Over the last few years, AI-assisted development, or what some of us call “vibe coding”, has unlocked new ways to think about software creation. For designers, product strategists, or solo builders, AI can feel like an always-on co-pilot: ready to explain things, scaffold features, and offer suggestions at any hour. At its best, vibe coding is about pairing your ideas with an AI like ChatGPT to quickly prototype, test, and evolve your thinking. It’s a fantastic way to build momentum, especially on small tools and side projects. But let’s be clear: AI is a boost, not a replacement for real product development.
This post is a reflection on how vibe coding has sharpened my design skills, expanded my technical thinking, and taught me where its limits really lie, particularly when building something meant to scale.
Why Vibe Coding Works (Especially for Small Stuff)
Fast Prototypes
AI dramatically lowers the barrier to entry. You can go from idea to working prototype in hours. I’ve used it to spin up internal tools, validate SaaS concepts, and try out UI ideas before committing to a direction. It encourages speed and experimentation, without needing to know everything upfront.
Learning by Building
I’ve learned more about components, architecture, and state management by doing short, focused spikes than I ever did watching videos. The act of building (and then rebuilding) helps reinforce foundational concepts.
Sharper Design Thinking
Designing with code in mind has made me more aware of edge cases, trade-offs, and implementation challenges. I’m writing better documentation, spotting UX risks earlier, and having more productive conversations with engineers.
Where It Starts to Break Down
AI can help you move fast—but only within a narrow lane. Once your project starts growing in complexity, things shift.
You still need a team.
Successful apps aren’t just the result of code. They come from clear strategy, thoughtful design, rigorous engineering, and consistent delivery. That means:
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Product strategists who align the app with real business goals
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Designers who craft usable, elegant experiences
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Engineers who think about performance, accessibility, and test coverage
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Delivery leads who keep everyone aligned and shipping
AI doesn’t replace these roles. It can support them, but only within the guardrails that real people create and maintain together.
You can’t skip the process.
Jumping straight into coding without research, planning, or architecture is tempting, however it leads to brittle, short-sighted software. Real projects need structure. Things like user interviews, journey maps, and backlog refinement exist for a reason. They give your work context and direction.
It will break (a lot).
AI makes confident guesses. Sometimes those guesses are wrong. Bad code, broken syntax, incomplete logic are all part of the package. The real skill is knowing how to debug, recover, and move forward. And that comes from experience, not shortcuts.
Best Practices for Solo or AI-Powered Projects
If you’re building something on your own with AI, these habits can help:
1. Start with a context.md.
Before writing any code, write a short document that outlines:
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Your project’s goals
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The audience and technical constraints
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Preferred tools, frameworks, and design systems
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Any naming conventions or key workflows
It doesn’t need to be long. But it does need to be clear. This becomes your north star when the details start piling up.
Meta Pro-tip: Use another AI to help organize your context.md document. Give it a brain dump of everything you know, ask it to interview you one question at at time to fill in the gaps.
2. Use a fresh AI chat for each feature.
Don’t build your whole app in one endless AI thread. Open a new conversation for each component or workflow. Drop in your updated context at the top. It keeps things clean, focused, and easier to troubleshoot later.
3. Keep features small and questions specific.
Vague requests lead to vague answers. Don’t ask, “How do I build an app?” Instead, try, “How do I build a 3-step onboarding flow in React with page transitions?” The more specific you are, the more useful the output.
4. Ask for patterns, not just code.
If you’re learning, treat AI like a mentor. Ask:
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What’s a good file structure for this stack?
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How do devs typically handle X?
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What should I consider when choosing between Y and Z?
Then follow up with deeper questions as your understanding grows.
5. Use Git (and break stuff on purpose).
Get comfortable with Git. Use branches. Commit often. Ask AI to walk you through anything that confuses you. When things break (they will) it becomes part of your learning cycle, not a blocker.
Extra Habits That Help
Test As You Go
You don’t need full coverage, but try scaffolding a few unit tests. Ask AI to help. You’ll learn how to think more defensively, which helps in debugging later.
Click Around Often
Test your app frequently. Don’t wait for “done” before checking the experience. Small gaps in logic or UX often become obvious just by clicking through.
Use Real Tools
Build in a real environment. Use your text editor, terminal, browser console, Firebase dashboard or whatever tools your future users (or team) would rely on. Avoid the temptation to stay in AI sandboxes.
Ask for Feedback
Even if you’re solo, share your progress. A quick code or UX review from a friend, mentor, or online community can surface blind spots before they become real problems.
AI is a superpower, not a replacement (yet?).
AI is making the line between design and development blur in exciting ways. Designers are coding more. Developers are designing better. The cross-pollination is real and promises a bright future for building products!
But meaningful software still comes from collaboration. It still benefits from process, research, structure, and expert perspective. AI can accelerate the journey. But it can’t define the destination, or keep a growing app sustainable over time.
So go ahead and vibe code. Spin up that side project. Build the tool you’ve been imagining. Just remember: speed is exciting, but substance is essential.
And keep your Git branch clean.