In partnership with
Hey friends. Happy Wednesday.
A founder said something to me recently that felt simple, but revealed something structural.
“I’ve gotten really good at prompting.
But I’m not sure I’m building better products.”
That sentence captures exactly where many professionals are right now.
We’ve learned how to work with AI.
We know how to structure prompts.
We know how to iterate outputs quickly.
But generating faster is not the same as deciding better.
Prompting got you started.
Product thinking will take you further.
The future is not about writing better prompts.
It is about designing better outcomes.
Because prompting improves output quality.
Product thinking improves decision quality.
And in a world where execution is increasingly automated, decision quality becomes leverage.
Today, we’ll unpack this shift at depth.
Here’s what we’ll explore:
Why prompting feels powerful but eventually plateaus
The structural difference between output optimization and outcome design
How strong product thinkers really think — context, constraints, trade-offs, metrics
A step-by-step exercise to transform a basic prompt into a product spec
A self-audit to assess where you are
A 90-day roadmap to move from AI user to product thinker
Formal data backing this shift
A spotlight question for an expert perspective
A premium worksheet to apply this in practice
Let’s go deeper.
— Naseema Perveen
IN PARTNERSHIP WITH YOU.COM
One major reason AI adoption stalls? Training.
AI implementation often goes sideways due to unclear goals and a lack of a clear framework. This AI Training Checklist from You.com pinpoints common pitfalls and guides you to build a capable, confident team that can make the most out of your AI investment.
What you'll get:
Key steps for building a successful AI training program
Guidance on overcoming employee resistance and fostering adoption
A structured worksheet to monitor progress and share across your organization
