Frequently Asked Questions About Building with AI

Yes, but it's harder. VCs care most about traction, market insight, and your ability to execute. Having a technical co-founder helps, but it's not always essential.

A basic MVP can cost $0-500 using AI tools. Production apps with users typically run $50-500/month for hosting, plus tool subscriptions of $20-100/month.

Talk to potential users, build a landing page to gauge interest, and create the simplest possible version to test the core value proposition before investing heavily.

Not necessarily, especially early on. AI tools let you build and validate without one. But as you scale, having technical expertise on the team becomes increasingly valuable.

Ideas are worth less than execution. Focus on building and launching rather than protecting. If you're worried about competition, move faster-speed is the best protection.

Free to $100/month for most apps. Vercel and Netlify offer free tiers that handle MVPs. Costs scale with traffic-budget $20-50/month for apps with real users.

Start with your immediate network, post in relevant online communities, and build in public. Your first 10-100 users should come from personal outreach, not marketing.

Buy (use existing solutions) when speed matters and your needs are standard. Build when you need differentiation or existing tools don't fit. Most projects are a hybrid.

MVP (Minimum Viable Product) is the simplest version of your app that lets you test your core idea with real users. It matters because building the wrong thing is the biggest startup risk.

Good ideas solve real problems that people already spend money or significant time addressing. The best test is whether you can get someone to pay for it before it's built.

Yes, apps are valued on revenue, growth, and customer base-not how they were built. Many AI-built apps have sold on marketplaces like Acquire.com for thousands to millions.

When you have validated demand and revenue, when you hit technical walls AI can't solve, or when security and reliability become critical. Don't hire too early-validate first.

Yes, many people are doing exactly this. AI tools are particularly well-suited for SaaS because the patterns are well-known-user auth, subscriptions, dashboards, and CRUD operations.

Talk to potential users, not friends. Watch people use your app without guiding them. Ask specific questions about pain points, not whether they 'like' it. Pay attention to behaviour, not just words.

At minimum: privacy policy, terms of service. If handling payments: consider business structure. If handling sensitive data: understand privacy laws. Consult a lawyer for anything complex.

Yes, with AI tools like Lovable, Bolt, and v0, non-technical people are building and launching real apps every day.

No-code uses visual builders with fixed components. Vibe coding uses AI to generate real code from descriptions, giving you more flexibility but requiring more learning.

Most people can build their first functional prototype within a weekend, but building production-ready apps takes 2-3 months of consistent practice.

Learning fundamentals is still valuable, but spending months on syntax before building anything is increasingly unnecessary. Learn concepts, not just commands.

Frontend is what users see and interact with (buttons, forms, layouts). Backend is the behind-the-scenes logic (databases, user accounts, business logic). Most apps need both.

A basic understanding helps enormously. You should grasp concepts like tables, relationships, and queries-even if AI handles the implementation details.

A conceptual understanding helps significantly. APIs are how different services communicate-when your app talks to Stripe for payments or sends emails, that's an API.

Yes, thousands of non-technical people are building and launching apps with AI tools. The key is starting simple, being patient with yourself, and accepting that you'll learn through doing.

Most people build their first genuinely useful app within 1-3 months of consistent practice. 'Useful' meaning something that solves a real problem, not just a tutorial project.

Building too much before validating. People spend months on features nobody asked for, when they should launch an ugly MVP in weeks and iterate based on feedback.

Start with templates when learning and when speed matters. Build from scratch when you need specific customisation or want to deeply understand how things work.

Read error messages carefully, ask AI to explain them, check browser console for errors, and isolate the problem by testing one thing at a time. Debugging is a learnable skill.

You'll learn software architecture, debugging, working with databases, and understanding codebases. The conceptual knowledge transfers directly; only the typing-code-yourself part is different.

Build first, take courses to fill gaps. Starting with a real project gives you context that makes courses more valuable. Pure course-taking without building rarely sticks.

Be specific, provide context, break complex requests into steps, and include examples when possible. Treat it like giving instructions to a capable but literal-minded assistant.

Join communities where builders hang out, be helpful to others, and build in public. Mentorship often develops organically from relationships, not formal arrangements.

