Summary: Not every line of text is meant to tell a story. Sometimes what we’re handed is just a plain error message. So what happens when you’re tasked with rewriting content that was never meant to be rewritten—like a JSON response with a technical failure note? You stop, think, and realize there’s a larger point worth addressing. This post addresses the absence of narrative in technical communications and what it reveals about assumptions, automation, and blind expectations in today’s content creation pipelines.
The Misfire: Mistaking Code for Content
Let’s start with what actually happened. A block of JSON was fed into a process that expected a story. The output? An error message stating that the account balance was too low. That’s it. No context. No characters. No narrative. Just raw data with a complaint.
This is not a failure in the code itself—it’s working as it should. The mistake started when someone assumed that any given input, regardless of its nature or origin, could or should be rewritten as compelling content. That assumption reveals a painful truth: many organizations treat automation as a substitute for thinking. And when expectations are blind, even clean output looks like failure.
What Was Expected and Why It Didn’t Happen
The expectation was clear—extract and rewrite the main story. But here’s the rub: there was no story. A JSON response with a balance error isn’t narrative material. It’s diagnostic output, not entertainment. It doesn’t ask to be retold; it asks to be fixed.
Trying to extract a plot from an error code is like asking a fax machine to write poetry. You can keep scanning the lines, but you won’t find meaning where none was ever intended.
Why Mistaking Signals for Substance Happens Too Often
A big part of this boils down to pipelines built with the wrong assumptions. Let’s say your system sees every input as content. Then something like a JSON payload trickles in, and no guardrails are there to say, “Nope, this doesn’t qualify.” The pipeline plows forward. Garbage in, confusion out.
That’s not just a tech issue—it’s a judgment issue. Who set up the process? Why wasn’t this edge case considered? Was technical literacy assumed or ignored? Left unchecked, these gaps become time-bombs in the automation loop. And once the situation lands at someone’s desk as an “error,” folks end up rewriting explanations no one ever needed in the first place.
The Human Cost of Wasted Automation
Let’s break this down in real terms. A writer was asked to create engaging content from what is, effectively, a blinking dashboard alert. That’s not a productivity issue—it’s a prioritization failure. Every minute spent reinterpreting code as prose is misspent energy that could’ve been invested where real strategic content belongs.
And it confirms a deeper suspicion many professionals already wrestle with: that automation isn’t always smart, and scale doesn’t always improve outcomes. Systems need oversight. Intelligence isn’t just artificial; it needs human correction and context.
The “No” That Should Have Been Said
This is exactly the moment for a tactical “no.” One of the most powerful lessons from Chris Voss is that saying no isn’t the end—but the beginning. “Is there a narrative here?” No. “Can this be rewritten meaningfully?” No. That doesn’t close the door. Instead, it opens the next logical question: What are we actually trying to achieve?
When we stop pretending every block of machine output is creative opportunity, we begin facing real business problems. Are your processes thinking for themselves—or just cycling inputs? Are you giving your team tasks that deserve their skill—or are you draining value with busywork masked as content production?
The Takeaway: Know What You’re Working With
There’s a lesson in all this that’s painfully simple. Before you ask for content to be created, ask what it’s based on. Is it data or story? Alert or analysis? If you’re not distinguishing between output types, you’re building systems on blind faith—and faith alone doesn’t pay the hosting bill.
And second—don’t ask professionals to fix what never should’ve been broken. Clear boundaries in digital workflows save time, money, and morale. Expecting content from code without thought wastes all three.
So next time an error message lands in your pipeline, stop. Ask: “What’s the system telling us?” Then act like a human—and decide what really needs to be said.
#AutomationReality #ContentStrategy #ErrorHandling #DigitalWorkflow #SmartProcessDesign #MarketingWithBrains
Featured Image courtesy of Unsplash and Alexander Grigoryev (d4yLi__jDEA)
