Vector databases, retrieval, embeddings, and RAG architectures.
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Getting a handful of objects into a vector database is easy. Getting millions in — reliably, without silently dropping data or melting your throughput — is where most ingestion pipelines start to hurt.
A coding assistant is only as good as the context you can feed it. This walkthrough builds one that retrieves over your own code and documentation using Weaviate's built-in MCP server.
Hybrid search combines vector similarity with exact keyword matching — and the keyword half lives or dies by tokenization: how text gets broken into the discrete units that BM25 scores against.
"Add security later" is how most AI prototypes ship — and how they get stuck before production. This piece follows a fictional health-tech company from a single API key all the way to a compliance-ready setup.
Authentication and authorization get lumped together, but they answer different questions: who are you? and what are you allowed to do? Getting the second one right is what keeps a shared database from becoming a liability.