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AI and LLM fundamentals

MongoDB collections can store conversation messages, task/run state, approved preferences, and memory records. A LangGraph checkpointer requires its expected integration contract rather than an arbitrary collection called memory. Business claims remain…

Multi-tenancy supports several organizations while preventing cross-organization access. MongoDB often fits flexible document records; PostgreSQL provides relational constraints, joins, transactions, and optional row-level security with pgvector. Both require…

Atlas is MongoDB's managed database environment; MongoDB Vector Search indexes supported vector fields for similarity retrieval. Source metadata and application records can live alongside chunk documents. A vector/search index is distinct from ordinary…

A practical textbook for building AI applications, agents, and reliable client solutions.

flowchart TD

Pinecone, Qdrant, Weaviate, pgvector, MongoDB Vector Search, Elasticsearch, and OpenSearch provide different ways to store and retrieve vector-backed knowledge. Some are dedicated vector services; others extend databases or search engines you may already…

Beginner — Where does the LLM call belong?

Requirements: Combine policy RAG, claim status, guided intake, document processing, reviewed communication, staff escalation, and multi-tenant operations. Define supported tasks and explicit exclusions.

MongoDB collections can store conversation messages, task/run state, approved preferences, and memory records. A LangGraph checkpointer requires its expected integration contract rather than an arbitrary collection called memory. Business claims remain…

AI and LLM fundamentals

Multi-tenancy supports several organizations while preventing cross-organization access. MongoDB often fits flexible document records; PostgreSQL provides relational constraints, joins, transactions, and optional row-level security with pgvector. Both require…

Atlas is MongoDB's managed database environment; MongoDB Vector Search indexes supported vector fields for similarity retrieval. Source metadata and application records can live alongside chunk documents. A vector/search index is distinct from ordinary…

MongoDB stores application documents and canonical records where appropriate. Redis provides scoped caching/counters/queue backing. A vector index serves derived retrieval representations; none should silently replace authoritative claim-service truth.

A practical textbook for building AI applications, agents, and reliable client solutions.

flowchart TD

Pinecone, Qdrant, Weaviate, pgvector, MongoDB Vector Search, Elasticsearch, and OpenSearch provide different ways to store and retrieve vector-backed knowledge. Some are dedicated vector services; others extend databases or search engines you may already…

Beginner — Where does the LLM call belong?

Requirements: Combine policy RAG, claim status, guided intake, document processing, reviewed communication, staff escalation, and multi-tenant operations. Define supported tasks and explicit exclusions.

AI Engineering learning module

AI Engineering learning module

AI Engineering learning module

AI Engineering learning module

AI Engineering learning module

AI Engineering learning module