Where Lovable Shines (and Where Engineers Still Matter)
Few platforms have captured startup imagination like Lovable. In just seven months, it hit $100M ARR, raised a $200M Series A at a $1.8B valuation, and became the go-to tool for founders needing a Proof of Concept (POC) in record time. Its pitch is simple: describe your idea in natural language, and Lovable generates a working app – front end, back end, database, and deployment – in minutes.
Anton, Lovable’s CEO, says their mission is “to enable those who have been held back by not being able to write code or the capital to hire engineers.” It’s an empowering vision, and one that has already put Lovable into the hands of millions of users.
But while Lovable can build a demo at lightning speed, the leap from demo to durable product – the leap from Minimum Viable Product (MVP) to Minimum Loveable Product (MLP) – is where engineering still matters most.
Where Loveable Excels
Lovable thrives in the messy early stage. Instead of static wireframes, founders can:
- Mock up ideas instantly and validate them with users.
- Lower upfront costs, avoiding premature hiring before a concept is proven.
- Generate working demos that an engineering team can later refine.
“You can build with Lovable and then any engineer can come in and take over.” – Anton Osika
Anton, their CEO has previously emphasised that Lovable was never meant to replace engineers – it was designed to hand them something to build on faster.
The Reality: What Engineers Prefer
At Mobile Wave Solutions, we don’t just analyse these tools – we use them. And while Lovable has generated enormous buzz, we’ve found that in practice, many of our engineers (reflecting our clients’ preferences) lean more on Replit.
Why? Because although both Lovable and Replit all rely on similar underlying models and produce broadly similar code, the difference is in speed, reliability, and usability:
- Replit wins on speed: shorter wait times, faster feature generation, smoother iterations.
- Figma/design integration still lags: Lovable promises seamless design-to-code, but they’re not yet stable in real-world use.
- Replit’s two modes: Its assistance mode boosts productivity like GitHub Copilot, while its agent mode can autonomously generate and refactor entire apps. For our teams, it’s the agent mode that delivers the most value.
In other words, while Lovable is powerful for creating POCs and sparking ideas, Replit remains the tool we reach for more often when client delivery is on the line. In fact, we use Replit. in combination with a number of different AI tools tailored for MWS engineers that provides our clients with the most efficient, secure and high-quality engineering available, surpassing the quality of code produced by any one AI tool alone.
Why Engineers Are Still Essential
Anton himself admits Lovable is “better than the average, but not better than the skilled.” That’s because the real work of shipping a product goes far beyond generating scaffolding code.
- Scalability: An app that looks slick in a demo may fail under real-world load. Engineers design for resilience, not just speed.
- Security: AI platforms today still face downtime, breaches, and data risks. Engineers enforce governance, encryption, and compliance.
- Integration: Products rarely exist in isolation. Engineers stitch prototypes into payment systems, databases, and enterprise workflows.
- Context & Strategy: AI can generate; engineers interpret. They decide what’s worth building now versus later, ensuring effort aligns with product strategy.
Ultimately, whichever AI tool you choose, engineers make the difference between a clever demo and a production-ready product. Even Anton asks: “If the context isn’t there, if the engineer doesn’t understand what is being done, what would that impact look like on us?”
Find a link to the original podcast here.
