of asking for help. Solution: Set a rule: if you're stuck for more than 2 hours, ask for help. Stack Overflow, Discord communities, or even hiring a mentor for an hour on Fiverr can save you weeks of frustration.
Mistake 6: No Version Control. You make changes that break everything with no way back. Solution: Use Git from the very beginning, even for tiny projects. Commit after each working step.
The Mindset Shift: From Tutorial Consumer to Independent Developer
The hardest part of moving beyond tutorials isn't technical—it's psychological. You need to shift from a consumer mindset to a creator mindset. Tutorials are consumption: you follow, you absorb, you replicate. Independent development is creation: you envision, you plan, you build, you debug, you refine.
This shift requires tolerating ambiguity. Tutorials have right answers. Independent projects have multiple possible approaches, each with trade-offs. You need to become comfortable making decisions with incomplete information—and revising those decisions later when you learn more.
It also requires embracing failure as data, not defeat. When my scraper failed to handle JavaScript rendering, that wasn't a sign I should quit. It was data point: "I need to learn about dynamic content loading." Each failure teaches you what you don't know, which tells you what to learn next.
Most importantly, it requires patience with yourself. That Reddit poster felt frustrated after two hours. I felt overwhelmed after a day. But independent development is a skill that develops gradually. Your first project might take a month and be full of bad code. Your tenth will take a week and be much better. The learning happens in the struggle.
Resources That Actually Help (Beyond "Just Build")
If "just build projects" is insufficient advice, what should you actually do? Based on the most helpful responses in that Reddit thread and my own experience, here are concrete resources and approaches:
Project-Based Books: Books like Automate the Boring Stuff with Python provide structured projects with explanation of the decision-making process, not just implementation steps.
Code Review Platforms: Sites where you can submit your code for review by experienced developers. You learn not just whether your code works, but why certain approaches are better than others.
Open Source Contribution Guides: Many projects have "good first issue" labels with detailed instructions. This gives you practice working with existing codebases—a crucial real-world skill.
Pair Programming: Working with someone slightly more experienced than you. You see how they approach problems, ask questions, and get immediate feedback.
Project Templates: Starting with a basic template (like a simple web app skeleton) and extending it. This gives you structure without being a full tutorial.
Build Logs/Development Diaries: Reading about other people's project journeys, including their mistakes and course corrections. You learn the process, not just the outcome.
Conclusion: Better Advice for 2026
So what's better than "just build projects"? Based on everything I learned from my failed scraper and that revealing Reddit discussion, here's more nuanced advice for beginners in 2026:
Start with modified tutorials, not completely original projects. Choose projects with natural constraints—APIs, specific requirements, or limited scope. Plan before you code, even if just a bullet-point list. Embrace tools when they let you focus on learning what matters. Expect to be lost—that's normal, not failure. Seek help early, not as last resort. And most importantly, view each project as practice for the process of development, not just production of a working application.
The goal isn't to avoid building projects—it's to build them in a way that actually develops your skills rather than reinforcing frustration. That apartment scraper? I eventually built a simpler version that worked for one website. It was ugly, broke often, and only I could use it. But I learned more from that imperfect, struggling project than from a dozen polished tutorials. The difference was approaching it with realistic expectations and a structured process, not just "building things" and hoping for the best.
In 2026, with more learning resources than ever, the challenge isn't finding information—it's knowing how to use it to bridge the gap between tutorial consumer and independent developer. And that begins with recognizing that "just build things" is the beginning of the conversation, not the complete answer.
