Not all vibes aregood.Vibe codingImage byAuthorAre you wondering WTF all this vibe coding stuff is thats been sweeping your social feeds? You probably get the gist that its about having a vision of an app or software you want to build and vibing your way into it with the help of an AItool.If youre an old-school coder like me, you might be laughing a bit at the idea that you can just blink software into realityespecially when you think about all the blood, sweat, and tears it traditionally takes to build excellent products. Its like a joke that it can suddenly be soeasy.Well, stop laughing. Vibe coding is real, and in this article, Ill explain it and break down how its changing how we imagine, build, and grow products and companies going forward. Ill also make a case for embracing vibe coding without losing your soul, including four frameworks to optimize your success with the good vibes from creating genuinely helpful, well-crafted software andapps.Same cycle, newvibeVibe coding is also just one more example of what I call the Great Democratization Cycle. Weve seen it in photography as it evolved from darkrooms to digital cameras, which eliminated film processing, to smartphones and Instagram filters, making everyone a high-end photographer. The same goes for publishing (from printing presses to WordPress), video production (from studio equipment to TikTok), and music creation (from recording studios to GarageBand on a laptop and now AI tools like Suno on your smartphone).Each wave democratized image creation while simultaneously changing what it meant to be a professional in thefield.Software development is in no way exempt. Weve come a long way from traditional coding (1970s-2010s), which was expert-driven and hard to get into. From the low-code/no-code movement (2010s) to AI-assisted development (early 2020s; i.e., Github Copilot), the path to easy software development has accelerated to where we find ourselves today: vibe coding. Thanks to platforms like Windsurf, Cursor, LoveableDev, and Replit, anyone can take their app or software idea to execution withinminutes.However, its not that simplenot for the non-technical entrepreneur who feels empowered or the veteran developer who feelsdissed.The seduction of simplicityLet me take you back to my first coding project. As a pimply-faced teen in my parents basement, I spent countless sleepless nights wrestling with syntax errors, debugging mysterious crashes, and finally experiencing that incomparable rush when my creation actually worked. The journey was killer, but it shaped my understanding of how software fundamentally operates.Fast forward to 2025, and were witnessing a revolution called vibe codinga term popularized by AI researcher Andrej Karpathy thats taken the tech world by storm. The premise? Simply describe what you want in natural language, and AI generates the code. No more syntax struggles. No more Stack Overflow deep dives at 2 AM. Justvibes.Its intoxicatingly easy.I recently tested this myself. I prompted CursorAI, an AI-enabled IDE (integrated development environment), and built an app called DaddyTime that helps discover new cool things I can do with my son (hesthree).Within 30 minutes, I had a fully functional progressive web appthat:Image byAuthor.Connected to local events in myareaIntegrated with a weather service (to suggest indoor or outdoor activities)Correlated ideas with localweatherIntegrated with my Google calendar for bookingeventsThe entire process took less than 30 minutesno coding required, just a conversation with anAI.This isnt an exaggerationits our new reality. And thats precisely what worriesme.The craftcrisisThis AI-driven accessibility is undeniably powerful. Designers can prototype without developer dependencies. Domain experts can build tools to solve specific problems without learning Python. Entrepreneurs can validate concepts without hiring engineering teams.But as we embrace this new paradigm, we face a profound question: What happens when we separate makers from their materials?Consider this parallel: Would we celebrate a world where painters never touch paint, sculptors never feel clay, or chefs never taste their ingredients? Would their art, their craft, retain itssoul?When we remove the intimate connection between creator and mediumin this case, between developer and codewe risk losing something essential: the craft. And its not just about producing working software. Itsabout:Understanding systems at a fundamental level, which allows you to solve problems when things inevitably breakCreating elegant, maintainable solutions that stand the test oftimeBuilding mental models that inform higher-level architectural decisionsDeveloping an intuition for performance, security, and edgecasesA Microsoft engineer was brutally honest about AI-generated code, stating that LLMs are not good at maintaining or extending projects over time and often get lost in the requirements and generate a lot of nonsense content.This isnt surprising. AI excels at mimicking patterns but lacks the deeper understanding that comes from years of hands-on experience. It can produce code that works initially but falls apart under pressure.As one tech CTO warned, overreliance on AI can lead to hidden complexitiesquick fixes that become unmanageable during scaling or debugging. The 75% that AI solves quickly often leaves the critical 25%making code production-readya looming challenge.And dont even get me started on the security risks this poses. You could be a few clicks away from leaking all your data by signing up for some cool thing that popped up in your IG feed. Thats not a vibe, isit?Beyond technical debt: creativedebtTheres something even more concerning than technical debt lurking in our AI-coded future: creativedebt.True innovation often