Learning Center
Understand what AI is doing while you build
27 guides covering the parts of an AI-built application people meet when something stops working: requests, keys, access rules, deployments and the errors in between. Free to read, no account needed.
Browse by topic
AI Building
2AI building is using a coding assistant to turn instructions into app changes. Follow how context, files, checks and deployment fit together.
Troubleshooting
9Troubleshooting is tracing a visible failure to its cause. Start with a failed request, empty list or deployment, then verify the fix.
APIs
3An API is a program's interface for requests and responses. Learn about keys, headers and status codes, then inspect calls made by an AI-built app.
Databases
1A database stores records that an app reads and changes through queries. Learn how tables, filters and access rules affect the rows a user can see.
Authentication
1Authentication verifies identity; authorization decides access. Learn why a successful login can still produce a denied request or an empty list.
Deployment
2Deployment turns source code into an app served at a public URL. Trace build failures, missing configuration and differences between preview and live.
GitHub
1GitHub hosts code repositories and their change history. Learn how commits, branches and deployment connections work when an AI tool changes your app.
Security
3App security controls who can access data and use credentials. Check secret storage, row access rules and common mistakes in AI-generated code.
MCP
2MCP is the Model Context Protocol for connecting AI applications to tools and data. Learn about servers, permissions and the actions those tools allow.
AI Agents
1An AI agent uses a model to choose actions through available tools. Follow the request-and-result loop and learn where human approval belongs.
Tools
1An app's tool stack combines builders, code hosting, deployment and data services. Identify which service owns each job before investigating a failure.
Launch Guides
1Launch readiness is checking an app before inviting users. Review access, payment handling, recovery, errors and deployment without inventing results.
Recently updated
- What actually happens when AI builds an app?Follow an AI app build from your request to file changes, packages, database rules and deployment. Learn what to inspect before trusting the result.
- How AI coding tools workUnderstand context windows, tool calls and build checks in AI coding tools. Learn why the same model behaves differently and how to verify its changes.
- API keys explainedWhat an API key is, what it proves, why some keys are safe in a browser and others are not, and how to handle one without leaking it.
- Why can't my frontend access my database?Empty lists, permission errors and silent failures between the browser and a hosted database — and how to tell which of the three you have.
- How Lovable, GitHub, Vercel and Supabase work togetherFour tools, four jobs. Where your code lives, where it runs, where your data sits, and what moves between them when you ship a change.
- How APIs work in AI-built applicationsRequests, responses, headers and status codes — explained through the calls an AI-generated app actually makes, and where those calls tend to go wrong.
Reading is the start, not the point
MessyDev is the hands-on version of these guides: you break something, work out why, fix it, and check the fix. The first exercise is free and needs no account.