Side projects are dead

For years, the standard advice for aspiring developers was simple: build side projects. Throw a to-do app on GitHub, make a weather dashboard, clone Twitter. It showed initiative. It proved you could code. Hiring managers loved it. That era is over. AI has collapsed the distance between idea and implementation so dramatically that the side project, as we knew it, no longer carries the weight it once did. When anyone can spin up a functioning app in an afternoon with an LLM, the mere act of building something is no longer a signal of anything.

The signal has been destroyed

Side projects used to work as a hiring signal because they demonstrated a rare combination: initiative, technical skill, and follow-through. Building a project from scratch required real effort. You had to understand the stack, debug obscure errors, and push through the tedious parts. The finished product was proof that you could ship. Now, with AI coding assistants handling everything from scaffolding to debugging, the barrier to producing a working project has dropped to nearly zero. A junior developer and a non-technical founder can produce the same looking output. When everyone can build a CRUD app in a weekend, having one on your GitHub profile tells a recruiter almost nothing. The 2026 hiring landscape reflects this. Recruiters scanning GitHub profiles spend less than a minute before moving on. They've seen hundreds of AI-assisted portfolio projects that all look the same. The signal-to-noise ratio has cratered.

What actually creates leverage now

If side projects in the traditional sense are dead, what replaces them? Two things stand out.

Build something people actually use

The projects that still matter are the ones that solve real problems for other developers or users. Think developer tools, open-source libraries, CLI utilities, things that people star, fork, and depend on. A GitHub repository with thousands of stars is a fundamentally different signal than a portfolio project. It means other developers evaluated your work, found it useful, and chose to adopt it. That's not something AI can fake. Stars represent community validation, and community validation is the new resume bullet point. I built DropDrawer because I needed it. It scratched a real itch. And even in a world where AI can generate boilerplate code in seconds, a tool that people actually reach for still has value. The hard part was never the code itself, it was identifying the problem, designing the right solution, and shipping something worth using. The lesson is straightforward: don't build projects to fill your portfolio. Build tools that fill a gap. If your project has users, that's worth more than any number of tutorial clones.

Start a company

The other path that creates real leverage is entrepreneurship, and AI has made this more accessible than ever. The cost of starting a startup from zero is approaching nothing. AI handles your first draft of code, your marketing copy, your customer support scripts, your data analysis. What used to require a team of five can now be done by a founder with a laptop and a few subscriptions. Reports show that over 78% of companies globally now use AI in at least one core business function, and the tools available to solo founders in 2026 are staggeringly capable. You can prototype in hours, validate in days, and launch in weeks. The barrier isn't technical anymore, it's taste, judgment, and the willingness to talk to customers. A startup you built, even one that failed, tells a hiring manager something powerful. Revenue numbers, user acquisition metrics, churn rates, these are the new differentiators. They show you understand not just how to build, but how to create something people want. That's a fundamentally harder problem than writing code, and it's one AI hasn't solved.

The new hierarchy of proof

Think of it as a ladder of credibility in the AI era:

The gap between levels one and two versus level three has widened enormously. AI compressed the effort required for level three to almost nothing, which means the signal value followed it down.

What this means for your career

If you're early in your career and wondering where to invest your time, stop building throwaway projects. Instead, pick one of two directions. Find a genuine pain point in your workflow or your community's workflow and build a tool that addresses it. Open-source it. Write good documentation. Make it easy to adopt. If it's genuinely useful, the stars and contributors will follow, and that's worth more on your resume than ten portfolio projects combined. Or, take an idea and try to turn it into a real business. The cost is near zero. The tools are better than they've ever been. Even if the startup doesn't work out, the experience of acquiring users, handling payments, and making product decisions will set you apart in ways that no side project ever could. The age of building things just to show you can build things is over. In a world where AI can build anything, the question has shifted from can you build it to should it exist, and can you make people care? That's a much harder question. And it's the only one worth answering.

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