A new era of coding has begun—well, technically, it started a while ago, but only now is it getting a name: Vibe Coding. You’ve probably seen the memes floating around or caught some hot takes from the Y Combinator crew and other tech outlets.
If you’ve been living under a rock, here’s the deal: Vibe Coding is all about prompt-driven development using AI-powered tools like Cursor or Replit. Instead of painstakingly writing every line of code, you describe what you want to build in plain language, and the AI generates the actual code for you. Your job? Direct, refine, and polish the AI’s output—while focusing on the bigger picture.
Now that we’re on the same page about what Vibe Coding is, let’s talk about why this matters—really matters—for how we build products. This isn’t just another productivity hack; it’s a fundamental shift in how ideas move from our brains into the real world.
As product people, our job has always been to design, prototype, validate, and iterate—but the friction between thinking and building has always been there. You know how it goes: you have a brilliant idea at 2 AM, but by the time you’ve fought with CSS, wrestled with your framework, or debugged some obscure error, the magic is gone.
Vibe Coding smashes through that barrier. Suddenly, we can prototype at the speed of thought. Need a landing page to test demand? Done by lunch. Want to tweak your entire UX flow? Try three versions before dinner. The implications go way beyond just building MVVs—this changes how quickly we can learn, adapt, and scale ideas that actually work.
I’ve been living this since I first tried Cursor in 2024. At first, it felt like cheating—until I realized this is just how building works now. I’ve launched multiple AI-coded sites that are live and running smoothly. But my real “aha” moment came when I built bodocs.co.za in Q1 2025 as a stress test: Could I go from zero to a functioning micro-SaaS using mostly AI? The answer was a resounding yes.
These days, Cursor is my daily driver for client work. The difference is night and day:
- Landing pages that used to take days? Now shipped in hours
- Product prototypes that required weeks of dev time? Ready for user testing tomorrow
- Those “wouldn’t it be cool if…” features? Actually getting built instead of rotting in Figma
But here’s the real kicker—it’s not just about doing the same work faster. It’s about doing better work. When the busywork melts away, we can focus on what actually matters: solving real problems, crafting better experiences, and iterating based on what users actually needrather than what was feasible to build.
So what does this mean for traditional product workflows?
Processes like the Design Sprint or the Double Diamond design framework, wireframing in Figma, and meticulous prototyping have been gospel for years—but now, with AI, we can skip straight to high-fidelity, functional prototypes in record time. Does that mean we should ditch design tools altogether? Just prompt our way to polished products and throw Figma out the window?
Well… yes and no.
If you’re not using AI in your workflow today, you’re leaving massive productivity gains on the table—plain and simple. But that doesn’t mean you should hand the reins entirely to the machines.
Here’s the reality: AI is powerful, but it’s not infallible. It can be like a drunk toddler—overconfident, erratic, and occasionally convinced it’s doing brilliant work when it’s actually spiraling into nonsense. (If you’ve seen those AI-generated videos where faces melt into the void like a tequila-fueled nightmare, you know exactly what I mean.)
The key is balance.
- Use AI to accelerate the boring parts—coding boilerplate, generating UI variations, or spinning up quick prototypes.
- Stay firmly in the driver’s seat for critical thinking, user empathy, and intentional design.
- Treat AI like a hyper-talented intern: Give it direction, check its work, and course-correct when it veers off track.
Figma isn’t dead—but its role is evolving. Instead of laboring over static mockups, we can invest that time in real, interactive prototypes faster than ever. The frameworks aren’t obsolete; they’re just getting a turbocharger.
Yes, we can now spin up entire websites in minutes – but here’s the hard truth: the magic isn’t in the AI, it’s in your input. What you ask for, how you guide it, and the design principles you enforce make all the difference.
AI lets us skip the tedious steps, but not the critical ones:
- Deep customer understanding
- Intentional problem-solving
- Innovative solution design
- Continuous validation
The algorithms don’t have what you have: real-world context. They don’t observe customers struggling with your product. They don’t feel the frustration of a broken user flow. They can’t replace your ability to synthesize insights from a dozen different sources at once.
So what does this mean for the future of product craft?
From a Product Designer’s Perspective:
Design has always been important, but now—more than ever—it’s the differentiator between forgettable products and ones that truly resonate. Over the years, I’ve built my fair share of quick, vibe-driven coding projects, and one lesson became clear early on: just like AI-generated images, you can often spot when a product leans too heavily on AI.
The interfaces start to feel familiar in the wrong ways—relying on the same predictable layouts, the same sanitized interpretation of “modern and clean,” the same homogenized aesthetic that AI models have been trained to replicate.