Melbourne has a vibrant tech ecosystem with strong fintech and SaaS communities. It's smaller than Sydney but more collaborative, with good access to talent and growing investor interest.

Yes, many. Discord servers for specific tools (Lovable, Cursor), Twitter/X builder communities, and local meetups are the most active. Online communities are often more helpful than local ones for technical questions.

Follow key builders and newsletters on Twitter/X, join tool-specific Discord servers, and don't chase every new tool. Focus on mastering one tool while staying aware of major developments.

You debug it the same way any app is debugged-error messages, testing, and iteration. AI tools can often help fix issues they created, or you can hire help for complex problems.

Yes, AI-generated code is regular code that any developer can work with. It's often cleaner than average because AI follows consistent patterns.

You can scale AI-built apps to significant user bases. However, high-scale applications usually require professional optimization and may need partial rewrites.

AI code can have security vulnerabilities like any code. Common issues include improper input validation, weak authentication, and exposed API keys. Professional review is recommended for sensitive applications.

Use established services for authentication and storage. Minimise the data you collect. Understand privacy laws like GDPR and Australia's Privacy Act. When in doubt, consult a professional.

Most AI tools generate standard code you can export and continue developing elsewhere. The risk is real but manageable if you understand your export options.

Use Git for version control, deploy updates through Vercel or your hosting platform, and communicate changes to users. AI tools often integrate version control automatically.

Technical debt is the future cost of shortcuts taken today. AI-generated code can accumulate it faster than you realise, but for MVPs, some debt is acceptable. Address it when it slows you down.

It can be, but it requires review and testing. AI code is a starting point, not a finished product-treat it like hiring a junior developer who needs supervision.

Lovable is currently the most beginner-friendly option, with Bolt as a close second. Both let you build without touching code while still producing real, deployable applications.

ChatGPT can help you plan and write code snippets, but it can't directly build or deploy a complete app. You need specialised tools like Lovable, Bolt, or Cursor for that.

Lovable for complete apps, v0 for UI components. Lovable builds full-stack applications with databases and auth. V0 generates beautiful UI components you integrate into existing projects.

Supabase is the current favourite for beginners-it's free to start, has a visual interface, and handles authentication too. Firebase is another solid option.

Stripe is the standard choice-it integrates with most AI tools and handles subscriptions, one-time payments, and tax compliance. Expect to spend some time on this integration.

Yes, through responsive web apps (PWAs) or cross-platform frameworks. True native iOS/Android apps are harder with current AI tools but improving rapidly.

Most AI tools handle deployment automatically. If deploying manually, Vercel and Netlify are the easiest options with generous free tiers and one-click deployment from GitHub.

Yes, but marketplaces are complex. You can build a functional MVP, but features like escrow payments, dispute resolution, and trust systems require careful implementation.

AI tools can build most custom features with good prompting. For truly unique requirements, you can extend AI-generated code manually or hire help for specific components.

Lovable builds complete apps from descriptions (no coding required). Cursor is an AI-enhanced code editor that helps developers write code faster. Different tools for different skill levels.

Use a service like Supabase Auth, Clerk, or Auth0. Never build authentication from scratch. AI tools integrate these services well and they handle security complexities you don't want to manage.

Supabase is an open-source backend platform that gives you a database, authentication, and APIs in one place. It's popular because it's powerful, beginner-friendly, and free to start.

Yes, both Lovable and Bolt let you export your code. You get standard React/Next.js projects that can be deployed anywhere and developed with any tool.

It's usually decent-following modern patterns and best practices for straightforward features. But it lacks the judgement of experienced developers for complex decisions and edge cases.

VS Code or Cursor for editing, GitHub for version control, and the same databases and services you'd use with vibe coding. The difference is in depth of knowledge, not fundamentally different tools.

For most projects, let your AI tool choose. Lovable and Bolt use modern, well-supported stacks (React, Next.js, Supabase). Don't overthink this until you have specific requirements that demand it.

Lovable and Bolt are AI app builders for non-coders. Replit is a development environment with AI assistance, better suited for those with some coding knowledge or willingness to learn.

Yes, modern AI tools like Lovable and Bolt generate full-stack applications including backend logic, database schemas, and API endpoints-not just user interfaces.