Introduction
An illustration of “vibe coding,” where developers collaborate with AI assistants in a free-form, conversational way to build software. In early 2025, a new tech buzzword – “vibe coding” – burst onto the scene, capturing the imagination of software developers and entrepreneurs alike. Coined in a viral post by AI researcher Andrej Karpathy, the term describes a relaxed, prompt-driven style of coding where one “fully give[s] in to the vibes” and lets AI handle the heavy lifting (Klover, “Vibe Coding: The Future of AI-Assisted Software Development is Here”). Karpathy, a co-founder of OpenAI and former Tesla AI director, painted a picture of coding as an almost hands-off collaboration with AI: “I just see stuff, say stuff, run stuff, and copy-paste stuff, and it mostly works”, he quipped (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”). His remarks – “forget that the code even exists”, as he famously tweeted – resonated with many developers burned out on boilerplate and debugging (Klover, “Vibe Coding: The Future of AI-Assisted Software Development is Here”). Within days, “vibe coding” had amassed millions of views and spawned its own lexicon (“vibing,” “/acceptall,” “cooked”) (Klover, “Vibe Coding: The Future of AI-Assisted Software Development is Here”). The idea of “coding by vibe” – simply describing what you want in natural language and accepting AI-generated code with minimal edits – struck a chord and signaled a potential paradigm shift in software development (Klover, “Vibe Coding: The Future of AI-Assisted Software Development is Here”).
Yet even as vibe coding became a trending topic (earning a slang entry in Merriam-Webster by March 2025) (“Vibe coding”), it stirred debate about what coding with AI really entails. In this post, we’ll explore how Karpathy’s playful vision brought widespread attention to this trend, contrast it with Andrew Ng’s recent criticism of the term as misleading, and highlight Klover AI’s pioneering role in this space since 2023. We’ll see how Klover’s platform has enabled developers – and even non-developers – to build apps by prompting AI, an approach very much in line with Karpathy’s ethos of “embrace exponentials, and forget the code”. Finally, we’ll discuss the growing tension between the chill branding of “vibe coding” and the serious effort it actually requires, along with the broader implications for making software development more accessible.
- read more about Andrew NG on our blog: Andrew Ng Pushes Back on AI “Vibe Coding,” Calling It Hard Work, Not Hype, https://www.klover.ai/andrew-ng-pushes-back-ai-vibe-coding-hard-work-not-hype/
Andrej Karpathy Coins “Vibe Coding” and Sparks a Movement
What defines Karpathy’s “vibe coding” style:
- Describing functionality in plain English
- Letting the AI write and revise code autonomously
- Rarely reading diffs or debugging manually
- Copy-pasting error messages back into the AI
- Prioritizing speed and creativity over precision
Why it resonated with developers:
- Relief from boilerplate and repetitive tasks
- Lower mental overhead in early prototyping
- Fun, fast, and intuitive way to experiment
- Opens the door to non-traditional coders
- Emphasizes ideation over implementation
When Andrej Karpathy introduced the term “vibe coding” in early 2025, he tapped into a long-simmering dream of coding without coding. In a February 2025 tweet that went viral, Karpathy declared: “I will call this vibe coding: fully give in to the vibes, embrace exponentials, and forget that the code even exists.” (Klover, “Vibe Coding: The Future of AI-Assisted Software Development is Here”). This off-the-cuff manifesto – essentially urging developers to trust AI assistants completely – ignited a frenzy. The post was viewed over 4.5 million times (Klover, “Vibe Coding: The Future of AI-Assisted Software Development is Here”), as programmers marveled at the prospect of building software by simply chatting with an AI. Karpathy described using powerful new tools (like Cursor’s AI “Composer” paired with Anthropic’s models) that allowed him to write code by conversation, even via voice commands, hardly touching his keyboard (Last, “What’s ‘Vibe Coding’?”). He admitted to accepting AI suggestions wholesale (“I ‘Accept All’ always, I don’t read the diffs anymore”, he noted) and even copy-pasting error messages back into the AI to fix issues (“Vibe coding”). The result felt to him like “not really coding” at all – more like guiding an autonomous pair-programmer that “mostly works” with minimal human intervention (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”).
