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5. Proxy communication

Proxy discovery doesn't work. Plain and simple. Why?

You cannot:
. Understand customers without first-hand observations
. Empathize with customers without direct interaction

If companies are serious about creating products, those doing the work should talk to customers.

4. Lack of direction

You need to understand what's most important now and focus your discovery efforts on uncovering value drivers for that objective.

Without direction, you'll get overwhelmed with all the possibilities.

3. Lack of structure

Without structure, teams will discuss the work more than they will do it.

Here's a simple structure:
. Define the objective
. Explore the problem space
. Name value-drivers
. Prioritize
. Ideate
. Test assumptions - agree on how you document it
. Decide based on evidence

2. Lack of prioritization

You will always have more to do than capacity.
If you don't prioritize, teams will stretch themselves too thin.

It's fundamental to know what you're after and what you're leaving out.
My learning: First, define what you want to explore, then start discovering.

Yet, 5 mistakes set discovery and success apart

1. Research obsession

If delivering something is faster than discovering it, then ship it

Don't do:
. Open-ended research without an objective
. Extensive research without de-risking ideas

Follow this:
The more complex, the more discovery you need

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5. Do What Business Wants vs. Do What Customers Need

Focusing on stakeholders wants is the quickest way of delivering solutions customers couldn't care less about.

You need to understand the business wants while finding the overlap with the customer's needs.

4. Keep Low-value Features vs. Remove Low-value Features

The more features you have in your product, the more complex it becomes

A great product is the one you have nothing to remove, not the one you have nothing to add.

3. Follow Plans vs. Follow Goals

Hard Reality = following a plan becomes the goal while everyone forgets the real goal

A better way:
. Set a goal
. Use your knowledge to define the next step
. Step into the unknown
. Learn from reality
. Adapt action based on reality, not theory

2. Measure Velocity vs. Measure Impact

Knowing how fast you can create output tells you nothing about how fast you drive value.

I discourage teams from velocity reports.

I encourage teams to measure the impact of their work and, based on their learning, decide what to do next.

1. Maximize Features vs. Maximize Value

More features ≠ More value
Creating features without evidence that they solve a problem is a bad product practice. Sadly, that happens too often.

Focus on removing bad ideas fast enough instead of accelerating delivery.

5. Transform Data Into Insights

How long does it take for you to transform data into insights?
AI can do that in seconds, which is surprisingly good :)

. Data alone means nothing
. Transforming data into insights is the magic
. Use AI to accelerate that for you

4. Interactive Prototypes

You can create interactive prototypes in less than a minute with a few AI tools, such as Uizard by Miro Labs.

. Curate your prompt
. Get your interactive prototype
. Tweak it
. Test it
. Learn and adapt

3. Level Up Your Work

Feedback is present, but not everyone will give it to you.
Use AI to boost the quality of your work.

. AI can give you feedback, e.g., Miro offers that
. You can immediately benefit from multiple angles
. Ultimately, leveling up your work

2. Write Product Experiments

The faster you learn, the sooner you succeed.

. Product experiments don't need to take weeks
. AI can help you uncover multiple experiments
. You can start in hours and scale up as you gain evidence
. Beyond that, AI can give you guidance on how to run your experiments