I ran a comparison over ~2 months using 6 different AI app builders on real freelance client projects. Each project had a similar scope: authentication, dashboard, basic CRUD functionality, Stripe checkout, and deployment. The only difference was the platform used. Tools tested were Lovable, Bolt new, Base44, Replit Agent, v0 combined with manual work, and Cursor with Claude. The ranking is based on a single practical outcome: whether the client was still actively using the app in production after 30+ days. Cursor + Claude — 6/6 successful deployments This ended up being the most reliable setup. The workflow is less “AI builds everything” and more structured: I scaffold the app, Claude assists at the file level, and I review all changes before committing. It was the slowest to start compared to others (roughly 3x slower than Lovable), but it required almost no rework later, which made it the fastest overall in delivery time. Key advantage was full ownership of the codebase, full Git workflow compatibility, and flexibility to switch tools or models at any point. v0 + manual implementation — 5/6 shipped Very strong for frontend/UI generation. Everything UI-related is fast and clean, but backend logic, authentication, and payments still need manual implementation. The output quality was consistent enough that handoff to another developer or team was smooth in most cases. Lovable — 2/6 shipped (including 1 production site) Extremely fast for initial prototypes. However, once projects became more complex, changes often introduced unintended side effects elsewhere in the system. One project was eventually exported and completed in Cursor within a couple of days. Replit Agent — 1/6 shipped The agent itself performs reasonably well, but the platform creates friction. Costs also became unpredictable due to autoscaling behavior in one case. Even with export options, there is still enough platform coupling that migration requires significant cleanup. Base44 — 0/6 shipped Quick to scaffold, but unreliable when things broke. Some issues were difficult to trace back to actual source code, which made debugging inefficient and unclear. All projects were eventually dropped. Bolt new — 0/6 shipped Good for demos and early-stage prototypes, but not stable enough for production use. The main issue was the gap between something that appears functional and something that holds up under real usage. Exporting out of the environment was also more painful than expected. Overall takeaway Across all tools, one pattern stood out clearly: The only setups that consistently worked long-term were the ones where I fully owned the codebase and could treat it like a standard development project. Tools that kept everything inside their own environment tended to hit limitations once the project moved beyond MVP stage. Other factors like UI quality, speed of generation, or AI capability mattered less than long-term maintainability and portability. This was specifically for paid client work where reliability after handoff matters. For prototypes or demos, the results would likely look different since tools like Lovable perform very well in early-stage builds. Curious what others are using for production client work, and whether anyone has actually managed to keep Base44 or Bolt running reliably at scale. submitted by /u/juniperbush12
Originally posted by u/juniperbush12 on r/ArtificialInteligence