How vibe coding proved that AI really can simplify real life
Every time someone opens an AI chatbot on the subway or at the grocery store, a lot of people still feel that itch: have we forgotten how to think on our own? Couldn’t we just do a normal search and calmly interpret the results? At the same time, the numbers tell a different story: a good chunk of people are already talking to AI systems several times a week and have built that into their routine, whether for work, study, or pure digital improvisation.
Within this context, a new practice has popped up and started turning heads: vibe coding. The idea is simple but powerful: people who are not programmers use AI models to build hyper-specific apps and websites focused on a single real-life problem. No massive platforms, no app with millions of users. These are microapps, almost like digital crafts, built to solve very concrete things: organizing a wedding, managing a workout routine, coordinating family tasks, or automating some annoying detail in professional life.
Instead of reinforcing that classic fear that AI will make everyone lazy, vibe coding points to a different path: technology as a tool to expand what regular people can do, helping turn ideas into functioning software even when the person building it has never managed to finish a programming course in their life.
From failing computer science to building useful apps with AI
A clear example of this shift is the story of Shayan Mirzazadeh. In college, he failed computer science twice. It looked like one of those classic cases of someone who would always have to depend on others whenever something more technical came up. But years later, in his early 30s and working as an account manager, Shayan started using AI to do exactly what he couldn’t pull off in college: get apps off the ground.
He started vibe coding very practical solutions, both for work and home. One of the projects was an app to help his fiancée track Pilates class and training flows. Instead of endless spreadsheets, he built, with AI’s help, an interface that actually matched her real routine: schedules, groups, notes, all organized in a way that made sense for the couple.
Shayan jumped into this alongside a coworker, Jayne Ingram-Roberts, who also treats vibe coding as a fun side quest. She created, for example, a fantasy-league-style app to follow the reality show Big Brother, aimed at friends who love the show and wanted to play with points, predictions, and custom rankings.
The pair’s most ambitious project is Seatbee, a website for creating wedding seating plans. The motivation came from a very real pain point: Jayne had struggled to organize the table layout for her own wedding two years earlier. With AI acting as a technical partner, they built a tool where users define clear rules such as:
- All my coworkers have to sit together
- My sister and that uncle who drinks too much need to be on opposite sides of the room
After setting these rules, the person hits generate and the system automatically creates a proposed table layout. If something doesn’t make sense, they can tweak it and try again. According to the creators, Seatbee has already passed 200 users, which is quite significant for a totally niche, hobby-built app.
This is a good snapshot of the vibe coding spirit: specific, usually small projects that have no ambition to take over the world. In many cases, the creators even lose money but gain fun, learning, and the satisfaction of solving a concrete problem that, for them, is worth a lot.
The turning point: when AI actually started coding
This shift didn’t come out of nowhere. Developer and writer Paul Ford points to an important milestone: the end of 2025. Up to that point, AI models could spit out a code snippet here and there, but the results were unstable. The machine needed a lot of hand-holding: whoever was on the other side had to know how to code reasonably well, understand errors, debug, and rebuild key parts of the system.
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What changed was the arrival of models designed specifically for code, launched by big AI companies. Among them, standouts include:
- Claude Opus 4.5 from Anthropic
- Gemini 3 from Google
- GPT‑5.1 from OpenAI
These models became capable of doing something much more complete: writing code, running it, identifying bugs, trying to fix them on their own, and repeating the cycle until they got something functional. We’re not just talking about generating text, but about driving a small end-to-end development process within well-defined limits.
This matters because in code, the test is objective: either the program runs or it doesn’t. If it compiles, executes, and delivers the expected result, it counts, even if the code is not the masterpiece a senior engineer would write. As Ford himself puts it, the computer doesn’t care if the code is elegant or full of hacks. It cares if it works.
This binary criterion builds a level of trust that just doesn’t exist in the same way for AI-generated text or images, where beauty, clarity, or style are subjective. In vibe coding, if the app does what it promises, the tool did its job.
Hands-on learning instead of blind dependence on AI
A common criticism of chatbots is that they can weaken critical thinking and reduce user autonomy, both at work and in school. In some contexts, that makes sense: people who outsource everything to AI risk unlearning basic things.
In vibe coding, though, the movement is a bit different. Instead of replacing reasoning, AI turns into a kind of power tool: you feed in the raw idea, shape it, tweak the output, refine what comes out. One study compares this process to ceramics. The contact with the clay, the feel of the material, is part of the artisan’s thinking. With code, manipulating, testing, breaking, and fixing the program blends into skill-building and intention.
Vibe coders interviewed in recent projects reported exactly that: they learned programming language concepts they had never seen before, started to understand what a deploy flow is, how an app actually gets online, and what it means to debug an error. Jonathan Butler, a 56‑year‑old entrepreneur who used to depend on others to build websites, compares the experience to being in a woodshop, making something with his own hands. His latest project is using vibe coding to organize the construction process of his new house.
In the end, anyone who digs a little deeper into this game comes out not just with a finished app, but with real notions of programming and architecture, even at a beginner level. AI is not a shortcut to skip understanding; it’s a push to get through the most frustrating part of the learning curve.
Hyper-niche software instead of giant platforms
Another reason vibe coding is interesting is its focus on tiny, hyper-specific problems. While the corporate world usually chases scale, margin, and growth, these microapps are born from a different question: what annoying little thing in my routine can I get rid of today?
