
TL;DR -Vibe coding is the practice of building real software by talking to an AI, in plain...
{% card %} **TL;DR -**Vibe coding is the practice of building real software by talking to an AI, in plain English, instead of writing every line by hand. The whole stack a beginner needs fits into four roles: a conversational AI tool for the rough draft, an AI-powered editor for the real work, a version control service to save progress, and a deployment service to put the project online. The human still picks what to build, judges whether the result is any good, and decides when it ships. The on-ramp is shorter than it has ever been.{% endcard %}
Vibe coding has become the shorthand for a way of building software that did not really exist three years ago. A person opens a conversation with an AI tool, describes what they want, gets working code back, and ends the session with something live on the internet. No bootcamp. No three-hour Homebrew install. No semicolon hunt at 2am.
This piece is for the software creator: the person who wants to build something useful, not someone trying to become a senior engineer at a megacorp. The advice differs depending on which path a learner is on, and the previous piece in this series sketched both. What follows is the practical shape of the software creator path, the tools that show up in it, and the moments where the human in the loop still really matters.
The best way to understand vibe coding is to walk through a real one. Let’s examine a site revamp: An experienced developer helped their partner, a cinematographer, replace his Squarespace portfolio with something built from scratch. He had no developer background.
The flow looked something like this:
The whole project took him a few weekends of conversation to get to a real website. No tutorial completed start to finish.
When a vibe coding session goes well, it looks just like this. The human is making decisions about taste, structure, and intent. The AI is handling the parts that used to take three hours of YouTube and a sympathetic friend.
The tool landscape can feel overwhelming when seen all at once, partly because the same task can be done in five different products. The simpler way to navigate it is by job. A vibe coding workflow generally pulls one tool from each of these four categories:
A workflow can use one tool per row, four total. That is really all the infrastructure that your first project needs.
A Note: The differences between the leaders in each tool category are small enough that a beginner will not feel them. Familiarity, free tiers, and whatever a friend already uses are reasonable tiebreakers. The right tool is mostly the one that actually gets used.
Vibe coding sometimes gets caricatured as the user typing “build it” and the AI building it. The reality is more collaborative, and the moments that require human judgment tend to cluster in three places.
To begin with, the AI cannot read your mind, so the quality of the first prompt shapes everything that follows. “Build me a portfolio site” is a workable starting point. “Build me a portfolio site for a cinematographer with a dark theme, full-bleed video on the landing page, a project grid that filters by year, and a contact form that emails me directly” gives the AI much more to work with and produces a much more useful first draft. Specificity is the entire skill.
Next is at the breakage point. AI assistants are very good at writing code that works on the first try most of the time. They are less reliable at catching when something subtly does not work. Examples include: A login that lets anyone in; a database connection visible to the public; a form that quietly fails on phone keyboards. These failures look like working code…until they don’t. Asking the AI to audit its own work, after the fact, with prompts like “what would a senior developer change about this?” or “walk me through the security of this database connection,” catches a good portion of these issues before they hit anything real.
Finally, AI can only offer you options – it can’t make decisions for you. What gets built next? What stays in scope? What is good enough to ship? You have to decide what matters.
Here’s your next move: Open a free account at any of the conversational AI tools mentioned. Ask it to build a simple version of something small and personal: a one-page site, a photo renamer, a tracker for whatever the reader is currently tracking on paper. Talk to it the same way one would talk to a patient friend. Ask follow-up questions when the response does not make sense. Save the project to GitHub when it works. Push it to the internet when it feels real.
The shape of software development has changed. The on-ramp is dramatically shorter, and the number of people who can credibly call themselves builders is about to grow by an order of magnitude. For someone just starting out, the question worth dwelling on now is what to build. The other questions sort themselves out from there.
MLH hackathons are a good place to bring that first project into a room of people doing the same thing. DEV is a good place to write about what got built once it ships. The build happens privately. The learning happens in public.
{% details Is vibe coding actually coding? %} Depends on the definition. The person doing it ends the day with working software that runs on real infrastructure, which is the part most people care about. The activity looks more like directing than typing. Many working developers now describe their own day-to-day this way.{% enddetails %}
{% details Do I need to know any code before I start? %} No. The cinematographer in the example above did not. What helps is being specific about what is wanted and patient about asking follow-up questions when the AI does something unexpected. Knowing a little code makes it easier to audit the output later, which matters more for anything handling real user data.{% enddetails %}
{% details Is the code any good? %} It is usually functional. It is sometimes great. It is occasionally subtly wrong in ways that matter. Code that handles passwords, payments, or personal information deserves a second look from someone who knows what to look for. Code that renames files in a folder probably does not.{% enddetails %}
{% details What happens when I get stuck? %} Most beginners stall in one of two places: a feature that will not work no matter how it gets reprompted, or a deployment step that throws an error message in unfamiliar language. The fix for the first is usually to restart that part of the conversation with a more specific prompt. The fix for the second is to paste the exact error message back into the AI and ask what it means. Search engines, the DEV community, and an MLH event are also genuinely useful at this point.{% enddetails %}
{% details Is this how real developers work now? %} Many of them, yes, at least for parts of the job. Senior engineers tend to use AI as a collaborator for unfamiliar territory and a multiplier for familiar territory. The skill that distinguishes them from beginners is knowing when to trust the output and when to dig deeper. That skill is learnable, and it develops through practice.{% enddetails %}
{% details How much does vibe coding cost? %} Most of the conversational AI tools have generous free tiers that are enough for a first project. GitHub is free for public repositories and most personal use. Cloudflare Pages, Render, Vercel, and Netlify all have free tiers that cover small sites. A custom domain costs roughly ten to fifteen dollars per year. A learner can ship a real first project for the price of a domain name and nothing else.{% enddetails %}
{% details Should I still learn to code the traditional way? %} That depends on the goal. Someone aiming for a software engineering career will benefit from foundations: a real language, the basics of how computers actually run code, some experience reading code written by other people. Someone who just wants to build a thing that solves a problem in their own life can probably skip that, at least at first. The previous piece in this series breaks out both paths in more detail.{% enddetails %}
aiMost of us have seen a coding agent fail to complete a task we know it can do. We just don't...
googlecloudWhen building Generative AI applications, developers often encounter a massive bottleneck: sequential...
discussI’ve been thinking about sharing some electronic circuit posts on Dev.to — small circuits, DIY...
agentsWhat nobody tells you about exporting your multi-agent prototype to a local workspace. Every...
agenticarchitectAutonomous agents are genuinely good at answering messy business questions. Give one an LLM and a set...
aiPR volume went up, ticket quality didn't, and the gap got filled with LLMs on both sides of the review: bots reviewing, bots replying, bots occasionally arguing with bots about priorities that only existed in a teammate's head. Our CEO named the actual problem, and it's bigger than code review.
Workflows from the Neura Market marketplace related to this Stable Diffusion resource