How to plan your first vibe coding project in 5 steps

Imagine asking an AI for an equipment-request tracker. It gives you a tidy dashboard but leaves out the manager’s approval. The app looks ready, but your team’s decision is still being made over email.

When planning your first vibe coding project, start by describing the work you want to improve. You don’t need a software background to describe a process you know. You do need to explain what the app must do before asking AI to build it. By the end of this guide, you’ll have a one-page project brief that outlines what belongs in the first version and what needs to be answered before anyone relies on it.

Plan the work before you ask AI to build it

Scope and planning, as covered in Ziplines’ Vibe Coding course, come before creating, testing, and sharing. First, decide whether you’re exploring an idea with a prototype or preparing a tool colleagues will use for actual work. That choice affects the data and ongoing responsibilities your plan must cover. Keep a document open as you go so you can collect these decisions in your brief.

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Step 1: Define the job and the person who needs it

Name the work that needs to change. “An equipment-request app” says what you might build, but leaves the reason for building it unclear.

Consider a fictional team that requests equipment by email. A manager approves purchases, but team members have to follow up to find out whether their requests have been reviewed or approved. They need a way to track the manager’s decision. This example will carry through the rest of the guide.

Use a job statement to connect the person, the moment, and the outcome:

When [situation happens], [person] needs to [complete a task], so they can [reach an observable result].

For this team: “When someone requests equipment, they need to see whether their manager has approved it or asked for more information, so they know what to do next.”

Then check the statement against today’s work:

• Where does the request go now?
• Who makes the decision?
• What does the requester have to chase down afterward?

Your understanding of the work gives you a starting point. If colleagues will use the tool, ask someone who submits or approves these requests to correct your description. If you’re its only user, trace a recent instance yourself.

Before moving on, check that you can explain the problem and the change you want without listing screens or software features.

Step 2: Map one complete workflow in plain English

What happens between submitting a request and knowing the answer? Write down that path and who acts at each point. A few sentences, a sketch, or a table can work; choose whichever makes the handoffs easiest to follow.

For the fictional team, the first draft of the workflow looks like this:

Next, walk through an ordinary exception. Someone requests a monitor but leaves out why they need it. Can the manager return it with a comment? Decide how the requester adds an answer and when the request goes back for review.

That return path belongs in the plan. You don’t need to catalog every unusual situation, but this one determines whether the main task can be finished. Add “returned for details → requester updates → manager reviews again” to your workflow.

Check the handoffs

Keep purchase and delivery separate if your project only covers approval. In this example, an approved request means the manager has agreed to it; ordering equipment remains part of the team’s existing process.

Read the path to a colleague. At each handoff, they should be able to say who’s responsible next and what information that person receives. If you have to improvise an answer, add it to your notes.

Step 3: Cut version one to the smallest useful outcome

A spending dashboard sounds useful. So do automatic reminders and a connection to the purchasing system. Evaluate each idea to determine whether it’s essential. Ask yourself: If you remove this capability, can the person still finish the job you described?

Sort the ideas you’ve collected into “version one” and “later.” For the equipment-request example, assume the team is willing to open the tracker to check progress:

You can revise the “later” column. If your actual users won’t check the tracker and need a notification to continue, revisit that decision with them. What belongs in version one depends on the workflow you’ve agreed to support.

Now decide how much of that workflow you’re ready to represent. If it depends on confidential information, complicated access rules, or a connection you haven’t confirmed is available, you can plan a prototype using made-up records. Or narrow the project to a part you can properly define and review.

Write the boundary into your notes: “This first version demonstrates the approval path with fictional requests.” Check that the capabilities you’ve kept cover the full path from submission to decision, and put every postponed idea on the later list.

Step 4: Make AI ask the questions your plan has missed

You’ve now described who needs the tool, what work it must cover, and where the first version stops. The next step is to ask AI to identify gaps or unanswered questions. Paste those notes into the AI assistant you already use, leaving out confidential information, and add this instruction:

I’m planning a small app. Below are my notes about its users, their problem, the workflow, and what belongs in version one. Ask me the five unanswered questions that would most change this plan. For each question, explain what decision depends on the answer. Don’t design or build anything yet, and don’t fill gaps with assumptions.

Answer those five questions first. If an answer uncovers a larger gap, ask for another round.

For the tracker, AI might ask: “Can employees see everyone else’s requests, or only their own?” Confirm that decision with the process owner. A plausible answer from AI doesn’t establish your team’s rule.

Sort what comes back into decisions you can make now and facts you need someone else to confirm:

• Known: Write the answer in your notes and identify who confirmed it when relevant.
• Open: Record the question, who can answer it, and whether it blocks your planned version.
• Optional: Move suggestions about extra features or visual polish to the later list.

An unanswered access or data question may block a real staff tool while still allowing a prototype with fictional data. Make that choice yourself and update the scope to reflect it. Before ending the conversation, check that every unresolved question is in your notes and has someone responsible for answering it.

Step 5: Write a one-page brief and check that it is ready

Bring your decisions together in one document you can read without reopening the whole AI conversation. We recommend these six fields as a starting template. Copy the left-hand labels into your own brief; the right-hand column shows how the fictional equipment-request plan fits together.

The success-check field should say what you’ll need to observe when you test the app later. “The app looks good” leaves too much unresolved. The example names the actions and results you’ll need to demonstrate, including the return path.

Plan for changes and support

Decide who will maintain the tool. For a personal learning prototype, that may be you. For a tool people depend on, name who will receive problems, approve changes, and arrange technical help when needed. If nobody has accepted those responsibilities, keep actual use by staff as an open decision in the brief.

Save your project brief and update it whenever an agreed requirement changes. Record the reason too, so you can explain later why a feature behaves as it does. The brief won’t diagnose a code problem, but it gives you the intended behavior to compare with what happened.

Before asking for a build, hand the brief to a colleague and check:

• Can they explain who uses it, who makes each decision, and what happens next?
• Does the proposed first version demonstrate a complete outcome within its stated limits?
• Are unanswered questions assigned, with any blockers resolved for the version you’re about to attempt?

If any answer is no, revise the relevant field. Once the brief passes, you can explain what you want built and how you’ll judge the result. Moving from a prototype to real staff use remains a separate decision that requires the people, data, and technical review outlined in your plan.

FAQs about planning a vibe coding project

Do I need a full technical PRD?

No. You can start a small learning prototype with the brief above instead of a full product requirements document (PRD). If the project involves real users, sensitive data, or complicated connections, ask the relevant process and technical owners what additional requirements they need before proceeding.

Can AI make the plan for me?

Maybe. AI can organize your notes and propose questions, but check its account of the work with the people who know it. Keep any requirement you haven’t confirmed as an open question, especially when it concerns permissions or how another system operates.

What if my idea still feels too big?

Choose a smaller part of the work with a clear beginning and a useful endpoint, or explore the flow first with fictional data. If even that version relies on several unanswered technical questions, get help resolving those dependencies before committing to the build.