What number of occasions have you ever heard that (and even uttered it underneath your personal breath)? I do know I’ve heard it in conversations. I additionally know I’ve questioned the identical factor a couple of product or two — hey, the concept right here is tremendous easy, let’s get a pair buddies collectively and make the identical factor, solely higher!
I like João’s take right here. He reminds us that the core use case of an app or SaaS is commonly as simple because it sounds. But it surely’s the a scarcity of “second-order pondering” that forestalls from understanding the complexities behind the scenes:
Was the workforce short-staffed and compelled to make concessions?Was the venture managed in a waterfall, stopping some concepts from making it into the discharge?Was there a time constraint that influenced the course of the venture?Was the finances simply not there to afford a particular characteristic?Was there disharmony on the workforce?
There’s a lot that we don’t see behind the product. João articulates this so clearly when he explains why an organization like Uber wants a whole bunch of cellular app builders. They’re not there to help the preliminary use case; they’re charged with fixing second-order elements and hopefully in a manner that retains complexity at a minimal whereas scaling with the remainder of the system.
The world is messy. As software program is extra ubiquitous, we’re encoding this chaos in 1’s and 0’s. It’s greater than that. Some eventualities are harder to encode in software program than their pre-digital counterparts. A bodily taxi queue on the airport is kind of easy to grasp. There’s no GPS know-how concerned, no geofencing. An individual and a automobile can solely be in a single place at a time. Within the digital world, issues get messier.
Why can’t I edit my tweets?! Twitter ought to enable that.
It’s the identical deal. Options are sophisticated. Merchandise are sophisticated. Sure, it could be superior if this app had one explicit characteristic or used some slick framework to hurry issues up — however there’s at all times context and second-order pondering to think about earlier than going straight into answer mode. Once more, João says it significantly better than I’m in a position to:
It’s simple to oversimplify issues and check out new, leaner applied sciences that optimize for our use instances. Nonetheless, when scaling it to the remainder of the group, we begin to see the dragons. Those that didn’t construct their software program the suitable manner. Whole tech stacks relying on libraries that groups can’t replace as a consequence of causes™. Shortly, we begin realizing that our lean manner of doing issues might not serve most conditions.
Talking for myself a minimum of, it’s tempting to leap straight into an answer or some conclusion. We’re downside solvers, proper? That’s what we’re paid to do! However that’s the place the dragons João describes come into sight. There’s at all times extra to the query (and the reply to it). Until we slay these dragons, we threat making false assumptions and, finally, incorrect solutions to seemingly easy issues.
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