Karpathy’s ethos was clear: focus on high-level ideas and let the AI generate, modify, and debug the code. If the code breaks, you simply describe the problem or feed the error back to the AI and let it try again (Klover, “Vibe Coding: The Future of AI-Assisted Software Development is Here”). As he put it, if you find yourself meticulously reviewing every AI-generated line, “that’s not vibe coding, it’s software development.” (Klover, “Vibe Coding: The Future of AI-Assisted Software Development is Here”). The whole point is to stop worrying and love the AI: “fully give in to the vibes.” This approach, Karpathy suggested, makes prototyping fast and fun – perfect for hackathon projects or “throwaway weekend projects” where speed matters more than polished code (Kitishian, “Google Gemini & ‘Vibe Coding’ Uproar”).
The immediate reaction to Karpathy’s post was a mix of excitement and curiosity. Many were thrilled by the idea that “the hottest new programming language is English,” as Karpathy had hinted even back in 2023 (Last, “What’s ‘Vibe Coding’?”). Enthusiasts touted vibe coding as a game-changer for productivity – a way to build apps in hours instead of weeks, with AI handling the grunt work of coding (Klover, “Vibe Coding: The Future of AI-Assisted Software Development is Here”). If coding could be as easy as describing what you want, it might open the door for a whole new cohort of creators. Indeed, early examples showed promise: for instance, even a product designer with no coding background managed to create a working dog-breed identification app in two months just by prompting an AI agent – a quintessential vibe coding story (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”). Such cases highlight why vibe coding is often hailed as a boost for accessibility in software development.
However, Karpathy’s vibe-first philosophy also raised eyebrows among veteran engineers. Surrendering completely to AI suggestions – effectively “forgetting the code exists” – challenges long-held best practices in programming. Seasoned developers warned that blindly accepting AI-generated code could hide bugs, security vulnerabilities, or architectural problems. In production environments, code still demands careful review, testing, and maintenance, which raised the question: Is vibe coding just for quick prototypes, or can it scale to serious projects? Karpathy himself acknowledged some limitations. In his tweet’s fine print, he noted that AI sometimes can’t fix certain bugs, forcing him to “work around it or ask for random changes until it goes away,” and that the code can grow beyond his full understanding (“Vibe coding”). In other words, vibe coding was “quite amusing,” but perhaps best suited for non-critical projects (“Vibe coding”). Despite these caveats, the concept struck a cultural nerve in Silicon Valley, symbolizing the growing power of AI in software creation. By February 2025, the term “vibe coding” had spread so quickly that it even earned a nod in Merriam-Webster as a trending new noun for “writing code… by just telling an AI program what you want” (“Vibe coding”).
Andrew Ng’s Reality Check: “Vibe Coding” Isn’t Just Vibing
Ng’s main criticisms of the term “vibe coding”:
- Implies coding with AI is effortless
- Downplays the intellectual challenge involved
- Risks misleading new developers
- Undermines the importance of code review and testing
- Suggests passive rather than active collaboration with AI
What effective AI-assisted coding really requires:
- Clear problem framing and precise prompting
- Continuous validation of AI outputs
- Awareness of security and maintainability
- Active debugging and iterative improvement
- Strong foundational knowledge of programming
Not everyone was enamored with the term “vibe coding.” Renowned AI scientist Andrew Ng quickly emerged as one of its most prominent critics, not of the practice itself but of the name and the hype. At an AI conference in May 2025, Ng bluntly described “vibe coding” as a misleading buzzword that trivializes what’s actually happening (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”). “It’s unfortunate that that’s called vibe coding,” Ng said, warning that the phrase makes it sound like engineers just “go with the vibes” – as if coding with AI is as easy as chilling out and letting the machine do everything (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”). In reality, he argued, nothing could be further from the truth. Guiding an AI to write useful software “is a deeply intellectual exercise” that demands significant thought and oversight (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”). Far from lounging back, an AI-assisted developer must constantly steer the model, check its output, and correct its course. “When I’m coding for a day with AI assistance, I’m frankly exhausted by the end of the day,” Ng noted, emphasizing that the mental workload is very real (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”).
