AI curriculum

Course outline for Dynamic and Agentic Workflows

Generated plans must be validated before they control execution. Combine agent planning with deterministic checks and human intervention in an adaptable workflow.

Technology: Workflow Engineering
Duration: 6 hours
Modules: 3 · 2 hours each
Level: Prerequisites listed

About Dynamic and Agentic Workflows

Generated plans must be validated before they control execution. Combine agent planning with deterministic checks and human intervention in an adaptable workflow.

Dynamic and Agentic Workflows Course Objectives

Separate stochastic planning from deterministic execution.
Validate a generated task graph against constraints.
Define adaptation and intervention policies.

Pre-requisites

Programming and task graph familiarity.
Understanding of agent tool use and workflow recovery.

Lab Setup

Computer with a programming runtime and a local task graph runner.
Use generated-plan fixtures or a local model and synthetic tasks in a disposable workspace.

Detailed Course Outline

Proposed modules

Module 1: Planning boundaries

Deterministic vs stochastic stages
Plan generation
Plan validation

Practical outcome: Define constraints for accepting a generated plan.

Module 2: Compiling execution

Dynamic DAG construction
Agent stages
Execution plan compilation

Practical outcome: Convert a validated plan into executable task dependencies.

Module 3: Adapting safely

Workflow adaptation
Runtime decision-making
Human intervention

Practical outcome: Specify when adaptation requires human review.

Practical exercise

Validate and execute a generated task graph, then handle a runtime change with an approval gate.

How we train

Ask about exercises, instructor feedback and the prior knowledge you need. Tool-specific courses marked provisional may become modules in a broader course.

Discuss your learning goals