Editors built around AI
These tools understand your whole codebase rather than just the file in front of you.
- Best for: professional developers
- Strength: project-wide understanding
- Examples: Cursor, Windsurf
Vibe coding has gone mainstream. This lesson turns the original presentation into an explorable website so learners can quickly understand the tools, compare categories, and see when each approach makes sense.
Describe what you want, and AI writes the code, scaffolding, and often deployment flow for you.
Web app builders can assemble frontend, backend, authentication, and database layers from a single prompt.
The strongest vibe coders know which tool to reach for — and when — depending on speed, budget, skill, and project complexity.
Not all AI coding tools solve the same problem. Some are best for non-developers, some for professionals inside an editor, and some for technical power users who want control and efficiency.
These tools understand your whole codebase rather than just the file in front of you.
Broad compatibility and low switching cost. Ideal when you want AI help without changing your workflow completely.
Describe the application in plain English and the platform builds the frontend, backend, and database.
Powerful, often very cost-effective tools for users comfortable working directly in the terminal.
Use this section to match the tool category to the learner. It reframes the lesson from a list of products into a practical decision-making guide.
If you want to build a real app without writing code, start with web app builders. Bolt.new and Lovable can create full-stack applications from a single paragraph.
If you already work in VS Code or a similar environment, AI-native IDEs and extensions can transform your workflow and speed up multi-file work.
If cost matters, open-source options such as Cline and Aider can be extremely affordable because you typically only pay model usage costs.
Switch between the examples below to see how the lesson moves from abstract tool categories to realistic scenarios, prompts, and outcomes.
A small business owner needs a client portal where people can log in, view active projects, see invoices, and download deliverables. Existing SaaS tools are too generic or too expensive, and custom development would take weeks.
They need something purpose-built for their business, not a bloated subscription product or a costly bespoke build.
A single plain-English brief outlines the login flow, dashboard, invoices, file downloads, and visual style.
The platform produces a full application with authentication, database, and polished UI in minutes.
A developer needs to migrate a project from SQLite to PostgreSQL across more than 50 files. Manually, this means days of careful refactoring and retesting.
The change touches many parts of the system, so isolated code suggestions are not enough.
Agent Mode is asked to update database queries, adjust syntax, add error handling, and flag manual review points.
Cursor edits 53 files, runs tests, and fixes the errors it introduced, compressing days of work into hours.
This decision framework keeps the lesson practical. Learners can start from their own experience level, budget, and working style rather than chasing hype.
Bolt.new and Lovable offer one of the lowest barriers to entry. You describe the app in natural language and the platform assembles the experience for you. Both offer free tiers suitable for small experiments.
For developers who want a mainstream, affordable starting point inside an existing editor, Copilot is a simple on-ramp. It lowers switching friction and helps you test whether AI-assisted coding fits your process.
Almost every major tool now has a free tier. The fastest way to develop intuition is to build a small, familiar project in two different tools and compare quality, speed, and control.
Speed is not the same as quality. This section gives the lesson necessary balance by surfacing the risks that come with blindly trusting generated code.
Organisations build faster than ever, then discover maintenance debt, security weaknesses, and code nobody fully understands.
Use AI to go faster, widen your ambition, and reduce friction — but keep human review, testing, and architectural understanding in the loop.
The best next step is not to memorise a list of tools — it is to build. Choose one small project you understand clearly, try it in one platform, then compare the result with another.