Define AI Roles Before You Deploy Them
Define AI Roles Before You Deploy Them
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Most organisations introduce AI at the task level.
They trial prompts. They test a tool. They ask staff to “try using ChatGPT”.
But when roles aren’t defined first, AI amplifies inconsistency instead of reducing it.
If you don’t define what the system is responsible for, how it should behave, and where it sits in your workflow, you don’t get leverage.
You get drift.
This bundle helps you define AI roles properly before you deploy them.
Who It’s For
Who It’s For
This is for operationally stretched organisations that:
already have teams and reporting obligations
are experimenting with AI but don’t have structure around it
want consistency, not novelty
understand that tools amplify existing systems
If you’re leading an NDIS provider, association, community organisation, or service business that has outgrown informal processes, this will feel familiar.
You don’t need more AI enthusiasm.
You need role clarity.
What Problem It Solves
What Problem It Solves
The problem isn’t “we’re not using AI enough”.
The problem is this:
When AI is introduced without defined responsibility, three things happen:
Outputs vary between staff
No one owns quality control
The system slowly degrades into prompt chaos
AI is cooperative by design. It follows the framing it’s given.
If staff give different instructions, the outputs diverge.
If constraints aren’t defined, the system drifts.
If escalation paths aren’t clear, risk increases.
Defining AI roles first changes the mechanism.
Instead of:
Person → Tool → Random Output
You get:
Defined Role → Structured Inputs → Controlled Output → Human Oversight
That shift creates consistency, accountability, and repeatability.
What’s Included
What’s Included
1. Access to Gerry – AI Role Architect
1. Access to Gerry – AI Role Architect
Gerry helps you define the AI role properly before you build anything.
You clarify:
what the AI is responsible for
what “done” looks like
what it must not do
what knowledge it must follow
Gerry then produces a production-ready system prompt including:
responsibilities
boundaries
required outputs
formatting rules
failure conditions
escalation logic
Clear beats clever.
That’s the design principle inside the guide .
2. Access to Stephanie – SOP Architect
2. Access to Stephanie – SOP Architect
Once your GPT works, Stephanie turns it into operational documentation.
She helps you define:
where the tool sits in your workflow
who owns it
inputs and outputs
approvals and review steps
oversight and governance requirements
Because a working tool without documentation becomes fragile over time .
Build the GPT.
Then systemise it.
3. How-To Guide: “Get Started – Gerry & Stephanie”
3. How-To Guide: “Get Started – Gerry & Stephanie”
You receive the full implementation guide, which walks you through:
The 3 questions to ask before using
How to clarify role + outcome + boundaries
How to build your GPT correctly (using Configure, not Create)
How to test outputs before deployment
How to document and train your team
Human review and compliance safeguards
It is practical and step-by-step not theory .
Why This Matters
Why This Matters
AI is not a staff member.
It’s a structured system that executes instructions.
When you define its role the same way you would define a position description, you reduce ambiguity and protect quality.
When you skip that step, you create invisible risk.
This bundle helps you build the foundation first.
Investment
Investment
Define AI Roles Before You Deploy Them
$12 bundle
Practical. Structured. Immediately usable.
If you want AI to reduce friction instead of creating it, start with role definition.
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