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

Microsoft Agent Framework, or MAF, provides agent abstractions and explicit workflows. An agent handles model-driven interaction and tool use; a workflow connects agents and ordinary functions through controlled paths. Microsoft describes it as the successor…

An AI agent is software that uses a model to choose actions toward a goal, observes results, and decides what to do next within application limits. A chatbot describes a conversational interface; it may or may not contain an agent. A workflow defines the…

A deterministic workflow follows explicitly coded transitions for given inputs and recorded external outcomes. It can call nondeterministic services, but its orchestration rules remain controlled. It is the natural extension of validation, transactions, and…

An agentic workflow allows a model to choose some steps based on observations. The surrounding application limits the actions, resources, and impact of those choices. It is useful for variable tasks but offers less predictable paths and call counts.

Beginner — Deterministic versus agentic workflow?

A hybrid workflow combines deterministic control with model-driven interpretation or planning. A state machine defines named states and permitted transitions. The state machine constrains what can happen even when a model proposes something else.

A state machine models valid states and transitions. A DAG, directed acyclic graph, models dependencies without loops. Event-driven workflows react to events such as document.uploaded or review.approved instead of doing all work inside one HTTP request.

Long-running workflows persist progress while waiting for jobs, timers, or people. Retries repeat transiently failing work; timeouts cap waits; schedules start work at defined times. Durable waiting should not consume an open request or a sleeping application…

- Deterministic: known rules and transitions. Best for permission, arithmetic, approvals, and business commits.

Workflow engines and job systems provide different guarantees for dispatch, persistence, recovery, waiting, and coordination. Temporal is a durable workflow platform; BullMQ is a Redis-backed job library; Inngest and Trigger.dev offer developer-oriented…

Beginner — What is MAF?

AI and LLM fundamentals

Microsoft Agent Framework, or MAF, provides agent abstractions and explicit workflows. An agent handles model-driven interaction and tool use; a workflow connects agents and ordinary functions through controlled paths. Microsoft describes it as the successor…

Workflow engines and job systems provide different guarantees for dispatch, persistence, recovery, waiting, and coordination. Temporal is a durable workflow platform; BullMQ is a Redis-backed job library; Inngest and Trigger.dev offer developer-oriented…

A deterministic workflow follows explicitly coded transitions for given inputs and recorded external outcomes. It can call nondeterministic services, but its orchestration rules remain controlled. It is the natural extension of validation, transactions, and…

An agentic workflow allows a model to choose some steps based on observations. The surrounding application limits the actions, resources, and impact of those choices. It is useful for variable tasks but offers less predictable paths and call counts.

An AI agent is software that uses a model to choose actions toward a goal, observes results, and decides what to do next within application limits. A chatbot describes a conversational interface; it may or may not contain an agent. A workflow defines the…

A hybrid workflow combines deterministic control with model-driven interpretation or planning. A state machine defines named states and permitted transitions. The state machine constrains what can happen even when a model proposes something else.

A state machine models valid states and transitions. A DAG, directed acyclic graph, models dependencies without loops. Event-driven workflows react to events such as document.uploaded or review.approved instead of doing all work inside one HTTP request.

Long-running workflows persist progress while waiting for jobs, timers, or people. Retries repeat transiently failing work; timeouts cap waits; schedules start work at defined times. Durable waiting should not consume an open request or a sleeping application…

Beginner — What is MAF?

Beginner — Deterministic versus agentic workflow?

I use a queue for isolated background jobs and a durable workflow platform for long-lived coordination, timers, and human events when justified. BullMQ still needs explicit business lifecycle records; Temporal still needs idempotent activities and…

AI and LLM fundamentals

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