The Rise of Why

The focus on execution is dwindling. Asking “why” is growing. How are we prepping for a “why” driven future?

As the scales tip, how do we define what truly matters?

I’ve been loving the posts lately:

As “whys” become more important, I can see a few key areas spring up:

  1. Systems thinking - Understanding how systems work sets you up to see larger gaps (and create stronger whys)
  2. Getting to know your users - Audiences become more important than ever. Who are you doing this for?
  3. Validation matters - Knowing that you’re doing the right thing. Stop sooner when going the wrong direction.

I’m curious about what everyone here thinks. What other areas become valuable as automation consumes more of the “how” work that we do?

2 Likes

Love this thinking @ben.

For me, I actually prefer this shift toward ‘why.’ It mirrors what we see operationally when we step back from just executing (“what we do”) and focus on why we run them this way. It supports a well rounded pov.

Wooooooot

1 Like

I prefer the shift as well. But that’s probably because I’m a bit biased thanks to Simon Sinek’s work :laughing:

I think our work is complex, and the relationships are even more complex.

One founder working with their first design hire to build a marketing site is fairly simple. They need to execute the what so they can make money on all the ‘why’ of the product offering or service.

Once you have multiple interconnected systems :avocado: , it becomes a question of whether its worth changing or relinquishing certain parts of the system in favor of the new vision, initiative, feature, or brand direction. That has real consequences, and de-risking by validating the why becomes hugely important.

(:avocado: emoji for visual interest in the block of text)

1 Like

This made me think up a new block

There are a couple of pieces to this:

  1. “Why” has always had more components to it.
  2. Execution’s fewer components were larger in scope.
  3. AI decreases the components’ sizes (reduces repetitive work).

Software’s goal was always to automate work. LLMs become powerful helpers.

Curious if you’d reframe this chart differently. (I feel like I could include software itself that shrinks the problem spaces, rather than being AI-specific.)

1 Like

One thing I see here is that this is probably applicable to an existing, mature organization. AI is effective once you’ve chosen your tech stack, design system, etc…

For startups, many of the ‘why’ questions related to how tech stacks and design systems are built are dictated by engineers and designers as they gain alignment with founders.

This means that part of the value of answer why will be to move past the required human interfacing with the ‘how of execution’ to get to AI’s efficiencies.

1 Like

Interesting, with the rise of AI and practices like vibe coding, I feel like we’re actually moving away from “why” and more towards “what”, or maybe something like “quantity to weed out quality”. Seems like the focus is on pushing out content and designs quickly, and then let the bad ones get shaken out in the process of planning and building.

I don’t think this is over-production of content is going to disappear any time soon, so the process of refining the mountain of ideas is probably where it’s important to make sure the “why” can still make an impact.

1 Like

That’s a good callout. Perhaps what was originally needed was a lower cost of execution to try out many things.

That does mean that we’re getting to the why faster. Because of automation, most of the work can be discarded as a means to find the “why”.

Such a great classic Simon Sinek: How great leaders inspire action | TED Talk

Lol.

@ben Why has always been part of design… and people will always love their tools to create and make things. I’d be lying if I didn’t sometimes fall in love with the tools I create more than the things I create.

At the end of the day, most of finding a “why” is being curious.

1 Like

I would agree here. I think what’s shifting is how much time can I put into why.

It also is shifting- the why changes with the new playing fields that spring up with AI.