Practical skills
What you will learn
- Define the agent’s task, information sources, tool access and human approval points.
- Configure a bounded workflow and test ordinary, missing-information and failure cases.
- Recognise when the agent should stop, ask for help or hand work back to a person.
Applied learning
A task you can explain and check
Configure a research assistant that retains sources and asks before taking an external action.
Demonstrate an agent on agreed normal and failure cases, including a case where it must stop or request human approval.
Tools and platforms
Work in an agreed environment
Agent configuration, information sources, tool connections, permissions and tests.
The quotation identifies the tool or platform and required access after suitability and instructor capability are confirmed.
Instructor-led service
Agent-building module for training providers
Commission an instructor-led module that takes learners from an agent brief to a bounded training example, tested permissions and clear human handovers.
Audience
Established training providers serving learners who already use AI and are ready to configure and supervise an agent.
Starting point
- Learners can frame an AI task and check the result.
- The provider can identify a suitable training environment and arrange the necessary learner access.
- The brief identifies learner entry level and any coding or platform skills the chosen exercise requires.
Expected work product
A bounded training agent, accompanied by a task brief, permission map, test log and short operating guide.
- A defined purpose, information sources and limits.
- A configured exercise using agreed practice information.
- Tests for normal work, missing information, tool failure and a human approval boundary.
- A record of observed results and a clear stop or escalation route.
Delivery format
Instructor-led delivery within your programme, with a demonstration, guided build, testing and review. The module can be arranged as a workshop or a sequence of sessions.
Sample module agenda
- Task — Define the agent’s job, success criteria, inputs and limits.
Agent task brief. - Demo — Follow a bounded example and identify its information sources, tools and human decisions.
A permission and handover map. - Practise — Configure an exercise in the agreed environment using practice information.
A training agent or configured workflow. - Test — Check ordinary work, missing information, a tool failure and a request that needs approval.
Test cases and observed results. - Apply — Explain how the pattern could transfer to an approved work task and what would need to change.
Operating notes and a transfer plan. - Measure — Review usefulness, output quality and the effort needed to supervise the task.
A short evaluation against the starting brief.
Check the work
Learners demonstrate the example, explain its boundaries and show what happens when it should stop or ask for approval. The provider and AI Venture X agree the assessment rubric and who makes the final assessment decision.
Tool and platform fit
The quotation names the tool or platform and required access after suitability and delivery capability have been confirmed.
Request a provider module quotePractical learning
Task → Demo → Practise → Test → Apply → Measure
Start with a useful task, practise the method, test the result and plan how to apply and measure it at work.
- Understand the task and define a useful result.
- Demonstrate the method and its limits.
- Practise with safe examples.
- Test the output and explain the checks.
- Apply the method to approved work.
- Measure quality, effort and usefulness.
Get a scoped quote
Request a provider module quote
Tell us about your programme, learners and the specialist support you need.
Request a provider module quoteOr copy this email address into your mail app:
Prefer to talk? View discovery-call availabilityYour written quotation confirms the learning objectives, scope, tools and access, teaching arrangements, format, duration and price before you commit.