Online AI training for Australian work
Saifety combines AI safety, prompt engineering and product training in one course library. Each lesson turns a recognisable workplace situation into a decision you can practise and use again.
Current lesson
Prepare the data before the prompt
Lesson progress is saved
Each outline names the audience, the work covered and the practical result. It does not hide the course behind a vague promise about becoming an AI expert.
Foundation course
12 lessons
Australian staff and managers using AI at work
Make sound calls about workplace information, approved tools, unreliable answers, hostile instructions and mistakes that need to be reported.
Recognise when a task needs less data, a different workspace, closer human review or no AI at all.
The work covered
Relevant tools
Foundation course
10 lessons
Anyone who uses generative AI for everyday work
Turn a loose request into a brief that another person can inspect. Choose the useful context, set the evidence boundary and define what a finished answer should contain.
Prepare prompts with a clear job, source limits and review method, then revise the instruction when an answer misses the mark.
The work covered
Relevant tools
Product course
12 lessons
Teams using Copilot across Microsoft 365 and the desktop app
Choose the Copilot surface that suits the job, work from permitted files and understand what permissions do before you ask for a summary or draft.
Move between Copilot surfaces without assuming the account, files, connectors and data boundary work the same way in each one.
The work covered
Relevant tools
Product course
25 lessons
Teams using Claude across chat, Microsoft 365 and supervised workplace workflows
Use Chat, Projects, Skills, Artifacts and Microsoft 365 with a clear job and source boundary. Practise Word edits, Excel calculations, Outlook drafts, PowerPoint updates and supervised Cowork tasks using a complete synthetic business case.
Prepare a permitted Claude workflow, check its claims, calculations, changes and proposed actions, then hand the exact reviewed result to the person who owns the decision.
The work covered
Relevant tools
Product course
12 lessons
Developers and technical teams using Claude Code in a repository
Set repository instructions, permission boundaries and a testable task before an agent edits code. Review the diff and evidence before the work moves on.
Run a bounded Claude Code task, verify the result and prepare a useful review handoff without exposing secrets or trusting generated claims.
The work covered
Relevant tools
Product course
10 lessons
Teams using ChatGPT for documents, research, analysis and repeat work
Use chats, Projects, Canvas, search and data analysis without treating every surface or account as the same workplace boundary.
Choose the right ChatGPT workflow, prepare the source material and review each factual or operational claim before use.
The work covered
Relevant tools
Product course
12 lessons
Developers and technical teams using Codex locally or for cloud tasks
Give Codex a bounded software task, the repository rules and a clear verification path. Keep approval for risky actions and deployment with a person.
Choose a local or cloud Codex workflow, inspect the work it performed and hand over evidence that another developer can check.
The work covered
Relevant tools
Inside a lesson
The format changes with the skill being taught. Nobody needs eight screens of text when one realistic choice can expose the gap.
A short explanation sets up a recognisable job and the decision that matters.
Scenarios, sorting, spotting and rewrites make you choose before the reasoning appears.
Feedback connects the answer to the work, the data boundary and the next sensible action.
Selected challenges run prepared material through a live model and score the prompt.
You can move back to an earlier question, repeat a completed lesson and return to the course toolkit when the work changes.
Feedback explains the reasoning and maps to the content taught in the lesson. Progress remains saved between sessions.
Course questions
Course access, repeats, certificates and what each exercise asks you to do.
No. The foundation courses begin with ordinary workplace decisions and plain language. Product courses explain the relevant tools without assuming that every learner is a developer or AI specialist.
Yes. You can return to completed lessons and repeat the exercises. That is useful when your workplace adopts a new tool, changes a policy or wants people to refresh their judgement.
Yes. Prompting Fundamentals covers the job, context, examples, limits, output formats, revision and review. Live challenges let you test your prompt and receive feedback tied to a fixed scoring rubric.
The same safety habits run through every product course. You will see how the account, approved workspace, file permissions, connectors and local or cloud execution change the right workflow.
Your completed lessons remain available to revisit. Each product course also includes a workplace toolkit for checking data, choosing a surface, building a prompt and reviewing the result.
Open the first module of any course without a credit card. You can use the lesson and exercise format before choosing a plan.