Operating Agentic Systems
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Course Details
Designing an agentic workflow is only the beginning. Once a workflow moves into repeated use, new questions emerge: Who monitors it? What counts as failure? How are incidents investigated? What happens when behavior drifts? How are costs controlled? How are changes approved? Without operating discipline, agentic systems can become difficult to trust and harder to manage.
1Course Description
This Advanced-level course focuses on the operation of agentic systems after design and pilot work. It helps learners understand the practices needed to monitor, control, recover, review, and improve agentic workflows in ongoing use. The course treats agentic systems as operational responsibilities, not one-off experiments. Learners examine operating models, performance monitoring, exception patterns, failure recovery, escalation, incident handling, misuse controls, cost exposure, resource governance, change management, and drift control. By the end of the course, learners should be better prepared to support agentic systems that remain useful, controlled, economical, and accountable beyond initial deployment.
2What This Course Helps You Do
This course helps learners move from agentic workflow design to operational stewardship. The bottom-line value is sustained control. Agentic systems may support productivity and responsiveness, but they also introduce monitoring, incident, cost, and accountability requirements. For individuals, this builds advanced operating capability. For organizations, it supports safer use, clearer escalation, stronger reliability, and more disciplined management of agentic workflows over time.
3What You Will Learn
By completing this course, learners will be able to:
- Define what it means to operate an agentic system beyond the pilot stage
- Build an operating model for agentic workflows in production or repeated use
- Clarify roles for system owners, business owners, reviewers, escalation contacts, and governance stakeholders
- Monitor performance, exception patterns, task outcomes, and control health
- Identify signals that indicate weak performance, misuse, drift, or rising operational exposure
- Design escalation paths for failures, uncertain outputs, blocked tasks, and high-risk events
- Create recovery routines for agentic workflow breakdowns
- Investigate incidents involving incorrect outputs, inappropriate actions, unauthorized use, or control failure
- Assess whether controls are working as intended
- Manage cost exposure related to tokens, tool calls, human review effort, retries, and inefficient workflow design
- Define resource-governance expectations for agentic systems
- Apply change-control discipline when prompts, tools, data sources, roles, or workflow logic change
- Recognize and manage drift in behavior, outputs, assumptions, and operating conditions
- Create review routines that support ongoing improvement without uncontrolled change
- Communicate operating requirements to technical, operational, governance, and leadership stakeholders
4Who This Course Is For
This course is for operations leaders, AI governance teams, system owners, product owners, workflow managers, business process owners, transformation teams, and practitioners responsible for agentic workflows in active or repeated use. It is most useful for learners who already understand agentic workflows and now need a stronger operating model for reliability, control, cost, and accountability.
5Why This Course Matters
Operating agentic systems matters because AI-enabled workflows do not remain stable simply because they worked in a demo or pilot. Inputs change, users change, costs accumulate, exceptions appear, and workflows may behave differently across contexts. Without operating routines, organizations may discover failures only after harm, waste, or loss of trust. This course gives learners a practical foundation for keeping agentic systems under active oversight.
6Module Overview
This course is structured to move learners from operating-model design into monitoring, recovery, incident response, cost control, resource governance, change management, and drift control.
The course includes the following modules:
- Module 1: Operating Model for Agentic Workflows
- Module 2: Monitoring and Performance Management
- Module 3: Failure Recovery and Escalation Playbooks
- Module 4: Incident Handling, Misuse, and Control Effectiveness
- Module 5: Cost Control and Resource Governance
- Module 6: Change Management and Drift Control
7Practical Outputs You Can Produce
AISDI™ courses are work-product-driven. This means learners are encouraged to turn course ideas into usable outputs such as notes, prompt sets, checklists, decision aids, plans, templates, review routines, and role-specific artifacts. The examples below are indicative only. Learners can use ALMA™ to adapt outputs to their own role, industry, organization, workflow, current priorities, and practical constraints.