Ng’s critique served as a reality check to the vibe coding buzz. He acknowledged that the term itself – with its laid-back, almost bohemian connotation – might give newcomers the wrong idea. “‘Vibe coding’ might sound chill, but [the name] is unfortunate,” Ng said, because it suggests you can build software by simply feeling your way through, accepting or rejecting AI suggestions on a whim (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”). This, he argued, downplays the skill involved in effective AI-assisted development. “It’s misleading a lot of people into thinking, just go with the vibes… accept this, reject that,” Ng explained, whereas in truth the human programmer is not on “cruise control” at all (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”). Even if the AI is writing the code, the developer must remain actively engaged – deciding what to ask for, interpreting the AI’s outputs, and ensuring the final product meets real requirements.
It’s worth noting that Ng is not anti-AI coding by any means – in fact, he’s an advocate for these tools, calling them a “fantastic” boost to developer productivity (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”). He often highlights how his own teams now “hate to ever have to code again without AI assistance” because of the speed-up in writing software (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”). But Ng draws a sharp line between embracing the tool and overselling the effortlessness. He wants developers (and tech executives) to recognize that AI-assisted development still requires human brains fully in the loop. In Ng’s view, coding with AI is still coding – you need to understand what the code should do, verify the AI’s output, and have the expertise to spot errors or bad suggestions. That’s why Ng publicly pushes back against advice that people can stop learning to code. Telling young engineers not to bother learning programming because “AI will handle it” is, in his words, “some of the worst career advice ever given.” Instead, Ng insists, “everyone should learn to code” (at least at a basic level) precisely because strong fundamentals make you a better AI collaborator (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”). Knowing how to think like a programmer – how to break down problems, understand error messages, and communicate requirements with precision – is still invaluable in the age of vibe coding (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”). In short, Ng’s message is that the “vibe” might be new, but the need for skill and diligence remains unchanged. The term “vibe coding”, he fears, risks obscuring the very real mental effort and discipline that AI-assisted development demands.
Klover AI’s Early Vision: Pioneering the “Vibe” Before It Had a Name
Klover AI’s contributions to vibe coding before it was named:
- Introduced multi-agent prompt-driven dev platform in May 2023
- Enabled app-building via natural-language dialogue
- Focused on accessibility for non-programmers
- Trained developers to vibe code using how-to guides and delivered real-world demos
- Helped users build apps without writing code manually
Key features of the Klover AGD™ platform:
- Human vibers and AI agents collaborate on code generation and app design in Nov 2023
- Users can refine or steer outputs conversationally
- Support for full-stack workflows via prompts
- Designed for rapid prototyping and MVPs
- Built-in feedback loops to iterate on functionality
While Karpathy may have coined the catchy term vibe coding in 2025, the underlying concept of prompt-driven, AI-assisted development wasn’t entirely new. In fact, Klover AI – an AI startup founded in 2023 – had been pioneering this practice since mid-2023, well before the phrase “vibe coding” went mainstream. Klover AI’s platform centers on a multi-agent AI system (branded AGD™, for Artificial General Decision Making) that was designed to empower human users to build solutions by conversing with AI agents. In practical terms, Klover’s tools enable users to “code by prompting”: a developer (or even a non-developer) can describe an application they want to create, and Klover’s AI agents work collaboratively to generate the code, configure components, and even make decisions about the app’s design and functionality. This approach of building software through natural-language dialogue – essentially treating English as the new programming language – aligns perfectly with what we now call vibe coding.