emerges from constraints and deep domain knowledge. When you wrestle with a programming languages limitations, youre forced to think creatively within boundaries. This tension produces novel solutions and unexpected breakthroughs.When we remove this friction entirely, we risk homogenizing our solutions. If everyone asks AI for a responsive e-commerce site with product filtering, well get variations on the same themetechnically correct but creatively bankrupt implementations that feel eerilysimilar.The danger isnt just bad code; its boring products and AIslop.The knowledge gapwidensVibe coding creates two distinct tracks for engineers:Those who understand the foundations and can wield and direct AI effectivelyThose who depend entirely on AI outputs without comprehending whats happening under thehoodThis bifurcation has serious implications. When problems ariseand they willthe second group will be helplessly dependent on AI to fix issues it may have created in the firstplace.What happens when the AI cant solve the problem? Who do we turn tothen?Image meme viaReddit.As The Guardian aptly observed, Now you dont even need code to be a programmer. But you do still need expertise. This expertise gap will only widen as more people build software without understanding its inner workings.The swiss army knife imperativeRecent headlines confirm a troubling trend: Amazon plans to terminate over 14,000 managerial positions to save $3.5 billion annually. Meta, Microsoft, and countless others are making similar moves. The message is clearoperational efficiency is king, and specialization is becoming aluxury.This streamlining creates a new mandate: everyone must become a Swiss Army knife ofskills.Vibe coding accelerates this transformation. When anyone can generate functional code through conversation, the specialization that once protected technical roles evaporates. The implications ripple through organizations:Product managers cant hide behind documents and wireframestheyll need to generate working prototypesDesigners cant simply hand off mockupstheyll need to implement theirdesignsMarketers cant request custom toolstheyll build their own analytics dashboardsExecutives cant claim technical ignorancetheyll need to understand the systems theyoverseeThis isnt just speculation. Amjad Masad, CEO of Replit, revealed that 75% of Replit customers never write a single line of code already. The future is arriving faster than wethink.In this new landscape, value shifts dramatically from technical implementation to problem identification. As one entrepreneur noted, If you have an idea, youre only a few prompts away from a product. The bottleneck is no longer development speedits knowing which problems are worthsolving.Mental models for the vibe codingeraTo navigate this shift, we need new mental models. Here are four frameworks Im using to make sense of the vibe coding revolution:1. The creation-maintenance divideVibe coding excels at creation but struggles with maintenance. This creates a fundamental split:Creation: Easy, accessible, democraticMaintenance: Complex, requiring deep expertise, increasingly valuableSmart organizations will develop dual skillsetsrapid vibe coding for prototyping and proof-of-concepts, alongside rigorous engineering practices for production systems.2. The three tiers of softwarecreatorsAs coding barriers fall, a new hierarchy emerges:Prompt Engineers: Those who use AI to implement existingpatternsSolution Architects: Those who combine AI capabilities in novelwaysSystem Innovators: Those who create entirely new paradigms AI hasntseenYour value as a software creator will increasingly depend on moving up thisladder.3. Intellectual leverage vs. Execution leverageTraditional software provided execution leverage, automating repetitive tasks. Vibe coding gives us intellectual leverage, automating thinking itself. This means the highest-return activities shift from building things right to building the rightthings.4. The specialization paradoxAs tools become more powerful, success depends less on specialization and more on synthesis. The most valuable person isnt the deep expert in a single domain but the connector who understands multiple domains well enough to identify novel intersections.Finding the balance: augmentation, not replacementIm not suggesting we abandon AI-assisted codingthat would be like rejecting power tools in favor of hand saws. But we need to approach this revolution thoughtfully, preserving craft while embracing innovation.Heres what Ipropose:For individual creators:Learn the fundamentals first. Build a strong foundation in programming concepts before relying heavily on AI. I refuse to hire engineers who cant code without anLLMUse AI as a collaborator, not a replacement. Let it handle boilerplate while you focus on architecture and novel features.Understand what the AI produces. Take time to read and comprehend generated code before implementing it.Challenge AI outputs. Instead of accepting the first solution, ask, Is there a betterway?Develop T-shaped expertise. Deep knowledge in one area, with broad understanding acrossmany.For teams and organizations:Establish robust review processes for AI-generated code. Dont skip quality assurance just because AI wroteit.Create balanced teams with both AI enthusiasts and traditional craftspeople who can provide valuable checks and balances.Invest in education that emphasizes system thinking and architecture, not just prompt engineering and vibecoding.Document diligently. With less human-written code, thorough documentation becomes even morecrucial.Restructure around problem spaces, not technical specializations.For the community:Value and celebrate craftsmanship. Lets not lose sight of the artistry in well-crafted code.Develop ethical frameworks for responsible