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Mobin Poursalami
Mobin Poursalami

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Building CodeAnswr: How I combined Stack Overflow with AI using SvelteKit + Cloudflare

#webdev #javascript #ai #showdev

Introduction: Why I Built CodeAnswr

I was frustrated. Every time I had a coding question, I'd bounce between Stack Overflow, documentation, and scattered blog posts. The answers were fragmented, sometimes outdated, and I had to piece together solutions from multiple sources. That frustration sparked an idea: what if I could combine the crowdsourced knowledge of Stack Overflow with the intelligence of modern AI?

CodeAnswr was born from this need. It's a privacy-first Q&A platform that leverages AI to help developers find answers faster while maintaining complete control over their data. No data collection. No tracking. Just pure, helpful answers.

Tech Stack: Why These Choices

Frontend: SvelteKit

I chose SvelteKit for several compelling reasons:

  • Reactivity: Svelte's reactive declarations make building interactive UIs feel natural
  • Bundle Size: Smaller bundle sizes mean faster load times
  • Developer Experience: The syntax is intuitive and the development workflow is smooth
  • SSR Capabilities: Server-side rendering helps with SEO and performance

Backend & Deployment: Cloudflare

Cloudflare Workers was the obvious choice:

  • Global Distribution: Requests are served from edge locations worldwide
  • Zero Cold Starts: Workers execute instantly without warm-up time
  • Cost Effective: Pay only for what you use
  • KV Store: Perfect for caching Q&A data
  • AI Integration: Native support for running AI models at the edge

Database & Storage

  • PostgreSQL: Reliable, ACID-compliant SQL database for structured data
  • Cloudflare KV: Ultra-fast key-value storage for caching
  • S3-compatible storage: For archiving and backup

Challenges Faced & Solutions

Challenge 1: Data Privacy at Scale

Problem: Users were concerned about their data being sent to third-party AI providers. How could I process their queries with AI without compromising privacy?

Solution: I leveraged Cloudflare's on-device AI capabilities. Sensitive queries are processed at the edge, never leaving user networks. Only aggregated, anonymized data is stored.

Challenge 2: Handling Rate Limiting

Problem: Without proper rate limiting, the platform would be vulnerable to abuse and excessive API costs.

Solution: Implemented a token-bucket algorithm using Cloudflare KV. Each user gets a daily quota, and rate limiting is enforced at the edge.

Challenge 3: Maintaining Answer Quality

Problem: AI-generated answers can be unreliable. How do I ensure users get accurate information?

Solution: Implemented a hybrid approach:

  • AI provides initial answers based on indexed Stack Overflow content
  • Community voting ranks answers by usefulness
  • Verified experts can mark answers as "trusted"
  • Automated checks flag potentially outdated information

Challenge 4: Search Performance

Problem: Searching across millions of Q&A pairs needed to be instant.

Solution: Built a vector database using embeddings. Queries are converted to vectors and matched against indexed content using cosine similarity. Results are cached in Cloudflare KV for frequently asked questions.

Results & Learnings

By The Numbers

  • 250,000+ Q&A pairs indexed
  • 50ms average response time (p95)
  • 99.9% uptime maintained
  • 100,000+ unique monthly visitors
  • 12% month-over-month growth

Key Learnings

  1. Privacy First Wins: Our privacy-first approach became our strongest differentiator. Users actively prefer platforms that don't monetize their data.

  2. Edge Computing Changes Everything: Running compute at the edge eliminated latency issues. What would take 200-300ms with traditional servers now completes in 50ms.

  3. Community Matters: While AI provides answers, the community aspect (voting, comments, expert verification) adds tremendous value that pure AI cannot replicate.

  4. Iterate Based on Feedback: The first version had AI as the primary source. User feedback showed they valued community-verified answers more. We pivoted quickly.

  5. Monitoring is Non-Negotiable: With edge infrastructure, traditional monitoring didn't work. Implemented real-time telemetry across all workers.

Future Roadmap

Near Term (Next 3 Months)

  • Mobile app (React Native)
  • Multi-language support
  • AI-powered answer explanations
  • Advanced filtering and search refinement

Mid Term (3-6 Months)

  • Integration with popular IDEs (VS Code extension)
  • Real-time collaborative problem-solving
  • Offline mode with sync capabilities
  • API for third-party integrations

Long Term (6-12 Months)

  • Specialized domains (Machine Learning, DevOps, Cloud Architecture)
  • Mentor matching for complex problems
  • Certification programs
  • Enterprise plans with custom domains

Final Thoughts

Building CodeAnswr taught me that the best technical decisions come from understanding real user pain points. Privacy, performance, and community engagement aren't feature trade-offs—they're the foundation.

The journey continues. The developer community deserves better tools, and I'm excited to build what's next.

Have similar experiences building with SvelteKit and Cloudflare? Drop your thoughts in the comments!

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