Shall We Stop Building Useless Features? Let Me Tell You How AI Can Help You Rock!
4 steps to reduce waste and boost value
Hi everyone,
I’m getting frequent questions about AI replacing PMs. How true is that?
Many people are claiming AI will make PMs obsolete. Well, I disagree with that, but I’d say backlog managers have no future; AI will replace them. Yet, strong PMs will become even stronger with AI.
Let me tell you what generative AI will transform the game: Product Discovery.
Lately, I’ve heard a lot of wrong things about Product Discovery. Curiously, when it comes to testing solutions, I’m stumbling upon many “confirmation” techniques or “validation” approaches. That’s dangerous.
Falling into confirmation bias is a natural result when you focus on confirming you’re right. A better way is to accelerate learning so you can drop bad ideas.
Let me give you a simple step-by-step approach to boost learning and cut noise.
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A present for you: UPT20 (20% off annual plan) and UPT10 (10% off monthly plan).
Which question is more relevant to you?
How can we accelerate delivery?
How can we drop bad ideas?
Be careful! If you choose the first, you may fall into the feature factory trap. More features don’t mean more value. Yet, dropping distractions fast enough enables you to focus on the promising ideas.
Learning speed is what makes product teams stand out.
Generative AI will empower you to run experiments ten times faster. That’s mind-blowing.
Great tools like Uizard are already available to empower PMs to boost learning. From zero to a clickable prototype in 5 minutes, that’s incredible.
Reduced learning time is vital with digital products because our ideas are often wrong.
✅ Great PMs drop bad ideas fast enough
❌ Bad PMs fall in love with ideas and forget to test them.
How fast can you drop bad ideas?
The faster you can run product experiments, the sooner you learn what’s noise.
Here’s how you accelerate learning in 4 steps.
1. Define success: What’s the desired outcome?
2. Identify your assumptions: What are you assuming to happen?
3. Test critical assumptions: Run experiments to speed up learning
4. Decide: Persevere, pivot, or drop
1. Define success
Know what you want to achieve and what success looks like. What’s your desired outcome? You need to understand what’s in it for customers and the business.
Once you know what success looks like, you can decide if the investment is worth it.
It’s key to separate goals from ideas. The goal represents where you want to land, while the idea is an alternative to drive desired results. The following image represents an e-commerce example:
If you struggle to define the goal, you better refrain from pursuing the idea.
2. Identify assumptions
What does it need to happen so your idea succeeds?
Think about the following questions:
How well do we know customers want it?
How will the business benefit from it?
How might we deliver a valuable solution?
How ethical is it to pursue this initiative?
How will customers understand how to use it?
Answering these questions will reveal your assumptions. Test the ones for you lack evidence, and the idea becomes worthless if the assumption is falsified.
Ignoring assumptions is deadly. It ensures waste and frustration.
3. Test critical assumptions
Now comes the trick: how fast can you run experiments? First, you need to choose the experiment; you’d have several options:
Wizard of OZ: Fake until you can make it
Concierge: Be the product
Survey: Uncover patterns
Interview: Uncover unknowns and patterns
Unmoderated sessions: Let users play with products
Moderated sessions: Observe how users get the job done with your solution
Some experiments are more costly, others faster.
Recently, I stumbled upon Uizard, which enables anyone to create clickable interfaces in less than a minute. You write the prompt, and magic happens. You’ve got a prototype you can tweak and test. This can be a game changer for accelerating learning.
Strive to accelerate experiments and learn from results. The more you speculate, the less you learn. Move away from abstract conversations and start getting hands-on as fast as possible.
4. Decide
Every experiment should have an objective criteria. The result is binary, pass or fail. Based on the result, you can decide upon:
Persevere: run more experiments to gain stronger evidence
Pivot: Change the solution or audience
Drop: Accept it doesn’t work and don’t invest in it anymore
Double down on the winners and cut the losers.
Keep in mind that the faster you learn, the sooner you succeed.
Important to ensure the experiment is reliable, which means that your audience was the right one and they weren’t biased. In doubt, rerun the experiment before making a decision.
Making evidence-guided decisions is critical, but you must ensure the evidence is solid.
Let’s rock the product world together!
Here are three ways I can help you even more:
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Have a lovely day,
David
Let’s rock the product world together.
Thank you for this amazing overview! As I did a course this morning and it said: "AI is to enhance, not replace"