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Build from LLM fundamentals to RAG, LangGraph agents, secure workflows, and production AI systems.

A production graph sits within an authenticated application, durable execution service, approved tools, checkpoint store, and monitoring system. LangChain supplies components; LangGraph controls stateful execution. A graph can be deterministic, agentic, or…

LangGraph represents execution as a graph of steps sharing explicit state. Nodes do work and edges select the next step; the graph can contain both ordinary code and model decisions. It supports applications that need branching, repeated tool use, and…

Requirements: Convert the assistant into an explicit state graph, add durable progress, clarification/approval pauses, and safe resume.

If next steps are fixed, use a sequence of functions or a workflow. If next information actions genuinely vary, a bounded agent may help. Use LangGraph when explicit state, branching, review pauses, or recovery justify it; a short read-only loop can remain…

Beginner — What are nodes, edges, and state?

CrewAI organizes agent work around roles, tasks, and orchestration constructs such as flows. Google ADK is an agent development toolkit with agent and workflow-oriented components. Both provide reusable abstractions; neither makes a multi-agent design…

LangGraph essentials: nodes return state updates; reducers define merge behavior; edges control next steps; model routes need validation; production needs durable checkpoint storage and authorized threads. An interrupted node can restart, so pre-pause side…

AI and LLM fundamentals

Graph RAG retrieves through entities and relationships, such as customer → policy → endorsement → covered asset. It can combine graph traversal, document retrieval, and generated summaries. A graph represents connected facts; it is separate from LangGraph's…

This is a minimal orchestration demonstration, not an insurance backend. Dependencies are @langchain/langgraph and zod. It uses the documented StateSchema style; older tutorials may use Annotation.Root. Select compatible package versions before adopting…

A checkpoint records execution progress and state at a recovery boundary. Persistence saves it outside the process. Memory is selected information reused by later turns or tasks; a checkpoint is not automatically good long-term user memory.

Graph streaming exposes progress such as state updates, node events, and model token events. It lets a UI distinguish “retrieving,” “waiting for approval,” and “complete.” Stream modes and event APIs vary by version.

A production graph sits within an authenticated application, durable execution service, approved tools, checkpoint store, and monitoring system. LangChain supplies components; LangGraph controls stateful execution. A graph can be deterministic, agentic, or…

LangGraph represents execution as a graph of steps sharing explicit state. Nodes do work and edges select the next step; the graph can contain both ordinary code and model decisions. It supports applications that need branching, repeated tool use, and…

CrewAI organizes agent work around roles, tasks, and orchestration constructs such as flows. Google ADK is an agent development toolkit with agent and workflow-oriented components. Both provide reusable abstractions; neither makes a multi-agent design…

This is a minimal orchestration demonstration, not an insurance backend. Dependencies are @langchain/langgraph and zod. It uses the documented StateSchema style; older tutorials may use Annotation.Root. Select compatible package versions before adopting…

A checkpoint records execution progress and state at a recovery boundary. Persistence saves it outside the process. Memory is selected information reused by later turns or tasks; a checkpoint is not automatically good long-term user memory.

Graph streaming exposes progress such as state updates, node events, and model token events. It lets a UI distinguish “retrieving,” “waiting for approval,” and “complete.” Stream modes and event APIs vary by version.

Requirements: Convert the assistant into an explicit state graph, add durable progress, clarification/approval pauses, and safe resume.

I compare ecosystem/language fit, state contracts, review/resume behavior, persistence guarantees, observability, and hosting. LangGraph starts from explicit state-graph orchestration; MAF provides agent and workflow abstractions in its ecosystem. The…

If next steps are fixed, use a sequence of functions or a workflow. If next information actions genuinely vary, a bounded agent may help. Use LangGraph when explicit state, branching, review pauses, or recovery justify it; a short read-only loop can remain…

LangGraph essentials: nodes return state updates; reducers define merge behavior; edges control next steps; model routes need validation; production needs durable checkpoint storage and authorized threads. An interrupted node can restart, so pre-pause side…

AI and LLM fundamentals

Graph RAG retrieves through entities and relationships, such as customer → policy → endorsement → covered asset. It can combine graph traversal, document retrieval, and generated summaries. A graph represents connected facts; it is separate from LangGraph's…

AI Engineering learning module

AI Engineering learning module

AI Engineering learning module

AI Engineering learning module

AI Engineering learning module

AI Engineering learning module

AI Engineering learning module

AI Engineering learning module