Tìm Kiếm Các Vấn Đề Đáng Giải Quyết với ChatGPT

“This course contains the use of artificial intelligence.”

Most people are told to “be more innovative”.
Very few are told where to point that innovation.

The result? Teams chase random ideas, patch symptoms, and stay busy… but not necessarily useful. Slides talk about “digital transformation”, “AI”, and “innovation”. Your calendar shows firefighting, conflicting priorities, and vague “strategic projects” that never quite land.

This course exists to fix that gap.

Finding Problems Worth Solving is a practical, AI-powered guide to the one skill that sits underneath real innovation and better decisions:

Choosing good business problems – and committing to them.

Instead of giving you yet another list of creativity techniques, this course teaches you how to see your work as a portfolio of problems, and how to use ChatGPT as a structured thinking partner to:

• Spot problems that actually matter.

• Test whether they’re real, leverage, and solvable.

• Decide which ones deserve your time, energy, and political capital.

Think of it as learning to be the portfolio manager of your attention in an AI era.

Why “Problem-First” beats “Idea-First”

In many organisations, “innovation” quietly means:

“Please bring more ideas to the next workshop.”

But great innovators, product managers, and leaders don’t start with ideas.
They start with problems worth solving:

• Problems that connect to real customers and real business metrics.

• Problems that, if solved, remove a whole family of headaches.

• Problems that invite experiments, not endless debate.

This course walks you through a clear, repeatable way to go from:

“Everything feels messy and urgent.”

to

“Here are the 3–5 problems that are genuinely worth our energy – and here’s why.”

You’ll learn to distinguish between:

• Fake problems vs real problems.

• Busy problems vs leverage problems.

• Passive problems (reality hitting you) vs active problems (standards you choose).

And you’ll learn to weave these distinctions into how you talk about work, so you start to sound less like “someone who complains” and more like someone who thinks clearly about what matters.

Run / Improve / Transform – from your perspective

One of the core lenses in the course is a simple but powerful three-part view of work:

• Run – problems that stop you from doing the basics (things break, customers get angry, numbers go red).

• Improve – problems that, if fixed, make your current system faster, smoother, or less painful.

• Transform – problems that, if tackled, change your system: how your team works, what you offer, or how customers experience you.

You’ll learn to see your own day, week, and month through Run / Improve / Transform, and then use ChatGPT to:

• Make your problem list explicit instead of fuzzy.

• Sort it into the right bucket.

• Choose a healthy mix: enough Run to stay credible, enough Improve to create visible value, and a few Transform bets that express real innovation.

This alone changes how you interpret “be more innovative”.
Innovation stops meaning “do crazy new things” and starts meaning:

“Be deliberate about which Run/Improve/Transform problems you choose to carry.”

Problem Physics: Cynefin and the right “treatment”

Not every problem behaves the same way.

Some are like flat-pack furniture: follow the instructions and you’re done.
Others are more like gardening: you experiment, observe, and adjust over time.

In the course, you’ll get a friendly, practical introduction to Cynefin – a framework for thinking about different kinds of problems:

• Simple – known cause-and-effect; best solved with checklists and standard processes.

• Complicated – knowable with analysis and expertise; best solved with investigation and design.

• Complex – messy, adaptive situations; best approached through small experiments, learning, and iteration.

• Chaotic – fire situations; first stabilise, then move the problem into another domain.

You’ll learn how to use ChatGPT to:

• Rephrase your problem in a way that reveals its domain.

• Explore different “treatments” (checklist, analysis, experiment, or stabilisation action).

• Avoid the classic mistakes: writing a giant plan for a Complex problem, or over-analysing a Simple one.

This “problem physics” layer means you’re not just choosing problems; you’re matching them to the right way of working.

ChatGPT as your problem-thinking co-pilot

This is not a generic “how to prompt ChatGPT” course.
Instead, you’ll see ChatGPT being used in a very specific way:

As a thinking co-pilot for your problem portfolio.

You’ll use it to:

• Turn vague frustrations into concrete, observable problem statements.

• Generate candidate problems from customer feedback, team complaints, or messy notes.

• Classify problems by Run / Improve / Transform and by domain (Simple / Complicated / Complex / Chaotic).

• Explore possible ways to test or de-risk a problem before you commit to it.

• Practice how you might talk about a problem with your manager or team – with better framing and clearer logic.

You stay in control.
ChatGPT accelerates the thinking, but you decide:

• Which problems make it onto your list.

• Which ones get promoted to “worth solving”.

• Which ones become active problems you choose to champion.

From task-doer to “problem architect” in your team

Underneath all the tools, the course is about a subtle identity shift:

• From “I do tasks and react to whatever hits my inbox.”

• To “I am deliberate about which problems I hold and how I frame them.”

By the end, you’ll have:

• A written personal problem portfolio – your 3–7 problems worth solving next.

• A simple “Problem Canvas” to keep those visible and updated.

• A more confident way to speak about problems with managers and colleagues – not as complaints, but as thought-through opportunities for impact.

You won’t magically control what your company does.
But you will control where your mind, energy, and innovation time go.

And in a world where AI can generate a thousand ideas in a minute, the advantage shifts to the person who can say:

“Out of all of this, these are the problems that matter. Let’s start here.”