Summary: When dealing with artificial intelligence or any form of automation, it’s easy to forget that machines don’t think like people. AI reads data with strict logic—if the input isn’t structured correctly, it will flag an error. This post explains why “I apologize, but the raw text you provided does not contain a story that I can extract and rewrite…” isn’t just a tech hiccup—it’s a window into how we must rethink communication with machines, and, by extension, with each other and our clients.
Understanding the Signal Behind the Syntax
The phrase that triggered all of this—”I apologize, but the raw text you provided does not contain a story that I can extract and rewrite…”—is not only an error message. It’s the AI’s way of saying: This is not usable input. That message exposes something critical about how artificial intelligence interacts with us: it doesn’t guess. It doesn’t “fill in the blanks” emotionally or infer context like a human would. It processes what is there—and if nothing legible is given, no meaningful response follows.
So the broader impact? Input quality defines the output value. This isn’t just true for AI—it’s true in business, negotiation, client communication, and storytelling. If your message is vague, your audience walks away unclear. If your proposal lacks structure, your client won’t commit. If your data is bland, your marketing dies in silence.
Why Machines Need Structure—and So Do We
The original text wasn’t a story. It was basically a JSON error. Machines choke on things like that when they’re expecting plaintext narrative. But let’s be honest: people do too. We just don’t call it an ‘error message’—we call it confusion. The problem is the same. If format doesn’t match the function, understanding collapses.
This reveals an often skipped truth in communication: structure is not frosting—it’s the cake. Whether you’re training an AI model, pitching a new product, negotiating a business deal, or coaching a client through their next move—you need a framework beneath that communication. That’s what lets people—and code—process meaning.
Every “No” Is an Opening
Let’s look deeper into that AI phrase. It said, “I cannot generate a story from this type of data.” That’s a form of “No.” But in Chris Voss terms, that “No” is power. It’s not the end of the road; it’s the beginning of real discussion. What would’ve happened if the user stopped, mirrored that phrase, and asked:
- “So you’re saying this file doesn’t contain story content?”
- “What would you need instead?”
- “Can you explain what kind of input works better?”
These are open-ended questions. They turn errors into conversations. They invite clarity. Isn’t that exactly what we want in every client conversation, marketing message, presentation, and contract negotiation?
When Lack of Data Mirrors Client Behavior
Let’s bring this back to marketing—especially professional services. How often do clients deliver unclear input? A scattered email, vague goals, undefined values—and then they expect you to generate a clear, refined outcome. It’s no different than feeding code fragments into an AI expecting a story. Garbage in, garbage out.
Here’s the thing: most clients aren’t being careless. They don’t actually know how to give the input. Just like many users don’t know what AI platforms require. That’s where your authority—and your empathy—comes in. You guide them to become better communicators by asking:
- “What outcome would make this worth it for you?”
- “Can you walk me through what you’ve already tried?”
- “What’s standing in the way right now?”
That’s when they stop dumping you raw information and start co-creating direction with you. That’s when you go from being a vendor to being their navigator.
Errors Are Not Endpoints—They’re Insight Flags
An error message like the one we started with isn’t a failure. It’s a flare. A signal that the system—be it AI, business, or client—is trying to operate without enough clarity. These moments are where persuasion lives. Where trust can be built. Where experts stand up and lead.
Don’t gloss over failure. Confirm your client’s suspicions. Yes—this is hard. Yes—the last approach didn’t work for a reason. Yes—it’s not that they’re broken, but that they were flying blind without a map. When you frame things this way, you become trusted not because you offer magic—because you offer *sense*.
Turn Technical Limitations Into Strategic Teaching Moments
This AI rejection is deeper than a file-loading glitch. It’s a marketing masterclass: clarity matters, format matters, context rules everything. It’s your job to recognize when your prospects are sending you ‘raw text’—scattered ideas, mismatched expectations, unsupported assumptions—and then to educate them without condescension or cliché.
The question to ask yourself now is, “Where in my business is the response: ‘I can’t work with this input’—but I just haven’t put it in words yet?”
That—right there—is the opportunity. Not a bug. A signal. A call to bring structure, clarity, and dialogue back into your practice.
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Featured Image courtesy of Unsplash and Md Mahdi (VZoecsZCL3Y)
