Developer shares lessons from building sports app with Base44 and Claude
App concept and platform choice
The developer built a sports app at glanceplay.com designed for new or casual sports fans. The app provides quick, 60-second briefings before games, answering "what do I need to know before watching tonight?" The briefings are more accessible than box scores and more concise than full articles.
The app was built on Base44, which the developer found "great for getting something off the ground fast."
Problem with iterative development on Base44
The developer discovered that "every time I needed a code change — even small tweaks — I was burning Base44 credits. It added up fast." They realized many of these changes could have been handled directly by Claude instead.
Specific types of changes that became expensive on Base44 included:
- Iterating on UI layout and component structure
- Debugging API response formatting
- Refining prompts for the sports briefing logic
- General "why isn't this working" troubleshooting
Recommended workflow for AI-assisted development
The developer's advice: "Use a platform like Base44 (or Bolt, Lovable, etc.) to scaffold the initial structure, then lean on Claude heavily for all the incremental code changes, debugging, and prompt engineering. You'll go further on the same budget."
They found Claude "so much better at all of this, and it's a much more efficient use of resources when you're in that iterative build phase." Using Claude for these tasks would have been "free (or at much lower cost)" compared to Base44 credits.
Current status and challenges
The core product is live and working, but the developer is "still working on the load times (my biggest current headache)."
📖 Read the full source: r/ClaudeAI
👀 See Also
Using Kimi K2.6 to Properly Uninstall macOS Apps by Finding Hidden App Directories
A developer describes using Kimi K2.6 to automatically find and delete macOS app directories, including hidden ~/.appname and ~/Library/Application Support files, with a custom agent that edits its base knowledge to improve the process.
Claude Game Dev Log: Agentic Three.js Development Lessons and Stack
A developer shares practical lessons from building a Three.js line rider game entirely with Claude AI, including Git worktrees, TypeScript-first approach, admin sliders for AI limitations, and a tech stack using Firebase, WebSockets, and deterministic lockstep simulation.
Alien Pinball Postmortem: Full Physics Pinball Game Built with Claude + AI Toolchain
A developer shares how they built a complete browser pinball game using Claude Code (Opus), ChatGPT for art, Suno for music, and LittleJS+Box2D. Includes PixiJS-less workflow, AI-generated art aligned to physics geometry, and practical lessons on AI code co-development.
Hybrid RAG for Local Agent Memory with OpenClaw, Ollama, and nomic-embed-text
A developer implemented hybrid RAG retrieval for AI agent memory using OpenClaw with Ollama and nomic-embed-text, combining 70% vector similarity with 30% BM25 keyword matching. The setup runs locally without external APIs and includes MMR deduplication and temporal decay weighting.