AI Agent Workflows with LangGraph
A bounded agent workflow with saved execution traces. An unsafe action requires approval; an error has a recovery path; a termination limit is tested.
Register your interest. Dates and delivery are confirmed before enrolment opens.
What you will be able to do.
Build understanding, put it into practice and finish with work you can explain.
- An unsafe action requires approval; an error has a recovery path; a termination limit is tested.
Is this for you?
Intermediate learners who can demonstrate the entry competencies listed below. Preparation suggestions are optional.
Before you begin
Write a small function, branch on input and explain an error path Explain method status headers and JSON; send one safe request Create a branch, commit a change and recover an edit
How you will show your progress
An unsafe action requires approval; an error has a recovery path; a termination limit is tested.
From first principles to applied work.
Explain → Demonstration → Guided practice → Review
Planned outline. Lessons, trainer and schedule are confirmed before this course opens.
0190 live minutesModel state and tools
10 min explanation · 15 min demonstration · 45 min practice · 20 min review
Define a typed state for a support triage workflow
02120 live minutesBuild a bounded graph
15 min explanation · 20 min demonstration · 60 min practice · 25 min review
Implement a graph with one read-only lookup tool and a bounded route
03180 live minutesAdd approvals and recovery
25 min explanation · 35 min demonstration · 90 min practice · 30 min review
Pause for approval before a simulated outbound action and resume from checkpoint
0490 live minutesEvaluate runs and document limitations
10 min explanation · 15 min demonstration · 45 min practice · 20 min review
Compare successful rejected and timeout runs with an execution log
How you will practise and be assessed.
The planned assessment checks your result, your judgement and your ability to apply what you learned independently.
- 01
Build the promised result
Demonstrate the promised artifact
WHAT YOUR WORK SHOULD SHOWAn unsafe action requires approval; an error has a recovery path; a termination limit is tested.
- 02
Test a limit or failure
Compare successful rejected and timeout runs with an execution log
WHAT YOUR WORK SHOULD SHOWThe documented failure/uncertainty is visible, and no prohibited action or unsupported success claim occurs.
- 03
Apply it independently
Independently explain and change one assumption in a bounded agent workflow with saved execution traces.
WHAT YOUR WORK SHOULD SHOWThe learner predicts and verifies the change; AI output is not accepted without understanding.
Where this course stands.
Lab assets and supported tool versions are confirmed before teaching
Explore the source reference- Course ID
- S001
- Content
- Course outline in review
- Trainer
- Instructor to be confirmed
- Enrolment
- Not open · requests welcome
- Publication
- Planned
- Catalogue date
- 2026-10-15
Want to learn this?
Share your interest. We’ll confirm availability, batch dates and the fee separately, so you can decide when the details are ready.
- Your course is already selected
- Just your name and email to get started
- No payment or booking commitment
Know what your batch includes.
Learning support, assessment requirements and any certificate terms are confirmed with the batch before enrolment. Include your goals in your course request so the proposed format can be matched to what you need.
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