EV Battery Health Report X Lovable

Tools and resources- Lovable- GPT- Figma- Google Stitch
3rd party/ plugins- Stripe- Merchant bank- Discord- Slack
Time and team- 4-5 hours- Solo founder & builder- Evening hacker- Spiced tea
🔋 Problem statement
EV buyers lack an independent, data-informed ways to assess real-world battery health and range risk before purchase, leading to uncertainty and poor decision-making. The current solutions require booking a car retailer or garage service and paying for a technician to run a diagnostic.
My tool addresses the inconvenience by offering a remote service that gives an estimated report to speed up the process and help customers with buying and selling decisions. A report that downloads in seconds.
See origin prompt flow, iterated since, reduced for security 🔓
Product scope summary
I identified the trust gap in the used EV market and designed a focused, single-model MVP that translates mileage and age into a clear, statistically bounded battery degradation estimate.
I defined the product scope, built the end-to-end user flow, implemented strict payment gating via Stripe, and created legally conservative safeguards to protect both users and the business. By prioritising precision over breadth, I delivered a credible, monetisable tool that balances data transparency, risk management, and premium UX execution.

Vibecoding workflow
- Figma — Defined the core concept, mapped user flows, and built a design system canvas in parallel.
- OpenAI GPT — Validated the product idea, stress-tested modelling logic, drafted legal safeguards, and formalised system rules.
- Lovable — Built and shipped the live MVP, implemented payment gating, and deployed the production-ready experience.
- Stripe — Integrated secure checkout and payment confirmation logic.
- Merchant bank — Enabled transaction settlement and financial processing.
- Google Stitch — Rapidly explored layout structures for phase 2 in the fastest way and explored an upgraded design system to scale the product
- Discord — Collected early feedback, validated assumptions, and iterated quickly post-launch.


Learnings
Overall I solved a problem, ideated, designed, built and shipped a new product in record speed time. agentic AI platforms designed for full-stack software development are serious productivity hacks and immense fun.
Here are some themes I spent time problem solving and learning to refine my methods on, in a shorter time boxed period
- Prompt maturity: learning to write all-inclusive rules that served front and back end
- Lovable will not execute a high standard of UI polish – this must remain in the hands of craft to refine, polish and judge aesthetics
- Inconsistencies will occur throughout the flows unless I later created rule and logic patterns for holistic replacements and updates
- Stripe integration had delays in its backend/ security. It is not as ‘fast and swift’ as Lovable portal experience might suggest
- Technical knowledge will help you unblock, debug and ship faster
- Join Lovable on Discord – an incredible space to share and vibe with other builders!