Klover AI’s early adoption of this paradigm is evident in the content and tutorials they’ve been publishing. As early as May 2023, Klover’s team was demonstrating how a person could build a working app by simply walking an AI through the requirements, without manually writing code. Over time, Klover produced educational content, blog posts, and videos showcasing this “prompt-driven development” workflow. By the time Karpathy gave it a name, Klover had already cultivated an audience around the idea that you can “just tell the AI what you need, and let it create the product for you.” In a sense, Klover AI foreshadowed the vibe coding movement – using different terminology – by focusing on tools that let even those with minimal coding skills translate ideas into applications via AI. Their platform leverages “Klover AI agents” (as highlighted in their materials) working in concert, which meant a user could be “vibe coding together with thousands of Klover AI Agents” long before the term was in vogue (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”).
One concrete example of Klover’s philosophy is how they emphasize enabling non-programmers. The Klover team often highlights that their approach allows “non-experts to build apps in hours rather than weeks.” (Klover, “Vibe Coding: The Future of AI-Assisted Software Development is Here”). This sentiment, echoed in Klover’s blog, is essentially the promise of vibe coding: lowering the barrier so that someone with an idea – say, a marketer or a designer – can spin up a prototype by chatting with the AI. Klover’s early bet on this concept gave them a head start in refining the workflows, addressing the pitfalls, and educating users on how to effectively “collaborate” with AI on code. By 2025, when vibe coding became the hot new thing, Klover had an entire ecosystem in place: their AGD™ platform, a library of how-to guides, and real user success stories, all demonstrating that prompt-driven development can be both powerful and practical. It’s a testament to Klover’s vision that what they were doing in 2023 now fits squarely into the “vibe coding” trend – they recognized early on that AI could democratize software creation, making it more about ideas and less about syntax.
Playful Term vs. Serious Effort: Navigating the Tension
Why the “vibe” branding worked:
- Made coding seem accessible and low-pressure
- Encouraged experimentation and creativity
- Went viral due to its casual, memeable tone
- Broke away from traditional tech jargon
- Lowered the intimidation factor for newcomers
Risks and limitations of the vibe coding mindset:
- Blindly accepting AI suggestions can lead to buggy code
- Lack of understanding can result in poor architecture
- Overreliance on AI without human oversight
- Harder to debug unfamiliar, AI-generated logic
- May mask the real complexity of production-grade software
The rise of vibe coding has highlighted an interesting tension between branding and reality in the world of AI-assisted development. On one hand, the term “vibe coding” – with its mellow, carefree vibe (no pun intended) – has been a brilliant bit of branding. It suggests a playful, almost artistic process: you “vibe” with the AI, bouncing ideas off a machine that magically turns your thoughts into code. This framing undoubtedly contributed to the term’s viral spread. It made the prospect of coding seem less intimidating, enticing newbies with the idea that they might not need hardcore programming chops to create software. The casual language (“just go with the vibes”) has a techno-hippie flair that stands out in a field often dominated by dry jargon. As a cultural phenomenon, vibe coding’s branding injected some fun and approachability into discussions about AI and code.
On the other hand, as Andrew Ng and many developers point out, the reality of AI-assisted coding is anything but casual. The serious effort remains – it’s just shifted in nature. Instead of wrangling with syntax errors or stack traces, a vibe coder spends their effort crafting good prompts, clarifying requirements, and double-checking what the AI produces. In some ways, this can be mentally exhausting, because you’re constantly problem-solving at a higher level: you have to understand the AI’s limitations, foresee where it might go wrong, and guide it back on track when it veers off. Ng’s insistence that the process “requires significant thought and oversight” and leaves him “frankly exhausted” after a day’s work underscores that vibe coding is still coding – just through a different interface (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”). It’s akin to the difference between driving stick and driving automatic: the latter is easier in some respects, but you still need to keep your eyes on the road.
