Made an app via prompts. Now what?
You open Lovable, Bolt, v0, Replit Agent, or a similar platform. You type: “create an app to organize my study routine, with login, a dashboard, and a task list”. The tool thinks, installs things, generates screens, writes code, opens a preview, and suddenly it looks like software.
That moment is addictive because it feels like you skipped months of learning. And to be fair, there is real value there. For the first time, PMs, designers, founders, QAs, and junior devs can turn an idea into something clickable without starting with project setup, boilerplate, or terminal anxiety.
But this is the most important line in the session: preview is not production.
An app that opens in the browser can still have broken access rules, exposed secrets, fragile flows, unmaintainable code, odd dependencies, no tests, and an architecture that only works while the project is tiny. The flex is not generating something in 30 minutes. The flex is being able to maintain it tomorrow.
What vibe coding is
Vibe coding means creating software by describing intent in natural language and letting AI generate a large part of the code. The term became popular after Andrej Karpathy described a way of programming where you follow the “vibe”, talk to the agent, accept changes, paste errors back, and let the code grow without manually writing every line.
Plain English version: you say what you want, AI tries to build it, you inspect the result, ask for changes, run it again. It is less “I write every line” and more “I direct the outcome”.
That is not automatically bad. Vibe coding is great for:
- getting an idea out of your head and onto the screen;
- creating clickable prototypes for user conversations;
- learning by reading generated code and asking for explanations;
- testing product flows before spending engineering sprint time;
- building simple internal or disposable tools.
If you do not understand the code, have not reviewed data access, have not tested permissions, and do not know how to roll back, you do not own the software yet. You have a demo with confidence.
Why it feels like it works so well
Because prototypes have a different bar. A prototype needs to show intent. It does not need to survive traffic, audits, payments, privacy requirements, fine-grained permissions, and two years of maintenance.
It also works because many apps repeat patterns: login screen, list, form, dashboard, CRUD, filters, sidebar, table. Models have seen a lot of similar code and can recombine those patterns extremely fast.
This changes the game: you do not need to wait until you “know everything” to play with product ideas. You can build, break, ask, compare, and learn in the loop. Just do not skip understanding. AI accelerates feedback. It does not replace fundamentals.
How this connects to the next sessions
In this session, you are getting the vocabulary to avoid falling for marketing. Next, we go deeper:
- Session 2: Tools and models shows how to choose between AI IDEs, CLIs, cloud agents, and task-fit models.
- Session 3: SDD and Harness Design shows how to turn intent into a verifiable contract and operate agents with context, validation, and governance.
Quick term search
Use the search below as a pocket map. The goal is not to memorize jargon; it is to understand enough to ask better questions.
A computer program trained to read and write text. You send a question, it generates an answer.
The trained "brain" that processes text. Different models have different capabilities, speeds, and costs.
The act of asking the model to generate a response.
A chunk of text the model processes. It can be a word, part of a word, or a special character.
Everything the model can see while generating an answer: your prompt, chat history, system instructions, files.
The text you send to the model. It can be a question, a request, an instruction, or all of that together.
Initial instructions that shape how the model should behave. A briefing before the conversation starts.
Creating software by describing what you want in natural language and letting AI generate a large part of the code.
A platform that turns a description into a functional app with screens, code, preview, and sometimes deploy.
An early version used to test an idea, flow, or interface before treating it as a final product.
The starting structure of a project: folders, files, config, and base code.
A temporary view of the app running in the browser so you can test it quickly.
Publishing a version of the app to an environment other people can access.
An isolated environment where AI or the app can run without directly touching your main environment.
A request to review and merge code changes into a main branch.
The comparison showing exactly which lines were added, removed, or changed.
A clear description of what needs to be built, for whom, with which rules and limits.
Checking whether what AI generated works, matches the request, and does not create risk.
Taking responsibility for the code, even when AI generated it.
A shortcut that makes the project faster today and more expensive to change tomorrow.
Database rules that control which rows each user can view or change.
The code editor where you write software. VS Code, Cursor, and Windsurf are examples.
Command-line interface. You type in the terminal and get text back. Tools like Claude Code run this way.
AI suggests the next piece of code while you type. Like phone autocomplete, but for code.
The project information AI uses: open files, folder structure, dependencies, types, tests.
A program that uses AI to make decisions and take actions, not just answer questions.
An agent specialized in writing, editing, and reviewing code. It can access your project directly.
A standard that lets AI tools connect to external services in an organized way. Kind of like USB for AI tools.
The complete work system around an AI agent: instructions, tools, rules, context, and validation.
Takeaway
- Vibe coding is great for starting, learning, and prototyping. It is not an excuse to stop understanding.
- Prompt-to-app platforms move fast, but they make technical choices for you.
- Preview is not production. Generated code needs a spec, review, tests, and an owner.