Building Software in the Age of Vibes
Why vibe coding may be the most immature—and most important—software shift of the decade.
There’s a new kind of software development sweeping through startups and strategy decks alike. It’s fast. It’s weird. It kind of works. And if you squint, it might be the beginning of a new programming paradigm.
They call it vibe coding. Think prompt-based development where human developers act more like directors than builders—describing what they want, and trusting the AI to deliver the goods. Sometimes it does. Sometimes it… really doesn’t.
But it’s gaining traction for a reason.
Let’s unpack what vibe coding is, where it’s thriving (and crashing), and how leaders should be thinking about its place in their organizations today.
What Is Vibe Coding?
Vibe coding is not just another trend—it's the early experimental version of a transformational shift in software development. Much like the leap from text editors to IDEs, this represents a 10x evolution in how we engage with code. But unlike past tooling shifts, vibe coding changes who can build, how fast they can go, and what kind of mental models are required to lead the work.
At its core, vibe coding is prompt-driven development with minimal human intervention. Coined and demoed by Andrej Karpathy in early 2025 (source), it describes a workflow where you articulate your intent in natural language, let the AI write or change code, and trust the result with little to no inspection.
This isn’t just “AI pair programming.” It’s closer to AI ghostwriting, where the human doesn’t edit, just vibes (MIT Technology Review).
Think of it as the no-code ethos, now with Python, TypeScript, and other languages.
Why It Matters: Speed, Accessibility, and Systemic Change
The organizations that take vibe coding seriously now—not just using the tools, but actively shaping the ecosystem—will be tomorrow’s leaders. As with every general-purpose technology, those who get in early and figure out the supporting practices first will have a durable advantage. And yes, vibe coding will mature—it’s not a matter of if, but when.
Vibe coding opens the door to faster prototyping and broader participation in software creation.
Startups are shipping MVPs in days (Codemotion; Slashdot).
Non-developers are launching revenue-generating products (Reddit; Zapier).
Enterprises like IBM are using vibe coding for internal tooling and low-code empowerment (Nasuni).
The Upside: Why People Love It
1. Speed and Prototyping At its best, vibe coding feels like teleportation. You go from a vague feature idea to a working UI in under an hour. In Daniel Bentes’ 27-day experiment, the early days felt magical—rapid iteration, instant feedback, and whole features built in a single session (LinkedIn). For founders in early validation mode, or teams jamming out a pitch-deck demo, this speed is transformative.
2. Accessibility Vibe coding strips away the gatekeeping layers of traditional development. It empowers people who never learned to code—designers, marketers, domain experts—to build software using a language they already know. A CNBC journalist built a real, working app in 48 hours with zero engineering background (CNBC).
3. Cost and Efficiency When 10-person teams start delivering what used to require 50 engineers, people notice. Y Combinator reports portfolio companies hitting $1–10M ARR with teams small enough to fit in a WeWork booth (Slashdot).
4. Creative Freedom Without the friction of scaffolding, boilerplate, and syntax rules, creators can move directly from vision to expression. Andrew Chen describes projects that would never be worth scoping traditionally—a flight simulator built from thousands of AI prompts, just to see if it worked (Andrew Chen).
5. Developer Delight Even seasoned engineers find joy in skipping the dull parts. Simon Willison uses vibe coding to offload tedious tasks—letting the AI generate scaffolding or automate integration points while he focuses on design and data modeling (Simon Willison).
The Dark Side: What Can Go Wrong
This doesn’t mean the old rules of engineering go away. If anything, they become more important. Vibe coding without oversight is like letting a calculator draw graphs without understanding the math. The tools may make building easier, but they also make it easier to build the wrong thing—or something that breaks catastrophically under pressure.
1. Security and Reliability: The AI doesn’t care about OWASP. Vibe-coded apps frequently ship with glaring vulnerabilities—hardcoded credentials, missing auth checks, or unvalidated inputs (TechRepublic; Zencoder).
2. Maintainability and Debt: Daniel Bentes’ experiment started great, then descended into entropy. The AI began to contradict itself—rewriting styles, duplicating logic, and producing brittle code that was hard to change (LinkedIn).
3. Debugging Nightmares: AI-generated code can be a black box. Developers describe vibe-coded systems as “mystery meat”—code that technically works, but no one can explain why. When bugs arise, there’s no breadcrumb trail (Addyo; SEP).
4. Skill Erosion: For junior devs especially, vibe coding offers the illusion of fluency. There’s growing concern about a generation of developers who can ship features but can’t reason through them (Nucamp; Zencoder).