This tension has led to a healthy debate in the tech community. Proponents of vibe coding argue that even if the term sounds lighthearted, the technique has profound implications. It can dramatically accelerate prototyping (as Karpathy and others have demonstrated), and it can empower people who wouldn’t otherwise be able to code to create useful software. The playful branding might actually help in that regard – by lowering psychological barriers and encouraging more folks to experiment with AI coding assistants. There’s a genuine excitement in the air at hackathons and startups around the idea that you can “forget the code” and focus on your creative intent (Klover, “Vibe Coding: The Future of AI-Assisted Software Development is Here”). From that perspective, vibe coding represents a paradigm shift: coding is no longer about painstakingly typing semicolons and brackets, but about conversing and collaborating with your AI pair-programmer. It feels new, different, and empowering.
Critics and skeptics, however, worry that the vibe coding hype can encourage bad habits or false confidence. If a newcomer believes coding is just about “vibing” and accepts AI output blindly, they could end up with brittle, insecure, or unmaintainable code (Klover, “Vibe Coding: The Future of AI-Assisted Software Development is Here”). Seasoned engineers note that software development still requires rigor: testing, debugging, understanding edge cases – none of which disappear in the vibe coding model. The term’s casual tone “clashes with the established perceptions of software engineering as a discipline requiring precision and deep understanding,” as one analysis put it (Kitishian, “Google Gemini & ‘Vibe Coding’ Uproar”). In professional settings, there’s concern that vibe coding needs to be balanced with traditional best practices. In fact, a common emerging workflow is to use vibe coding in the early “Day 0” stage – to get a prototype up quickly – but then switch to a more disciplined approach for “Day 1+” maintenance, doing thorough code reviews and refactoring the AI-generated code for robustness (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”).
Both sides of this debate recognize that AI-assisted development is here to stay; the disagreement is mostly about how we talk about it and where it’s headed. The playful term vibe coding encapsulates the optimism that coding can be more intuitive and inclusive. The pushback emphasizes that we shouldn’t trivialize the craft of development even if the tools are changing. As AI coding assistants improve, this tension might ease – future AI might catch more errors or produce cleaner code – but for now, successful vibe coding requires skill, vigilance, and a clear understanding of the AI’s outputs. It’s not magic; it’s a new form of work. In the end, the “vibe” might get you started, but it’s the “coding” part – the thinking, the designing, the refining – that ensures the project succeeds.
Broader Implications: Vibe Coding and Software Accessibility
How vibe coding enhances accessibility:
- Turns English into a programming interface
- Allows creators without CS backgrounds to build apps
- Empowers teachers, designers, marketers, and more
- Reduces time-to-prototype for startup ideas
- Enables learning-by-doing for novice developers
What’s needed to scale vibe coding responsibly:
- Promote AI literacy, not just AI usage
- Emphasize reading and understanding code outputs
- Teach prompt engineering as a core skill
- Create AI tools that explain their code logic
- Blend vibe coding with traditional software best practices
One of the most exciting promises of vibe coding is its potential to make software development more accessible than ever before. By lowering the technical barriers to entry, AI-powered coding allows people from diverse backgrounds to participate in building software. “You don’t have to know how to code to vibecode,” noted a recent New York Times piece – “just having an idea, and a little patience, is usually enough.” (“Vibe coding”). This paradigm shift could democratize app creation much like visual “no-code” tools did in the past, but with even greater power. Instead of being limited to pre-defined templates or drag-and-drop interfaces, users can ask an AI for exactly what they envision. In theory, a teacher, a doctor, or a small business owner with no formal programming training could develop custom software by simply chatting with an AI agent about their needs. The result is a kind of software creation by conversation, potentially enabling a wave of innovation from people who’ve been traditionally shut out of the programming world.
