Workshop - Plugging AI into Your App | Anthony Addae

Description

AI promises transformative features—from smart search to dynamic assistants—but shipping it reliably is harder than tutorials suggest. How do you embed LLMs without latency spikes? When should you use a vector DB vs. fine-tuning? Can you avoid vendor lock-in? This code-heavy, no-fluff workshop covers: ✅ Seamless Integration: Add AI to existing Python/JS apps (Django, Flask, Node) without full rewrites. ✅ Architecture Patterns: Hybrid pipelines (e.g., LLM caching with Redis, cost-efficient RAG with pgvector/Chroma). ✅ Tools You’ll Actually Use: Django for AI endpoints. ✅ Production Gotchas: Rate limiting, privacy-preserving embeddings, and fallback strategies for when APIs fail.