If you’ve recently heard the term “vibe coding” in a meeting or spotted it as Collins English Dictionary’s Word of the Year 2025, you’re witnessing a genuine shift in how software gets developed. This is more than just another productivity trend — it’s a legitimate change in development practices that’s already reshaping the industry.
What Actually is Vibe Coding?
The Origin
The term “vibe coding” was coined by Andrej Karpathy in February 2025, the co-founder of OpenAI and former leader of Tesla’s AI division. His exact quote captures the essence:
“There’s a new kind of coding I call ‘vibe coding’, where you fully give in to the vibes, embrace exponentials, and forget that the code even exists.”
The Key Distinction
What makes vibe coding different from simply using AI tools is that you’re accepting AI-generated code without fully understanding it. You’re not reviewing every line or debugging syntax — you’re trusting the AI got it right.
Simon Willison, a respected voice in AI coding, clarifies the distinction:
“If an LLM wrote every line of your code, but you’ve reviewed, tested, and understood it all, that’s not vibe coding in my book — that’s using an LLM as a typing assistant.”
Bottom line: If you’re actually reading and understanding the AI’s code, you’re not vibe coding — you’re coding with AI assistance.
Rapid Rise to Mainstream
- March 2025: Merriam-Webster added vibe coding to their “slang & trending” list
- 2025: Collins Dictionary named it Word of the Year
This went from Twitter meme to legitimate dictionary entry in approximately three months.
The Speed Advantage: By the Numbers
The productivity gains from vibe coding are substantial:
- 55% faster project completion compared to traditional manual coding
- 20-50x faster feature implementation with structured vibe coding workflows
- 5.8x faster application development times reported by companies embracing the approach
Y Combinator Snapshot
In Y Combinator’s Winter 2025 batch, 25% of startups had codebases that were 95% AI-generated — a quarter of the top startup accelerator’s class essentially using vibe coding to reach product-market fit.
Where Vibe Coding Excels
Vibe coding works exceptionally well for:
Rapid Prototyping and MVPs
- Test ideas in a weekend instead of months
- Perfect for startups validating product-market fit quickly
Small-Scale Applications and Personal Projects
- Kevin Roose from the New York Times (not a programmer) successfully created multiple functional applications using vibe coding
- If a journalist can build software, it speaks to accessibility
Quick Automation Tasks and Internal Tools
- Process data scripts in hours instead of scheduled sprints
- Simple internal dashboards and utilities
“Software for One”
- Personalized AI-generated tools for individual needs
- No longer requires developer expertise to solve personal problems
Early-Stage Validation
- Non-technical founders can build proof of concepts without hiring engineers
- Test ideas before significant financial investment
The Transformation
Vibe coding enables one person to accomplish work that previously required an entire engineering team.
Where Traditional Coding Still Dominates
Traditional development remains essential for:
Complex Enterprise Systems
- Building Salesforce-level platforms requires traditional approaches
- No one is vibe coding critical enterprise software
Performance-Critical Applications
- Applications where speed and efficiency matter most
Security-Sensitive Industries
- Financial services
- Healthcare
- Aerospace
- Regulatory compliance is non-negotiable
Long-Term Scalability and Maintenance
- Code touched by dozens of developers over years requires proper documentation and architecture
- Understandability is crucial
Compliance-Heavy Environments
- Regulatory requirements demand audit trails and documentation
- Code must be explainable to regulators
Mission-Critical Systems
- Where downtime costs millions per hour
The Pattern
Traditional coding required when: High stakes + High complexity + High security requirements
Vibe coding suitable when: Low stakes + High speed requirements + Small scale
The Democratization of Software Development
The Barrier to Entry Disappears
Traditional coding required years of learning:
- Programming languages
- Syntax and frameworks
- Design patterns
- Implementation details
Vibe coding requires: Understanding what you want the software to do and describing it in plain English.
The Role Evolution
Developers’ responsibilities shifted from:
- Writing code, architecting systems, debugging
To:
- Prompting AI, guiding development, testing outputs, validating results
The Accessibility Impact
- Amateur programmers can now produce functional software
- Non-technical creators can build and launch independently
- Traditional developers are obsolete? Absolutely not — but skills are shifting
The Risks Are Very Real
Security Vulnerabilities
Lovable (a Swedish vibe coding app) analyzed 1,645 AI-generated web apps:
- 170 contained security issues allowing unauthorized access to personal data
- Over 10% had serious security vulnerabilities
Fast deployment without understanding code means vulnerabilities slip into production, and fixing issues in code you don’t understand is extremely difficult.