AI coding that preserves innovation while mitigating risks.Share learning resources that combine AI tools with foundational programming knowledge.Create new certification paths that validate understanding, not just implementation ability.Distribution: the new cheat code and businessmoatWhile we debate craft versus convenience, vibe coding has another dimension that deserves attention: the democratization of distribution.Pieter Levels, the indie hacker behind Nomad List and a dozen other profitable solo ventures, recently dramatically demonstrated this shift. Using vibe coding techniques through CursorAI, he built and launched RemoteOK Jobs 2.0 in just six hours, then shared the entire process on socialmedia.Levelsio twitter profile image fromXI had the idea at breakfast, he posted. By dinner, it was live with 5,000users.This isnt just fast developmentits a fundamental collapse of the creation-to-market timeline. When Levels built his first successful product in 2014, it took him weeks of coding. Now, with AI assistance, hes compressing that cycle to less than a day while reaching audiences in the millions.The implications are profound:The idea-execution gap vanishes. When you can go from concept to working product in hours instead of months, more ideas get tested in thewild.Audience trumps technical complexity. Levels success isnt primarily about his coding skillsits about his deep understanding of his audience and distribution channels. He knows exactly who hes building for and how to reachthem.Marketing > Building. As Levels bluntly said: I spent 20% of my time building and 80% telling people about it. That ratio used to be reversed.This hints at a future where technical implementation is so streamlined that distribution becomes the primary differentiator. The winners wont necessarily be those who build the best product in a technical sense but those who make the right product for a specific audience and get it in front of that audiencefastest.For entrepreneurs, this means investments in audience building, community development, and marketing channels may yield higher returns than investments in technical infrastructure.For larger organizations, it means the teams that understand customers and distribution will increasingly drive product development, not the other wayaround.In this brave new world, the greatest advantage goes to the creators whocombine:Deep audience understandingRapid implementation through vibecodingEstablished distribution channelsA willingness to launch fast and iteratepubliclyThats a very different skill set than what created tech success a decade ago, and it favors domain experts, community builders, and audience cultivators over traditional technical specialists.Disrupting the disruptors: no-codes no-future?Perhaps the most fascinating second-order effect of vibe coding is how it threatens to make the no-code/low-code movement obsolete almost overnight.For the past decade, platforms like Webflow, Bubble, and Airtable have carved out a valuable middle ground: visual interfaces that let non-developers build functional software without coding. These platforms found product-market fit by eliminating the need to write code while still requiring users to understand logical structures and workflows.Vibe coding leapfrogs this paradigm entirely. Why learn a proprietary visual interface when you can simply describe what you want in plain language?This disruption of the disruptors creates cascading effects:No-code platforms must evolve or die, likely by integrating AI to become AI-enhanced no-code.Visual programming becomes a transitional technology rather than the end-state many predicted.The value shifts from tools to prompts and patterns, creating new opportunities for prompt marketplaces and pattern libraries.Traditional developers and no-code creators increasingly compete in the samespace.The survivors will be those who recognize that the true value lies not in the implementation method but in a deep understanding of human problems and creative solutions.A call for thoughtful evolutionPeople have always created the most compelling software with vision, empathy, and a deep understanding of human needs. AI can help us execute that vision more efficiently but cant replace the human spark that drives genuinely transformative products.Consider that what separates good products from great ones is rarely technical perfectionits the human touch, the careful consideration of edge cases based on real-world experience, and empathetic design that anticipates userneeds.As Karpathy himself noted, vibe coding isnt about abandoning thoughtits about thinking at a higher level: I just see stuff, say stuff, run stuff, and copy-paste stuff, and it mostly works. The key word is mostly. The gap between mostly works and delights users is where human creativity and craft still reignsupreme.So, the question is: Will we use AI to amplify human creativity, freeing us from drudgery so we can focus on innovation? Or will we surrender our craft entirely, becoming mere prompt engineers orchestrating increasingly generic software?The choice isours.For my part, Im embracing AI as a powerful collaborator while fiercely protecting the craft that drew me to this field. While good vibes might get you a working prototype, its the marriage of human creativity with technological tools that creates truly extraordinary products.Not all vibes are goodbut with intention and care, we can ensure that the products we build in this new era combine the best of both worlds: AI efficiency and human ingenuity.The code of the future shouldnt just run. It shouldsing.Cracking the code of vibe coding was originally published in UX Collective on Medium, where people are continuing the conversation by highlighting and responding to this story.