[Discussion] Is it possible to vibe code a custom Data Analytics platform (like Salesforce/Scoop Analytics) using local AI (Ollama)? What roadmap do you recommend?
Hey everyone,
I've been thinking about an ambitious project and want to approach it purely through "vibe coding". I want to build my own data analytics app—something that can ingest data, run queries, and visualize insights, similar to Scoop Analytics or Salesforce dashboards.
My twist: I want to use a local AI model via Ollama (for privacy and zero API costs) to act as the coding assistant that helps me build it, and potentially as the "brain" that translates natural language to SQL queries within the app.
Since vibe coding with local models is a bit different from using powerful cloud APIs (like Claude 3.5 Sonnet), I'd love some advice on the best route to take.
My initial thought process:
- Using an AI-friendly IDE (like Cursor or Windsurf) connected to Ollama, or just managing the context manually.
- Testing models like Qwen 2.5 Coder or Llama 3 for the coding assistance.
- Using a Python/FastAPI backend for database connections and an ORM, with a React/Next.js frontend.
Questions for the community:
- Has anyone successfully vibe coded a full-stack data app using local models? How smooth was the experience compared to cloud LLMs?
- What tech stack plays nicest when you're letting a local AI write most of the code?
- Any tips for structuring prompts when dealing with complex database schemas?
Would love to hear your roadmaps, stack recommendations, or any pitfalls I should watch out for. Thanks!