Question 1

What tools do I need to build an LLM-powered application?

Accepted Answer

A typical stack includes: an inference API (OpenAI, Anthropic, or self-hosted), a vector database for RAG (Pinecone, Weaviate, Qdrant), an orchestration framework, an evaluation tool, and observability for tracing LLM calls in production. Not every project needs all layers.

Question 2

How should I evaluate AI/ML platforms for my team?

Accepted Answer

Three dimensions matter most: latency requirements, data sensitivity (can you send data to a third-party API?), and cost at scale. Run your actual workload through at least two providers before committing.

AI / ML Tools & Software