5. Failed MVPs: Many vibe-coded projects make a strong first impression—then implode. Reddit is full of postmortems: apps that seemed to work, but couldn’t handle real users or became too fragile to extend (Reddit).
What Comes Next: From Vibes to Outcomes
Vibe coding isn’t going away. But it will evolve—and not just in terms of how we prompt or direct AI, but in the entire ecosystem of tools and practices that support it.
Outcome-driven development: Instead of specifying "build a signup form," you’ll specify the outcome: “maximize signup conversion.” The AI will generate, test, and refine different implementations based on real-time user behavior. It’s a shift from code-as-instruction to code-as-hypothesis—a loop where the AI continuously adapts to user needs and business goals (Forbes).
Multimodal interfaces: As interfaces expand beyond text, expect to see visual sketching, voice commands, and even gesture-based prompting become viable ways to direct AI coding agents. Imagine speaking into a headset while drawing a UI layout with your hands—and having the app scaffolded in real time (IBM).
New team roles: The future of development will include roles like "prompt engineers," "AI product directors," or "outcome architects"—people who don’t necessarily code, but who define intent and guide AI to deliver aligned functionality. These roles will blend product strategy, UX insight, and systems thinking (TRM Labs).
Ecosystem Maturation: Vibe coding will require a full ecosystem of supporting tools to reach maturity. Expect innovations in testing frameworks, test data generation, security validation, scalability simulation, and cost prediction. These tools will be essential to moving vibe coding from toy to trusted infrastructure—just as DevOps tooling did for CI/CD.
What You Should Be Doing Now
1. Pilot Wisely: Start small. Identify non-critical projects—like internal tools, admin dashboards, or data visualizations—and use them as a safe sandbox to explore vibe workflows. Try building one feature with AI and compare the results. Start tracking what works and what doesn't.
Getting Started:
Use tools like Replit or Cursor to build a basic CRUD app with your product team.
Run a hackathon where the only rule is “no manual coding.”
2. Establish Guardrails: Don’t skip the essentials: code review, static analysis, automated testing. Think of AI as a junior developer—it needs oversight. Define clear protocols for security, performance, and compliance. Vibe coding should accelerate delivery, not compromise quality.
Getting Started:
Create checklists for reviewing AI-generated pull requests.
Use tools like SonarQube or CodeQL to scan output for issues.
3. Invest in Prompt Literacy: Effective prompting is a skill. Train your teams on how to frame instructions, give feedback to AI tools, and steer output toward desired outcomes. Treat prompting like interface design—it needs clarity, iteration, and user empathy.
Getting Started:
Run prompt design workshops.
Pair experienced developers with non-coders to co-pilot prompts.
4. Evaluate Your Stack: Not all tools are created equal. Test multiple vibe coding platforms—Cursor, Copilot Workspace, Windsurf, Superwhisper—and see which best fit your workflows. Look at integration depth, output quality, and transparency.
Getting Started:
Assign team leads to trial two different tools and report back.
Measure output accuracy, onboarding time, and team satisfaction.
5. Stay Open, Stay Grounded: This shift isn’t just technical—it’s cultural. Encourage experimentation but be clear about limits. Let teams share wins and war stories. Create space for exploration without hype. Curiosity is fuel, but discipline is your compass.
Getting Started:
Create a lightweight internal forum to share vibe coding lessons.
Appoint a vibe tech lead or “AI captain” to steward safe experimentation.
This isn’t just about tools—it’s about a shift in how we build. Proceed with curiosity and discipline in equal measure.
Final Thought
Vibe coding might not keep its name—enterprises probably won’t embrace the term. But don’t let the branding distract you: this is the beginning of a revolution in how software gets made. It’s not a passing trend. It’s the text editor before the IDE, the early web before web apps—immature, awkward, and absolutely foundational.
Is vibe coding the future of software development?
Not exactly. It’s the beginning of the future of software, full stop.
This WILL mature. Those who embrace it early, who learn to wield it responsibly, will have a major strategic advantage. Those who hesitate will be left playing catch-up.
That doesn’t mean the fundamentals of good engineering go away. Quite the opposite: vibe coding raises the bar for engineering discipline, because now anyone can generate code, but only skilled teams can deploy it safely, scalably, and ethically.
We should view this shift as the emergence of a new general-purpose technology for software development. Like cloud, like open source, like DevOps—it will reshape roles, workflows, and business models. And just like those movements, it demands a thoughtful, intentional approach to adoption.
Bottom line: Embrace it. Invest in it. But treat it with the care it deserves. Because it’s not just software that’s changing—it’s the nature of who builds it, how fast, and for whom.
If that doesn’t shift how we think about teams, tooling, and talent… well, then maybe we’re not vibing hard enough.
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