Foundations

What Is Vibe Coding? A Responsible Builder’s Starting Point

A grounded introduction to building software through conversation with AI.

Foundation stage · Module 1 of 15

Outcome for this lesson

Choose one small course project and use the describe, build, inspect, test, and refine loop responsibly.

Bring forward: No prerequisite. Bring a small problem you understand well.

Produce: A one-sentence project outcome, intended user, important constraint, and failure case.

0 of 15 core modules complete

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Foundation stage

Build the next result

This module gives you a safe starting point and one small project to carry through the entire course. Do not begin with a platform, a high-risk workflow, or a promise of income. Begin with a problem you understand and a result you can observe.

Your result for this module

A one-sentence project outcome, intended user, important constraint, and failure case.

Continuous case study

Course case study: Freelancer Follow-Up Tracker

Throughout the course, the worked example is a small tracker for a freelancer who wants to record a new inquiry and see the next follow-up date. It is narrow enough to test and useful enough to reveal requirements, privacy, accessibility, cost, and business decisions.

Do the work

  1. Choose one user and moment

    Name one person or role and the moment the tool should help. Example: a freelancer immediately after receiving a new inquiry.

  2. State one observable result

    Describe what the user can do or see. Avoid technology and revenue language. Example: record an inquiry and see the next follow-up date.

  3. Set a responsible boundary

    Exclude sensitive or high-risk work from the first project. Decide what data the project will not collect.

  4. Name one failure case

    Choose a failure that would make the result unreliable, such as saved information disappearing after refresh.

Copy-and-complete template

Create your module artifact

User:

Moment of need:

Observable result:

Important constraint:

Data I will not collect:

One failure case:

Keep sensitive information, passwords, API keys, payment data, and private customer details out of course notes and AI prompts.

Quality gate

Check the result before the quiz

  • The project serves one primary user.
  • The result can be demonstrated.
  • The first version avoids high-risk decisions.
  • A failure case is written before building.

How this moves the project forward

Module 2 uses this project card to decide exactly where human review is required.

Evidence checkpoint and lesson summary

Confirm the artifact, then answer the key questions

The questions cover a core idea, a realistic decision, and evidence from the lesson. Incorrect answers identify concepts to review; they are not a complete measure of your experience or ability.

Artifact checkpoint

This is an honest self-check. Do not enter private data here; keep the artifact in your own approved workspace.

1. A draft works once in the browser. What should happen next?
2. Which project is the strongest starting point for this course?
3. Which note is sufficient evidence for this lesson’s artifact?

Confirm the artifact and answer all three questions correctly to unlock the recommended next step.

About the author

Son Kim

Son Kim writes from first-hand experience as a blind AI user. He tests vibe-coding tools, models, plugins, connected hardware, and everyday AI workflows to document what improves accessibility, independence, productivity, earning opportunities, problem-solving, and quality of life—and what still requires human judgment.

Read the full author background

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