AI Agents for Business Workflows

About Course

Design and test business agents that choose tools within a controlled workflow. Build a read-only service agent, define tool contracts and state, add review gates and evaluate failures, costs and outcomes. Includes 24 lessons, complete fictional cases, private practice with feedback and a 48-question final quiz.

LO01: Specify an agent’s objective, permitted tools and completion criteria.
LO02: Trace a working read-only agent from request to evidence-based answer.
LO03: Design a controlled agent loop with a reliable result contract.
LO04: Enforce access and action permissions outside model instructions.
LO05: Handle invalid, failed and uncertain operations without duplicate effects.
LO06: Keep context and delegated work scoped, traceable and reviewable.
LO07: Evaluate an agent using evidence-based quality and resource measures.
LO08: Prepare a controlled release recommendation supported by test results.

Course Content

Agent purpose and scope
Distinguish agents from fixed workflows and define a bounded task and tool contract.

01. Distinguish an agent from a fixed workflow
02. Write an agent task charter
03. Design a narrow tool contract

Build the first tool-using agent
Connect a model and mock tool, validate arguments and track execution state.

Planning and structured outputs
Bound tool use, route requests and validate final results separately.

Evidence and authority
Use authorised knowledge, gate consequential actions and handle untrusted content.

Failure and recovery
Validate actions, classify tool failures and reconcile retries.

Context, memory and coordination
Manage conversation context, persistent information and specialist handoffs.

Evaluation and observability
Create test cases, score outcomes and interpret traces and operating costs.

Release and integrated practice
Use shadow testing, operational monitoring and a complete service-agent case.

Assessment

Add this certificate to your resume to demonstrate your skills & increase your chances of getting noticed.

Student Ratings & Reviews

No Review Yet

AI Agents for Business Workflows

About Course

What Will You Learn?

Course Content

Agent purpose and scope
Distinguish agents from fixed workflows and define a bounded task and tool contract.

01. Distinguish an agent from a fixed workflow

02. Write an agent task charter

03. Design a narrow tool contract

Build the first tool-using agent
Connect a model and mock tool, validate arguments and track execution state.

04. Build a first agent with a mock lookup tool

05. Validate tool arguments before execution

06. Track agent state and completion accurately

Planning and structured outputs
Bound tool use, route requests and validate final results separately.

07. Bound planning and tool use

08. Route requests to the right capability

09. Create a reliable final-output contract

Evidence and authority
Use authorised knowledge, gate consequential actions and handle untrusted content.

10. Use knowledge tools with permission-aware retrieval

11. Gate consequential tool calls with human review

12. Treat external content as untrusted input

Failure and recovery
Validate actions, classify tool failures and reconcile retries.

13. Validate proposed actions with business rules

14. Classify tool failures and choose a bounded response

15. Reconcile retries and duplicate write attempts

Context, memory and coordination
Manage conversation context, persistent information and specialist handoffs.

16. Manage conversation context deliberately

17. Control persistent memory and retention

18. Coordinate specialists without losing control

Evaluation and observability
Create test cases, score outcomes and interpret traces and operating costs.

19. Build an evaluation set before tuning

20. Score outcomes and investigate failure patterns

21. Inspect traces, latency and operating cost

Release and integrated practice
Use shadow testing, operational monitoring and a complete service-agent case.

22. Use shadow testing and staged release

23. Monitor changes, incidents and rollback readiness

24. Complete the service-agent practice and handover

Assessment

AI Agents for Business Workflows – Final Quiz

Earn a certificate

Share this course

About Course

What Will You Learn?

Course Content

Agent purpose and scope Distinguish agents from fixed workflows and define a bounded task and tool contract.

01. Distinguish an agent from a fixed workflow

02. Write an agent task charter

03. Design a narrow tool contract

Build the first tool-using agent Connect a model and mock tool, validate arguments and track execution state.

04. Build a first agent with a mock lookup tool

05. Validate tool arguments before execution

06. Track agent state and completion accurately

Planning and structured outputs Bound tool use, route requests and validate final results separately.

07. Bound planning and tool use

08. Route requests to the right capability

09. Create a reliable final-output contract

Evidence and authority Use authorised knowledge, gate consequential actions and handle untrusted content.

10. Use knowledge tools with permission-aware retrieval

11. Gate consequential tool calls with human review

12. Treat external content as untrusted input

Failure and recovery Validate actions, classify tool failures and reconcile retries.

13. Validate proposed actions with business rules

14. Classify tool failures and choose a bounded response

15. Reconcile retries and duplicate write attempts

Context, memory and coordination Manage conversation context, persistent information and specialist handoffs.

16. Manage conversation context deliberately

17. Control persistent memory and retention

18. Coordinate specialists without losing control

Evaluation and observability Create test cases, score outcomes and interpret traces and operating costs.

19. Build an evaluation set before tuning

20. Score outcomes and investigate failure patterns

21. Inspect traces, latency and operating cost

Release and integrated practice Use shadow testing, operational monitoring and a complete service-agent case.

22. Use shadow testing and staged release

23. Monitor changes, incidents and rollback readiness

24. Complete the service-agent practice and handover

Assessment

AI Agents for Business Workflows – Final Quiz

Earn a certificate

Student Ratings & Reviews

Agent purpose and scope
Distinguish agents from fixed workflows and define a bounded task and tool contract.

Build the first tool-using agent
Connect a model and mock tool, validate arguments and track execution state.

Planning and structured outputs
Bound tool use, route requests and validate final results separately.

Evidence and authority
Use authorised knowledge, gate consequential actions and handle untrusted content.

Failure and recovery
Validate actions, classify tool failures and reconcile retries.

Context, memory and coordination
Manage conversation context, persistent information and specialist handoffs.

Evaluation and observability
Create test cases, score outcomes and interpret traces and operating costs.

Release and integrated practice
Use shadow testing, operational monitoring and a complete service-agent case.