How to Plan a Vibe Coding Project Before the AI Decides for You

You did not choose your database schema. You did not choose how login works, where the business logic lives, or why there are three different ways to fetch a user. The AI chose all of it, quietly, around your fourth prompt, and you said “looks good” because the screen worked. Now something is broken and you are trying to work out what your own app does. That is when builders discover the real question was never how to vibe code faster but how to plan a vibe coding project so the decisions stay yours. One long-time Cursor user described it well in a builder forum: the agent makes so many unannounced assumptions and architecture choices that, past a certain size, you are lost inside your own codebase. Fixing a bug stops being a normal edit and turns into an archaeology dig through decisions you never made.

What this problem looks like

The pattern that shows up again and again in builder forums has a shape. A developer with years of pre-AI experience described watching people begin with a fuzzy idea, hand the AI most of the structural choices, then pile patch on patch with no clear picture of what each one altered. Eventually the codebase becomes inconsistent and every new feature breaks something adjacent. Several people this developer knew spent months on this and quit.

A builder with a product-management background and no shipping experience built a large internal tool in a month and wrote down what they wished they had known on day one. The first item was not a tool or a model. It was: start with a product requirements document, break it into small steps, and decide what to build first.

A student team vibe coded an entire final-year project with nobody understanding the architecture. When the machine-learning piece silently stopped working, nobody could fix it, because nobody had decided how it was supposed to work. It only succeeded when one member rebuilt it with a plan. And when a working engineer complained that their AI agent’s code quality slid unless they reviewed everything, the replies were blunt: a one-line request for an entire SaaS gives the model no context, so a clean vibe coding architecture is not going to emerge from it.

Why the AI makes silent architecture decisions when you vibe code

This is a mechanism, not a flaw in the model. A coding agent is trained to finish the task in front of it. When your prompt leaves a gap, it does not stop for a design review; it fills the gap with the most common choice and moves on. Every unanswered question becomes a default: a table structure, a folder layout, an authentication approach.

Defaults are not bad on their own; the problem is that they are invisible and they compound. You see a working screen, not the twenty choices that produced it, and the next prompt builds on all twenty. When something breaks, the decision you need to reverse is buried under weeks of code that assumes it.

There is a second mechanism. The model’s context window, meaning the amount of conversation and code it can hold in mind at once, is finite. It does not remember why it made a choice a hundred prompts ago. If that reasoning was never written down, it does not exist for the model or for you. One developer’s warning was that once the human loses the thread, the AI follows soon after. This is the same force that produces the tangled codebase months in.

How to plan a vibe coding project properly

The fix is to move the decisions out of the AI’s head and into a document you can read, before code exists. Here is the order, in the Claude Code version; Cursor, Lovable and Replit have equivalents.

Step 1: Write a one-page spec before the first prompt

Call it a PRD if you like. It needs who the user is, the three to five things the app must do, what it does not do in version one, and what “done” looks like for each feature as a yes-or-no check. Then add the technical decisions you can make (database, hosting, login, paid tier or not) and write the rest as open questions. Vibe coding spec first does not mean you know everything; it means every open question is visible instead of silently answered by a default.

Step 2: Use Claude Code plan mode and read the plan

Claude Code plan mode makes the agent describe what it intends to do before it touches a file. Start every non-trivial feature there, then read the plan. A senior engineer who builds side projects from a phone without reading the code treats this as the phase that matters most, because decisions made here, good or bad, multiply downstream. If a section does not make sense, ask the agent to explain it. If the plan is too big to hold in your head, have it split into smaller plans.

While reading, hunt for the decisions being made on your behalf. Ask: “What new tables does this add? What existing code does this change?” Make the agent list every architectural choice with its alternatives; approve or change that list before any code is written.

Step 3: Put the decisions in CLAUDE.md so they survive

CLAUDE.md is a file in your project that Claude Code reads at the start of every session (Cursor uses rules files; other tools have an AGENTS.md or similar). Put the spec summary, the stack, and your conventions in it. The builder above added rules such as keeping business logic out of UI components only after their files became unmanageable. Write yours early. Add a line saying the agent must ask before adding a new table, a new dependency, or a new way of doing something the codebase already does. This is how a decision made today is still enforced next month, when the conversation that made it is gone.

Step 4: Build micro-features, one per session

Define one feature, explain how it fits the existing system, say what must not change, and review the result before moving on. Use a fresh session per feature. One useful trick: build the user interface first with fake data. It is a cheap way to confirm the AI understood the request, and it forces you to decide what data you need before the backend exists.

Step 5: Checkpoint with git and tests after every plan

Git saves your code at a point in time so you can return to it. Have the agent commit after every completed plan, or set up a hook that does it automatically. Every plan becomes a checkpoint you can roll back to, which is also your insurance against the AI deleting working code. Ask for a plain-English list of test cases in every plan, then have the agent write those tests; you need not read the test code, only confirm the list covers what matters. See how to test a vibe coded app. For anything complex, add sub-agent passes before implementing: one to critique the plan, one for security, one to audit the tests. It feels slow, and it is still faster than reverse engineering your own product in month three.

How a Red Corner CTO would have prevented this problem

Before the first prompt, a CTO would have sat with you for an hour and turned your idea into a page of decisions: the user, the core loop, the data model drawn as boxes and arrows, and the four or five choices that are expensive to reverse later, such as how identity works, how money moves, and where the data lives. They would have made those choices with you, explained the trade-offs plainly, and written them into CLAUDE.md so the agent inherits them every session. They would have insisted on git from the first commit.

During the build, the CTO would have read your plans with you, not your code. In the first weekly review they would have caught the agent inventing a second way to fetch users, or quietly adding a table that duplicates one you already had, and stopped it before anything depended on it. They would have set the rule that any new table, dependency or pattern needs a yes from a human, and been that human. They would have noticed when a plan got too big to hold in your head and split it.

Before launch, they would have asked the questions the agent never asks: what happens when two people edit the same record, what happens when the payment succeeds but the database write fails, which decisions are we stuck with once real data exists. They would have walked the data model once more, because schema mistakes hurt most after users arrive.

After launch, they would keep the plan alive. Every new feature gets a short plan, a checkpoint, a review. When something breaks, you open the spec and the decision log instead of guessing at the code, because you know why the system is the way it is. That is what owning your product, rather than renting it from the model, looks like.

Frequently asked questions

Do I need a spec to vibe code a small project?

For a weekend toy, no. One builder made a complete game for their child in an afternoon with one long prompt and no plan. Once other people will use the thing, or you expect to keep adding features for months, the plan becomes the cheapest work you will do.

Is Claude Code plan mode worth using for every change?

For any change that touches data, authentication, payments or more than one part of the app, yes. For a typo fix, skip it. The discipline is to read the plan when you use it; a plan you approve without reading is just a slower silent decision.

How do I vibe code properly if I cannot read the code?

Read the plans and the test case lists instead, and ask the agent to explain anything you do not understand until you could describe it to a friend. Understanding the system at a high level is what lets you steer. A CTO in the loop closes the rest of the gap.

Get a CTO in your corner

You do not need a computer science degree to plan a vibe coding project well. You need someone who has made these decisions before sitting next to you while you make them. Red Corner gives founders and builders real CTOs who review the plan before the code exists. Visit redcorner.io and get a CTO in your corner.