AI and Data in Business
Enterprise AI Agents and Agentic Workflow Engineering
This in-depth course develops directly applicable capability in Enterprise AI Agents and Agentic Workflow Engineering. It connects Agent Architecture and Work Decomposition, Tool Use and Enterprise Integration, and State, Memory, and Context Engineering to the decisions, controls, and activities participants need to perform in their workplace.
Overview
Practical learning for workplace transfer.
This in-depth course develops directly applicable capability in Enterprise AI Agents and Agentic Workflow Engineering. It connects Agent Architecture and Work Decomposition, Tool Use and Enterprise Integration, and State, Memory, and Context Engineering to the decisions, controls, and activities participants need to perform in their workplace. The five-module curriculum progresses toward Agentic Workflow Engineering Lab, using evidence, scenarios, and work products appropriate to the subject.
Objectives
- Analyze agent architecture and work decomposition, including planner, executor, memory, tools, and orchestration components.
- Configure or structure tool use and enterprise integration, including function schemas, api contracts, authentication, and least privilege.
- Evaluate state, memory, and context engineering, including session state, durable memory, summaries, and retrieval.
- Manage control, evaluation, and observability, including human approval gates, policy checks, and escalation paths.
- Apply agentic workflow engineering lab, including model a multi-step enterprise process with decision points.
Target audience
- Professionals responsible for this subject area
- Managers, supervisors, and team leaders
- Analysts, specialists, engineers, or coordinators working with the relevant processes
- Project, implementation, assurance, or improvement team members
- Professionals preparing for broader responsibilities in this field
Program outline
A clear structure for the learning journey.
Program outline
Outline points are grouped in one designed block instead of being treated as separate module cards.
Module 1: Agent Architecture and Work Decomposition
Planner, executor, memory, tools, and orchestration components
Single-agent versus multi-agent workflow decisions
Deterministic steps, probabilistic decisions, and stop conditions
Module 2: Tool Use and Enterprise Integration
Function schemas, API contracts, authentication, and least privilege
Connecting agents to knowledge, business systems, and queues
Idempotency, transaction boundaries, and error propagation
Module 3: State, Memory, and Context Engineering
Session state, durable memory, summaries, and retrieval
Context budgets, data minimization, and tenant isolation
Preventing stale memory and cross-workflow contamination
Module 4: Control, Evaluation, and Observability
Human approval gates, policy checks, and escalation paths
Tracing plans, tool calls, outcomes, latency, and cost
Task-success evaluation and failure taxonomy
Module 5: Agentic Workflow Engineering Lab
Model a multi-step enterprise process with decision points
Configure tools, permissions, retries, and approval controls
Test abnormal paths and produce an operational runbook
Materials provided
- ○ Course-specific presentation slides
- ○ Guided exercises, scenarios, or configured-environment activities appropriate to the subject
- ○ Course-specific worksheets, checklists, or calculation templates
- ○ Applied workplace case materials
- ○ 4D Certificate of Completion issued by 4D Training & Consultancy
- ○ Post-course support for implementation questions
Training Options
Programs can be delivered in-house, online, or in a blended format depending on your team's schedule, location, and learning objectives. When an external certificate or exam is included, certification rules and fees remain under the relevant awarding body's policies, while 4D provides the training and preparation support.
Why choose 4D
4D Training & Consultancy adapts the program to the client’s operating environment. Delivery combines structured explanation with subject-specific analysis, exercises, and implementation decisions so participants can transfer the learning to real responsibilities without implying vendor authorization.
Related courses
AI Agents and Workflow Automation for Business Operations
This course helps business and operations teams understand how AI agents and workflow automation can reduce repetitive work, improve handoffs, and support faster execution. Participants learn how to map processes, identify automation candidates, design human-in-the-loop controls, and manage risks before scaling AI-enabled workflows.
View courseAI Change Management and Adoption for Managers
This course helps managers lead teams through AI adoption with clarity, confidence, and responsible use. Participants learn how to address resistance, redesign work, set expectations, coach employees, define safe-use rules, and measure adoption without creating fear or unrealistic expectations.
View courseAI for Business Leaders and Department Managers
This course helps business leaders and department managers understand how artificial intelligence can be used responsibly across departments. Participants explore practical AI use cases, productivity opportunities, governance requirements, implementation risks, and decision-making considerations without needing a technical background.
View course