A traditional corporate app tries to serve thousands of companies and ends up turning into a bloated Swiss Army knife, with endless menus, features few people use, and often paywalls that lock the one feature users actually liked. A vibe‑coded app goes the opposite way: it starts from one person’s problem, or a very small group’s problem, and delivers a solution sized exactly to that problem.
A few real examples show this well:
- Healthcare and family care apps created by people who live with seniors, people with dementia, or patients in treatment, organizing medication, schedules, warning signs, and small daily logs.
- A homegrown system for hiring babysitters and drivers that helped a father organize school escorts and pickup and drop-off schedules in a way no generic platform could match.
- A smart grocery list built by a firefighter named Joe Poynton that organizes supermarket items based on aisle locations, saving time between shifts.
These tools would almost never be launched by a big company because the audience is too small to justify a full product. But for the people who use them, they’re game changers. It’s a way to bring software into the daily lives of people who, until now, were just passive consumers of generic apps.
Vibe coding as a gateway for people who always felt excluded from tech
Vibe coding also plays an important inclusion role. Software engineers Maya Miller and Chloe Garden lead the SiSTEM Collective, a New York–based community focused on Black and Latina women in tech. Part of their work is organizing workshops for nontechnical people, showing in an accessible way how to use modern tools.
In one of these sessions, the theme was exactly building apps with AI’s help. Participants walked in with a raw idea and walked out with a working prototype. There were about 30 women, including some total beginners who had never really dealt with code.
Two projects stood out: microapps to track hair-washing routines. The users wanted to record which products they were using, whether those were helping with haircare goals like growth, strength, or elasticity, and notice over time what worked best. It’s the kind of super-personalized software, with fields, reminders, and metrics that would be very unlikely to appear in a generic, ready-made tool.
This kind of experience directly connects tech to real life. It’s like finally fixing that eternal leak in the sink or setting up a clear schedule for who feeds the cat each day, avoiding that infamous double dinner. Small things that never make headlines but make a huge difference for peace of mind.
A future where anyone publishes their own microapps
Developer Kyle Jensen, who works with entrepreneurship programs at Yale’s School of Management, has also joined this movement. He has vibe coded an SAT prep app for his son, research tools for his wife, and custom search systems for colleagues.
In his view, there’s an explosion of interest in this type of creation, especially in management and business circles where lots of people understand problems deeply but know little about code. For Jensen, this points to a near future where regular people, without the dev label, will launch and update apps frequently, much like they already build complex spreadsheets or simple automations in online services today.
This scenario also changes how society sees AI. Instead of being just another chat interface to answer emails or generate summaries, it becomes a building tool. Paul Ford sees vibe coding as a way to give some tech control back to people who don’t want to spend all day chatting with robots but do need to build something concrete for work and life.
When the reporter becomes a weekend vibe coder
To better understand this universe, the original article’s author decided to try it herself. She had a very specific big-city problem: two supermarkets near her home, but one of them sat at the top of a serious hill. The idea was simple: compare weekly deals from both stores and decide, with some logic, when it was worth climbing the hill.
She tried to build, with an AI model’s help, a system to extract offer information from the weekly flyers in PDF format. The result: she discovered that supermarkets are still, unintentionally, a sector resistant to AI. Scraping old, poorly formatted PDFs is still hard even for advanced models.
Even so, the process wasn’t a waste. In trying to solve the problem, she learned a lot about how data scraping works, what techniques exist to decode messy documents, and what practical limitations still show up.
On top of that, there was another important lesson: how to talk to AI. At first, she treated the model like a newsroom colleague, using metaphors, long context, and very open-ended suggestions. Little by little, she realized she needed to be more specific, break down tasks, and explain step-by-step what she wanted the code to do.
In the end, the original plan of automatically comparing the flyers didn’t work. But in a true startup spirit, she pivoted the project. Together with the AI, she created an app that helps decide whether a promotion is worth the extra walk up the hill: the person enters the discount, base price, maybe a few other variables, and the app says whether the physical effort is worth the financial benefit.
Is it a kind of silly app? Definitely. Will it become a unicorn? Of course not. But her answer is straightforward: I’m going to use it. And for anyone who wants to save on cheese without suffering too much on the way back, that’s more than enough.
Bringing back the handmade internet, now with AI backstage
After talking to several vibe coders and testing it firsthand, the lingering feeling is that we’re going back to a more decentralized, weird, and fun internet. Not a web dominated only by a few giant platforms, but the old-school one, full of quirky personal sites and useless apps that did nothing but send the word Yo to your friends or simulate a beer being drunk on your screen.
This time, though, the improvisation comes with more technical muscle because AI is carrying the heavy load. At the top, tough discussions continue about the environmental impact of data centers, concentration of power, and the effects of automation on work. None of that disappears with vibe coding. But at the base, you can see millions of regular people using AI in a more authorial way, to solve problems that are uniquely theirs and to put their own vibe into the software they use.
In the end, vibe coding reveals a more human side of artificial intelligence: less hype about total economic revolution, more tailored tools for people who just want to organize their lives better, add a bit of fun to boring daily processes, and discover along the way that they’re also capable of building technology, even if they flunked that programming class back in the day.
