AI Engineering
Learn LLMs, RAG, agents, secure tools, and production AI through practical insurance examples.
LangChain overview, models, prompts, and chains
LangChain is a framework ecosystem for assembling model-driven applications. Model wrappers, prompt templates, and composable operations make integration easier. A chain is a sequence of transformations or calls; it can be fixed and does not automatically…
LangChain tools, retrievers, retrieval, and structured output
A retriever returns candidate documents for a query. A tool exposes an action with a description and argument schema. Structured-output wrappers ask supported models for typed data and help parse the result; these are adapters around the concepts already…
LangChain agents versus simple code
LangChain agent construction combines models, tools, and runtime behavior into an agent interface. Simple code uses direct SDK calls and ordinary functions instead. Both can produce production applications if their reliability and security requirements are…
What does LangChain provide?
Reusable model, prompt, tool, and retrieval components and higher-level agent integrations. It helps compose applications but does not own domain security or guarantee output truth.
What is a chain?
A sequence of transformations or calls, such as prompt → model → parser. A chain can be deterministic and is not automatically an agent; an agent chooses some actions based on observations.
When would you avoid LangChain?
For a small direct API call with clear validation, plain SDK code may be easier to understand and maintain. I adopt abstractions when they reduce actual integration complexity and keep provider requests, costs, and failures inspectable.
A tutorial's imports fail. What do you do?
I identify its intended version, consult the current official docs, and separate the concept from the old API. I pin compatible dependencies and avoid mixing legacy chain APIs with newer agent construction patterns.
Difficulty is an editorial estimate. Completion means you chose to mark a question as understood.