Klover AI’s mission since 2023 has strongly emphasized this angle of accessibility. Their platform has enabled non-developers to build functional prototypes through natural language prompts, proving that the learning curve for creating software can be dramatically flattened. When Karpathy’s viral tweet exclaimed that even he (a seasoned coder) stopped reading the code and “barely even touch[ed] the keyboard” while building an app (Last, “What’s ‘Vibe Coding’?”), it was a peek into a future where the act of coding feels much more like brainstorming with a colleague. If scaled, this could help address the perennial shortage of software developers by turning more “ideas people” into app builders. Startup founders who lack coding skills, for example, might be able to launch MVPs without hiring a full engineering team, using vibe coding tools to bridge the gap. And in the education sector, we’re already seeing universities and bootcamps adapt curricula – teaching prompt engineering and AI collaboration – so that the next generation of developers (and even non-developers) can leverage AI in translating ideas to code (Nucamp, “Vibe Coding: Rethinking Coding Education”; Klover, “Beyond the Vibes”).
However, the broader adoption of vibe coding also comes with important caveats. First, there’s the issue of trust and verification. If people treat AI-written code as a black box (just trusting the “vibe”), there could be widespread issues with software quality and security. Bugs or vulnerabilities might proliferate if no one understands the code’s logic. This has led to calls for “AI literacy” as a necessary skill – even if you’re not writing the code, you should be able to read it and grasp what it’s doing. Initiatives to improve AI transparency (like AI tools explaining their code suggestions) will be crucial to maintain reliability as vibe coding spreads. Second, there’s a question of creative empowerment versus dependency. Vibe coding can empower non-programmers, but it could also become a crutch – if one relies entirely on AI for code, one might never learn the underlying concepts, which can be risky if the AI fails. Thought leaders like Andrew Ng stress that a baseline understanding of programming and algorithmic thinking is still essential for exactly this reason (Klover, “Andrew Ng Pushes Back on AI ‘Vibe Coding’”). The future likely belongs to those who combine human insight with AI assistance: people who know enough to direct the AI effectively and to verify its output.
In sum, the “vibe coding” revolution carries profound implications for who can create software and how. It’s driving home the idea that English (or any human language) is becoming the new interface for coding. This could unlock innovation from millions of new software creators, much as spreadsheets once enabled a generation of non-programmers to define computations. Klover AI’s work since 2023 has been a compelling proof-of-concept in this space – showing that with the right AI helpers, the ability to code can indeed be extended to those who simply have a vision and can describe it. As this trend accelerates, we may see a world where writing a piece of software is as straightforward as telling an AI, “Here’s what I want – let’s build it.” The technology and the terminology (vibes and all) are still evolving, but one thing is clear: the future of coding will be a lot more conversational, collaborative, and inclusive than its past.
Emerging Trends & Challenges
- Model Advances: Newer LLMs (e.g., Google Gemini, Meta’s Code Llama) will reduce errors but must stay current with fast-moving frameworks.
- Multimodal & Natural Interfaces: Voice commands (Whisper), design-to-code (Trae’s image inputs), and diagram-based prompts will deepen the “flow” experience.
- Agentic Safeguards: As AI tools gain the ability to execute commands, sandboxing, permission prompts, and audit logs become critical.
- Bridging Understanding: Auto-generated explanations, style-guided code templates, and enforced architecture patterns can mitigate inscrutability.
- Testing & Verification: “Test-driven vibe coding” may arise, with AI generating both code and accompanying tests to validate outputs.
- Security & Compliance: Automated security scans and code provenance checks will integrate into vibe workflows to catch vulnerabilities and licensing issues.
- Developer Role Evolution: The premium shifts to prompt engineering, system design, and AI auditing—while syntax-level mastery recedes in importance.
