Chapter 1: Understanding the Role of Product Owners

Have you ever considered that Product Owners function as prompt engineers, but instead of interacting with machines, they work closely with developers?

"Product teams and developers collaborating to unveil new features."

Murphy's Law states, "Anything that can go wrong, will go wrong." This phrase resonates with many in the product management field. How often have well-intentioned directives from the Product team been meticulously executed by developers only to miss the mark? This disconnect arises because each role operates within its own context, leading to varied interpretations of the same goal. So, how can we bridge this gap?

I've written extensively about various strategies to address these challenges. Most of them rely on methods that require practice and immediate feedback for effective learning. The crux of my recommendations is rapid iteration, which can be hard to implement. The major challenge is that we need the entire team to learn and evolve together. While this collective growth is beneficial, it can also be time-consuming and costly. Compared to the approach I’m presenting here, traditional methods often seem slow.

To truly enhance your learning practices, how can you facilitate swift iterations?

The good news is that, with today's incredible tools, particularly ChatGPT, there's an incredibly fast way to learn. The key isn't just using ChatGPT, but knowing how to leverage it effectively.

In the most rapid agile cycles, from ideation to launch, there's still a time gap of several hours. In many development scenarios, this delay can range from one week (as seen in the quickest SCRUM methodologies) to six months (as in frameworks like SAFe).

Consider how little you can learn if feedback takes six months. Even with a one-week delay, your opportunities to learn are limited. You might try something, wait a week, attempt to recall your reasoning, and then try a new approach—leading to just four chances for improvement in a month. Conversely, if you can shorten that loop to just three hours, your ability to learn skyrockets. With fresh memories of your actions, you can test new ideas multiple times a day, offering you a plethora of chances to refine your skills—provided you already possess a baseline competence.

Now, imagine a scenario where feedback takes mere seconds, all thanks to ChatGPT.

With such rapid iterations, you can significantly enhance your ability to craft user stories. You’ll quickly identify misunderstandings, gaps in information, and areas for improvement. ChatGPT excels at highlighting ambiguities and unclear definitions. While it isn’t human, it mimics human-like reasoning, producing inconsistent results when faced with vague information. By prompting ChatGPT to develop small software components, we can uncover missing details.

The Example

Let’s look at a practical example. Suppose we want to design a simple app for a number-guessing game. We could start with a prompt like this:

Prompt: Create an app to play a number-guessing game.

The output is surprisingly effective:

But is this truly what we envisioned? A closer inspection reveals discrepancies. ChatGPT, like our developers, fills in gaps with its interpretations:

• There are no instructions; players need to know they should input a number and press "guess" or "Enter."
• An attempts counter was added, which we didn’t request.
• It includes feedback on whether the guessed number is higher or lower than the target, which, while helpful, wasn't part of our original vision.
• The range for the random number is from 1 to 100, which we also didn’t specify.

Once we recognize these issues, we can iterate. For instance, if we want to restrict the game to a single-digit number, we could refine our prompt:

Prompt: Create an app that has one secret one-digit number and asks the user to guess it. If the guess is correct, display a congratulatory message; if not, prompt them to try again.

ChatGPT responds effectively:

This version is indeed closer to our expectations, but we still need to consider:

• The range is correct as per our request.
• It accurately provides feedback for correct and incorrect guesses.
• It includes a prompt to guide players, which we anticipated even if we didn’t explicitly ask for it.
• However, there’s still no termination condition; players can continue guessing indefinitely.

Without delay, we adjust again:

Prompt: Create an app that has one secret one-digit number and asks the user to guess it. If they guess correctly, display a congratulatory message and a button to play again; if incorrect, prompt them to try again.

This modification addresses some issues but introduces new ones:

This new version meets some expectations:

• It allows guessing a one-digit number and congratulates the user upon a correct guess, with a button to restart.
• The button has a clear label.

However, we lose feedback on incorrect guesses, as it no longer displays a “try again” message or instructions for players, even though we expected them.

The beauty of this iterative process lies in its speed and simplicity. Within the time it takes to brew a cup of coffee, we can refine our idea multiple times, each iteration yielding valuable insights and bringing us closer to our goal.

While I could continue this example to showcase further steps until we reach the ideal solution, there's one more crucial lesson: what happens if we repeat the same prompt?

Prompt [repeated]: Create an app that has one secret one-digit number and asks the user to guess it. If they guess correctly, display a congratulatory message and a button to play again; if not, prompt them to try again.

The resulting output may be slightly better this time—purely by chance:

Did ChatGPT learn from the previous attempt? No, it didn’t. The improved outcome was just luck. Repeating prompts often yields a mix of better and worse results.

The Learning Journey

So, how long does it take to move from one attempt to another? Just seconds. Consider this: ChatGPT generates results far quicker than a developer can create a small feature. However, we spend more time analyzing and understanding the output than ChatGPT does generating it.

This rapid feedback loop is excellent for learning. After each prompt, you can evaluate the outcome and identify what worked and what didn’t. The ability to repeat prompts and receive varied results allows you to dive deeper into ambiguities.

Now, think about this: if you can check your assumptions in mere seconds instead of hours or even days, how much can you practice in a single day? How frequently can you dedicate time each week to enhance your skills? Consider the exponential growth in your understanding and abilities over just a few weeks.

So, what’s holding you back? With ChatGPT, you have an exceptional training environment right at your fingertips. Experience rapid iterations, instant feedback, and a wealth of learning opportunities. Why not take the plunge and begin your journey of accelerated skill enhancement today?

Are you interested in an app to automate the feedback loop discussed in this article? If so, please share your thoughts in the comments.

Chapter 2: Leveraging ChatGPT for Product Management

This video demonstrates how to utilize ChatGPT to free up time for Product Managers, offering practical strategies for efficiency.

In this video, learn how to harness ChatGPT for product management and boost your productivity effectively!