Code Quality Inconsistency
- AI-generated code varies wildly in structure and quality
- Human validation is necessary but difficult if you don’t understand the code
- Debugging unfamiliar code is exponentially harder
Karpathy’s candid admission:
“Sometimes the LLMs can’t fix a bug so I just work around it or ask for random changes until it goes away.”
This works for weekend projects — not for production systems.
AI Limitations with Complexity
- Excels at simple tasks and basic algorithms
- Struggles with complex problems
- Difficulty with multi-file projects, poorly documented libraries, and safety-critical code
- LLM-generated code structure varies, complicating debugging
Real-World Failures
- Kevin Roose: AI fabricated fake reviews in an e-commerce site
- SaaStr Founder: Replit’s AI agent deleted entire database despite explicit instructions
- Fast Company (September 2025): Senior engineers citing “development hell” with vibe-coded applications
Data and IP Risks
- External LLM prompts may expose confidential business information
- Intellectual property could leak into AI training data
- Serious legal implications
What Experts Actually Think
Andrew Ng believes “vibe coding” is misleading and trivializes the skill involved in AI-assisted development.
IEEE Spectrum Engineers agreed vibe coding is valuable for learning unfamiliar languages and technologies, but diverge on production use.
Simon Willison’s Assessment:
“Vibe coding your way to a production codebase is clearly risky. Most of the work we do as software engineers involves evolving existing systems, where the quality and understandability of the underlying code is crucial.”
Key Tension: Vibe coding excels for greenfield projects and prototypes but is risky for maintaining complex systems over time.
Gary Marcus (AI Skeptic): Argues vibe coding’s success comes from reproducing existing patterns, not creating original solutions — remixing Stack Overflow, not inventing new approaches.
The Hybrid Approach: The Real Answer
Most efficient modern teams blend both methods strategically:
- Use vibe coding for initial modules and rapid prototyping
- Get something working fast and validate the idea
- Switch to traditional coding for refinement, scaling, and production reliability
- Have experienced engineers review generated code and refactor as needed
- Add proper tests and documentation for complex sections
This isn’t vibe coding OR traditional development — it’s vibe coding AND traditional development.
Use speed where speed matters. Use rigor where rigor matters.
What This Means for Your Team
For Developers
Vibe coding doesn’t replace you — it changes what you do. You spend less time fighting syntax and more time architecting solutions, reviewing AI output instead of writing every line.
Whether this is better depends on what you enjoy about coding. Problem solvers win; developers who love crafting elegant code may feel differently.
For Managers
Adopt vibe coding for some projects and avoid it for others:
- Experiment on low-stakes internal tools
- Keep traditional approaches for critical systems
For CTOs
Don’t mandate either approach company-wide. Different problems need different tools:
- Your infrastructure team probably needs structure
- Your innovation team probably needs speed
- Let teams choose based on project requirements
Real-World Application: Attract Group’s Approach
At Attract Group (building custom software since 2011), the philosophy is pragmatic rather than ideological:
For startup MVPs requiring quick market validation: Leverage AI-assisted development and rapid iteration to move from idea to testable product faster.
For enterprise systems (healthcare CRM with compliance requirements): Bring traditional software engineering practices, thorough documentation, and regulatory rigor.
For most projects: Somewhere in between — vibe code initial prototypes, then refactor with traditional practices for production.
Technical Expertise
- Tech stacks: React, Vue.js, Flutter, Laravel, Django
- Developers across US and Netherlands
- Efficient remote coordination
The Philosophy
Choose the right tool for your problem. Sometimes it’s AI-assisted speed. Sometimes it’s battle-tested engineering practices. Usually it’s both.
The Bottom Line
What’s Real:
- Vibe coding is fast (55% speed improvements are genuine, not marketing hype)
- Accessibility gains are real — non-technical people can build software
- This genuinely differs from previous development approaches
What’s Also Real:
- Security vulnerabilities are not exaggerated
- Code quality issues exist
- Limitations with complex systems are significant
- Traditional development isn’t dead; it’s evolving
The Right Answer:
The future isn’t vibe coding OR traditional coding. It’s knowing which approach solves your actual problem.
- Building a weekend project or testing an idea? Vibe code it.
- Building software people’s livelihoods depend on? Maybe don’t fully give in to the vibes.
- Most real-world projects? Use both strategically.
Everything else is just noise.