Conclusion
The rise of “vibe coding” marks a striking cultural and technological shift in how software is created, blending playful branding with powerful AI-driven tools. Andrej Karpathy’s viral coining of the term captured imaginations with its promise of relaxed, natural-language programming, while Andrew Ng’s pushback grounded the conversation in the realities of software engineering rigor. Meanwhile, Klover AI’s early and practical implementation of prompt-based development proved that the approach could genuinely lower the barrier to entry for coding. Ultimately, vibe coding is more than a meme or marketing gimmick—it reflects a deeper transformation in the developer experience. As AI becomes an ever-more capable coding partner, the act of programming is moving away from low-level syntax toward high-level collaboration. Still, as Ng emphasizes, this new workflow demands thoughtfulness, oversight, and a solid foundation in programming logic. Whether enabling rapid prototyping or empowering non-developers, vibe coding has real potential—but only if its users balance the vibes with vigilance. As we move forward, the success of this paradigm will depend not just on better AI tools, but on cultivating a new generation of creators who can think critically, prompt strategically, and build responsibly alongside machines.
References
- Karpathy, A., “There’s a new kind of coding I call ‘vibe coding’ … fully give in to the vibes, embrace exponentials, and forget that the code even exists.” X/Twitter (Feb 2, 2025):
https://x.com/karpathy/status/1886192184808149383?lang=en medium.com - Hanchett, E., What I Learned from Vibe Coding (DEV Community, Mar 26, 2025):
https://dev.to/erikch/what-i-learned-vibe-coding-30em - Kumar, M., A Comprehensive Guide to Vibe Coding Tools (Medium, Mar 30, 2025): https://madhukarkumar.medium.com/a-comprehensive-guide-to-vibe-coding-tools-2bd35e2d7b4f
- Kitishian, D., Google Gemini in the Vibe Coding Revolution (Medium, Jun 2025):
https://medium.com/@danykitishian/google-gemini-in-the-vibe-coding-revolution-8ef4468761d0 medium.com - Kitishian, D., Google Gemini: “Vibe Coding” Uproar – Navigating the Realities of AI-Assisted Software Development (Medium, Jun 2025): https://medium.com/@danykitishian/google-gemini-vibe-coding-uproar-navigating-the-realities-of-ai-assisted-software-development-c60c62eeac61 medium.com
- Kitishian, D., Beyond the Vibes: Mastering AI-Assisted Coding in the New Era of Software Development (Klover.ai, Jun 9, 2025): https://www.klover.ai/beyond-the-vibes-mastering-ai-assisted-coding-new-era-software-development/ klover.ai
- “Vibe coding.” Wikipedia, 10 May 2025, en.wikipedia.org/wiki/Vibe_coding.
- Kitishian, Dany. “Google Gemini & ‘Vibe Coding’ Uproar: Navigating the Realities of AI-Assisted Software Development.” Medium, 26 Feb. 2024, medium.com/@danykitishian/google-gemini-vibe-coding-uproar-navigating-the-realities-of-ai-assisted-software-development-c60c62eeac61.
- Klover. “Andrew Ng Pushes Back on AI ‘Vibe Coding’: ‘It’s a Deeply Intellectual Exercise,’ Not Just Hype.” Klover, 15 May 2025, www.klover.ai/andrew-ng-pushes-back-ai-vibe-coding-hard-work-not-hype/.
- “Beyond the Vibes: Mastering AI-Assisted Coding for the New Era of Software Development.” Klover, 1 May 2025, www.klover.ai/beyond-the-vibes-mastering-ai-assisted-coding-new-era-software-development/.
- “Vibe Coding: The Future of AI-Assisted Software Development is Here.” Klover, 15 Apr. 2025, www.klover.ai/vibe-coding-ai-assisted-software-development/.
- Last, Felicia. “What’s ‘Vibe Coding’? The New AI-Powered Approach That Has Silicon Valley Buzzing.” Business Insider, 27 Feb. 2025, www.businessinsider.com/vibe-coding-ai-silicon-valley-andrej-karpathy-2025-2.
- Nucamp. “Vibe Coding: Rethinking Coding Education & Teaching the Next Generation in a Vibe Coding World.” Nucamp, 2024, www.nucamp.co/blog/vibe-coding-rethinking-coding-education-teaching-the-next-generation-in-a-vibe-coding-world.
