Solve Someone Else’s Problem
Episode 16 helps you move beyond private AI use by solving a real problem for someone else. Use this classic companion page to listen, read and understand the idea before moving into the full Learning Design View.
Listen or download wherever you prefer.
You can follow Zero to AI on the major podcast platforms and download episodes for later.
What this episode is about
Episode 16 of Zero to AI is about moving AI capability out of your private workspace and into a small, useful collaboration. Personal productivity gains can stay hidden unless someone else can point to a clear work outcome you helped improve.
The aim is not to become the unofficial AI helpdesk. It is to find one defined problem, help someone work through it safely, and capture a simple piece of external evidence that shows your workflow created value.
AI capability becomes more credible when someone else can explain how it helped them do better work.
The simple peer-help loop
A good peer consult stays small, practical and safe. You are not redesigning someone else’s whole workflow. You are helping them solve one clear bottleneck, then recording what changed.
Look for a colleague who regularly loses time to summaries, updates, analysis notes, briefing material or other text-heavy work.
Choose one task that can be improved safely inside a short working session, without taking responsibility away from the person who owns it.
Talk through the structure, context and checks while your colleague operates the AI tool on their own screen.
Record what the work was like before, what changed afterwards, and a short written reference from the person you helped.
What to look for
Good candidates are tasks that are repetitive, text-heavy, easy to explain and low enough risk to practise on safely. Think weekly status updates, meeting summaries, short briefing notes, consultation summaries, research digests or first-pass document restructuring.
Avoid confidential, sensitive or high-risk work unless your organisation’s rules clearly allow the tools, data and process you are using. This exercise is about building trust, not creating a hidden workaround.
Keep the keyboard with them
The person you are helping should control their own screen. You can guide the structure, but they should see, check and own the output.
Make the result observable
Capture a simple before and after: time saved, clarity improved, friction reduced, quality lifted or confidence increased.
Ask for a short reference
A useful reference does not need to be dramatic. Three honest sentences from the person you helped can make the value much easier to explain later.
Keeping the work safe and accountable
Keep the consult inside your workplace rules, privacy expectations and data protection requirements. AI tools need direct supervision; every important claim, citation or conclusion should be checked manually against the original material before it is used.
The goal is to build practical team confidence without creating hidden risk, false accuracy or dependency on one person.
Suggested peer-consult prompt
You can use this as a starting point with your preferred AI assistant. It is included here as static guidance only. The full Learning Design View gives you the structured fields and final reference asset builder.
Act as a practical AI workflow coach. Help me support a colleague with one text-heavy work bottleneck. Ask me for the task, audience, current process, normal time required, source material, privacy constraints, quality requirements, AI-assisted workflow, human checks, result achieved, time or clarity improvement, and a short peer reference. Keep the workflow safe, realistic and easy for the colleague to repeat without depending on me.
Practical reflection
This episode is about making your AI capability visible through helpful work. The proof comes from solving a real problem for someone else and recording the result in a way that can be understood later.
Who is one person you could help this week, and what is one small text-heavy task you could improve safely?
Where to go next
This page is the classic companion version of Episode 16. It is useful if you want to listen and read without using the interactive Learning Lab. When you are ready to build the actual peer workflow reference, move into the full Learning Design View.
You can also return to the Learning Journey, browse the Zero to AI blog, or use the Start Here page to understand the wider approach.
This is the classic companion view.
The main Episode 16 Learning Design View remains the place for guided responses, local saving, progress tracking and the final peer workflow reference. This page is intentionally simpler, so people who prefer the previous podcast/article format can still listen and read without entering the interactive Lab flow.
To use the full guided experience, visit the Episode 16 Learning Design View.
Ready to turn the idea into evidence?
Move from the classic companion page into the full Episode 16 Learning Design View when you want to capture the peer consult, build the reference asset and save your progress locally.