But great products aren’t just functional—they’re memorable. They have personality. They connect. And for that, design isn’t just a layer—it’s the foundation. We need to push beyond templated solutions and inject real humanity into what we build.
That means crafting interfaces that don’t just follow trends but reflect the uniqueness of the brands they represent. It means questioning what “fresh” even means and redefining it on our own terms. Because the most exciting products—the ones that stick with us—aren’t the ones that look like everything else. They’re the ones that feel intentional, distinctive, and alive.
So yes, AI can automate a lot. But vision? Taste? A point of view? That’s on us. And that’s why design isn’t just important—it’s irreplaceable.
From a Product Developer’s Perspective:
This is a superpower to 10x your productivity—not to replace you. Most “vibe coders” don’t have a background in programming or writing code, two essential skills for making any video coding project viable at scale. And let’s be real, there are things vibe coders simply can’t do properly, like building secure software—especially in fintech.
If you’re a programmer, you’re probably already using AI in some form to handle the grunt work of writing boilerplate code. At this point, you’re likely spending more time reviewing code than actually writing it. If you’re not doing this, you’re leaving productivity and execution speed on the table—because the devs leveraging AI will outpace you, delivering faster and with higher-quality code.
That said, AI in its current state isn’t here to replace developers with vibe coders. It just doesn’t work at scale if you don’t understand what you’re doing or how to read the code. So instead of fearing it, use AI as your superpower—to 10x your output, your Git commits, and your impact.
From a Product Manager perspective
The integration of AI into product design and development isn’t just an incremental improvement—it’s a fundamental shift in how we build, iterate, and deliver. Speed and flexibility are no longer just advantages; they’re necessities. With AI, your team can compress what used to take multiple sprints into a fraction of the time, unlocking the ability to experiment, learn, and adapt at an unprecedented pace.
Traditional Agile sprints were built for a different era—one where design, development, and testing moved in sequential, time-bound phases. AI changes that. Now, early-stage products can go from customer feedback to deployed improvements in a single sprint. Instead of waiting weeks to validate an idea, you can prototype, test, and refine in near real-time.
A/B testing, once constrained by resource limitations, becomes exponentially more powerful. AI enables you to launch multiple feature variations simultaneously, analyze performance instantly, and double down on what works—without slowing down delivery. The result? Faster validation, smarter decisions, and a product that evolves in lockstep with user needs.
Rethinking the way we work for maximum impact
To fully capitalize on this shift, your entire approach to product development needs to adapt. That means:
- Shorter feedback loops – Use AI to rapidly prototype and test ideas, reducing reliance on lengthy design phases.
- Continuous deployment – Move beyond rigid sprint boundaries and embrace a flow of smaller, faster releases.
- Data-driven experimentation – Leverage AI-generated insights to prioritize what to build next, minimizing guesswork.
Your role as a Product Manager is no longer just about managing backlogs—it’s about enabling speed. By automating repetitive tasks, AI frees your team to focus on high-impact work: strategy, innovation, and deep customer understanding.
The old Agile framework wasn’t built for this velocity. Teams that cling to traditional sprint structures risk being outpaced by those who embrace AI-driven agility. The key? Empower your team to experiment relentlessly. Encourage them to adopt AI tools that accelerate design, development, and testing—then refine processes based on what delivers the best results.
This isn’t just about working faster; it’s about working smarter. With AI handling execution at scale, you gain more time to focus on what truly moves the needle: delivering a product that users love.
The future belongs to those who move quickly, adapt constantly, and leverage AI to its fullest potential. The question isn’t whether you should rethink your approach—it’s how fast you can start.
Final Thoughts
Vibe coding is here to stay—but hype cycles fade, and reality sets in. Eventually, teams will gravitate back toward what actually works: proven methods for building scalable, maintainable products. Tools like Cursor and Warp are undeniably powerful—but only in the hands of developers who know how to ship secure, production-ready software. Sensitive data, compliance, and long-term reliability? Those aren’t exactly the concerns of the vibe-coding crowd.
At its core, programming is a craft. Understanding the code your users depend on isn’t optional—it’s the foundation of security, performance, and trust.
So, will we see an avalanche of half-baked, AI-generated spaghetti code? No doubt. Will some of it accidentally work? Sure. Will some of it fail spectacularly yet still turn a profit? Sadly, yes. But as always with AI: garbage in, garbage out.
Would I blindly trust AI to build a product? Never. Real innovation still requires real expertise—designers, engineers, marketers, and product leaders working in sync, backed by real investment. AI is a lever, not a replacement. The future belongs to those who wield it wisely.
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