We tried using Lovable to build an online business — here is what we learned
Lovable promises to turn plain-English descriptions into fully functional web apps. We put that claim to the test by building a real product from scratch — no hired developers, no prior coding knowledge required. Here is an honest account of what went well, what surprised us, and where the current limits lie.
What is Lovable?
Lovable (formerly GPT Engineer) is an AI-powered app builder that lets you describe a web application in plain English and receive a working codebase in return. It uses a combination of Claude Sonnet and GPT-4o under the hood to generate, iterate on, and deploy full-stack React applications — without the user needing to write a single line of code.
Unlike simple landing-page builders, Lovable targets functional applications: dashboards, SaaS products, internal tools, and marketplaces. The promise is that a non-technical founder or solo operator can go from idea to deployed product in hours rather than months.
Underlying models Lovable uses Anthropic's Claude Sonnet for most generation tasks, with GPT-4o available as a fallback. The model selection is largely abstracted away from the user — Lovable manages routing internally. See the AI Tools page for a summary and the Claude model card for safety documentation.
What we built
[Content to be added — describe the specific product or tool built during the experiment, the starting prompt used, and the goal of the project.]
The experience: prompt to product
Getting started
[Content to be added — first impressions, sign-up flow, initial prompt, and the quality of the first generated output.]
Iteration and refinement
[Content to be added — how well Lovable handles follow-up instructions, debugging loops, design changes, and adding new features after the initial build.]
Deployment
[Content to be added — Lovable's one-click deployment, custom domain setup, and what happens when you need to go beyond the platform's built-in hosting.]
Where it excels
[Content to be added — specific use cases and task types where Lovable performed above expectations.]
Where it struggles
[Content to be added — limitations encountered: complex logic, database relationships, third-party API integrations, pixel-perfect design, mobile responsiveness, and cost at scale.]
Verdict
What works well
- Speed from idea to working prototype
- No coding knowledge required
- Clean React codebase you can export
- One-click deployment
- Strong for MVPs and internal tools
Watch out for
- Complex logic requires prompt discipline
- Cost can escalate on larger projects
- Limited control over backend architecture
- Design customisation can be frustrating
- Not a replacement for a senior engineer
[Full verdict text to be added after completing the experiment.]
Who is it for?
Lovable is best suited to: solo founders validating an idea before raising funding; operators who need internal tools without waiting for engineering capacity; and product managers who want a working prototype to show stakeholders rather than a deck. It is less well-suited to teams building complex, data-intensive applications with strict performance or security requirements.
Pricing
[Content to be added — current pricing tiers and what you get at each level. Check lovable.dev for up-to-date pricing, as plans change frequently.]
Disclosure: This site contains affiliate links. If you sign up to Lovable through a link on this site, we may earn a commission at no additional cost to you. Our reviews are independent — affiliate relationships do not influence our assessments.