Building a Full App with Lovable + Claude + Gemini: A Case Study
A software engineer with no fullstack/frontend experience built Earnest — a free app that helps users track bank account bonuses (open account, meet requirements, collect bonus, close it, repeat). The stack combined Lovable, Claude, and Gemini to produce a working product with over 100 real users.
Stack & Surprising Findings
- Lovable handled UI and scaffolding — got the developer from zero to a real app "embarrassingly fast."
- Claude was far better at understanding intent when the full user flow was described instead of individual features.
- Gemini served as a useful second opinion when the developer was stuck.
- The hardest part wasn't the AI itself — it was knowing what to ask for.
Results
- 19+ active promotions tracked
- $9,700+ in available bonuses tracked
- 100+ real users
- $5,000+ in bonuses earned by users so far
The app is live at earnest.lovable.app. The developer is open to sharing more about specific prompts that worked, what failed completely, and how they debugged without being able to read the code properly.
📖 Read the full source: r/ClaudeAI
👀 See Also
Pioneering OpenClaw: Revolutionizing Large Corporate Workflows
Explore how OpenClaw is being deployed in large corporate settings, enhancing automation and efficiency in complex workflows. This discussion highlights key benefits and user experiences.
BinktermPHP: A Full BBS/FidoNet Platform Built Primarily with Claude
BinktermPHP is an open-source web-based BBS written in PHP 8 with PostgreSQL, featuring a built-in binkp FidoNet mailer, echomail/netmail, file areas, door games, real-time server push, and an MCP server that exposes echomail to AI assistants. The developer reports building it almost entirely using Claude for implementation while handling architecture and testing.
Claude Managed Agents Released: Multi-Agent Orchestration and 70 Days of Practical Lessons
Anthropic launched Managed Agents for multi-agent orchestration and enhanced toolchains. A developer shares 70 days of experience using role-split agents (Opus decision layer, OpenCode engineer, research agents) and the critical shift from 'execute this' briefs to 'you can question my premise' briefs.
Practical Lessons from Using AI Agents on a 100k LOC Codebase
A developer shares six specific techniques learned while using Claude Code and Cursor to build a pandas-compatible API layer on top of chDB, including maintaining a CLAUDE.md rules file, using zero-context agents as critics, and structuring multi-agent workflows with filesystem-based coordination.