Examples of practical outputs from this course may include:
- agentic system operating model
- role and responsibility map for system operation
- performance monitoring checklist
- exception-pattern review routine
- failure recovery playbook
- escalation and incident response plan
- misuse and control-effectiveness checklist
- cost and resource exposure review
- change-control log structure
- drift monitoring checklist
- operational review cadence
- leadership briefing on agentic system operating requirements
8Learning Components and Format
This course is delivered through AISDI™’s AI-integrated learning environment and is designed for structured, self-paced, practical learning.
The learning experience includes:
- Modular online course content that can be completed on demand
- Practical explanations linked to real work, role context, and implementation decisions
- ALMA™-guided activities that help learners test, apply, and extend course ideas
- Scenario-based prompts and practical examples where relevant
- Job-role and context-aware prompts that support applied understanding
- Work-product-driven learning that helps learners produce usable outputs
- Knowledge checks and learning activities that reinforce understanding
- A final verification process for validated completion
9How AISDI™ Learning Works
AISDI™ courses are active, AI-interactive learning experiences. Each course combines instructional content, practical examples, visual material, and the Agentic Learning Multi-Dynamic Assistant™ (ALMA™) as part of the course experience.
The aim is practical capability, not passive course completion. Learners get the most value when they work through the course content, use ALMA™ to clarify and extend their understanding, complete the guided activities, and connect course concepts to their own role, workflow, organization, or personal context.
Visuals and graphics support the learning experience, but the main value comes from active engagement with the material and the embedded ALMA™ interaction layer. This helps learners move from awareness toward usable outputs, better judgment, and more confident application.
10ALMA™ in This Course
ALMA™ operates inside the AISDI™ course experience as the learner-facing AI interaction layer. In this course, learners can use ALMA™ to ask questions, clarify difficult concepts, test their understanding, and translate course ideas into their own working context.
The key value is contextualization. Learners can work with ALMA™ to explore how the course applies to their own job role, industry, organization, team, responsibilities, challenges, tools, and current level of AI maturity. Instead of leaving learners to interpret general course content on their own, ALMA™ helps them connect the material to practical decisions, workflows, outputs, and next steps relevant to their circumstances.
In this course, ALMA™ can help learners map operating responsibilities for their own agentic workflows, draft monitoring criteria, create failure-recovery routines, identify cost risks, and adapt operating controls to their organization’s size, workflow maturity, and risk tolerance.
11Course Language and ALMA™ Language Support
The course content is authored in English. Learners can interact with ALMA™ in more than 100 languages for clarification, examples, explanation, and contextual discussion, subject to the capabilities and limitations of AI-generated multilingual interaction. The official course content, completion process, and certificate remain based on the English course version.
12Knowledge Checks and Learning Activities
The course includes structured learning activities, knowledge checks, and applied prompts that help learners test understanding, reinforce key ideas, and connect course content to practical use. These activities support preparation for the final completion verification process.
13Time Commitment
Approximately 10 to 12 Hours of structured, self-paced learning, plus time for ALMA Activities™ and applied work-product development.
14Validated Completion Certificate
Learners who successfully complete the course and final verification process receive a Validated Certificate of Completion showing the course title, completion status, and relevant AISDI™ certificate alignment.
Certificate alignment: AI∇⋮ Expert™
15What This Is Not
This course is not a basic introduction to AI agents, a software operations manual, or a vendor-specific platform guide. It is a practical AISDI™ advanced course focused on operating agentic systems safely, reliably, economically, and under appropriate human oversight.
Access Options
This course is included in the Advanced+ subscription tier and may also be available through selected course passes, bundles, learning paths, or business access options.
Individual learners can explore subscription access. Teams, businesses, training providers, partners, and organizations can enquire about structured access options, including course passes, custom bundles, learning paths, cohort access, or enterprise deployment.
At a Glance
- Included In:Advanced+ Subscription
- Certificate Alignment:∇⋮ Expert™
- Primary Skills Clusters:Prompting Context Knowledge AI and Agentic Workflows
- Role / Audience:Manager
- Function / Use Context:Productivity
- Industry Context:Cross Industry
- Topic / Capability Focus:Agentic Workflows
- Duration:10 to 12 Hours
- Status:In Development