Stop Blaming the Bot: The Real Reason Your AI Outputs Feel Generic

We asked our team to share the common mistakes they see when using AI, and one overarching theme became clear: treating AI as an all-knowing mind-reader often leads to generic, and sometimes inaccurate, results. 

According to our strategy leaders, human-provided context can have a big impact on the response you get from your favorite AI tool.

The context gap: Why AI needs specificity

Katia Gutierrez, a DataTech Solutions Architect at WebFX, notes that the more details you provide in your prompt, the better AI can understand your needs.

“A common mistake I see in AI prompting is assuming AI is an expert in your field — and not providing enough context for the task,” Katia says. 

When asking AI to complete something for your business, Katia recommends first telling it about your business and industry, the purpose of your request, and what specific output format you expect from your prompt. 

Expert insights

“Always remember: AI is the expert in gathering information, but you’re the expert at interpreting your…needs and guiding the AI to apply the information effectively.”

Katia G.

DataTech Solutions Architect

Putting yourself in the “shoes” of the machine

Macenzi Barker, a DataTech Solutions Architect at WebFX, shares that “put[ting] yourself in the computer’s shoes” and thinking about what you would need from a set of instructions can help make your prompts clearer.

“If you were on the receiving end of the prompt you provided and did not have any additional information beyond what you’ve fed it so far, would you have additional clarifying questions?” Macenzi asks. 

She suggests including those clarifying details in your prompt to get your desired output.

Offering direction when navigating complex data

When moving from text generation to data analysis, the stakes for precision become even higher. 

Paige Yingling, Senior Account Executive at WebFX, finds that the biggest mistakes happen when AI is left to wander through large datasets, like CSV files, without “directional cues.”

If AI lacks these directional cues, it may result in problems with data analysis and incorrect outputs. 

Paige’s solution to a wandering AI is simple: Tell it where to look.

Expert insights

“I tell AI what columns and rows I want analyzed. This has helped AI from looking in the wrong place for the data.”

Paige Y.

Senior Account Executive

Avoiding assumptions when interacting with AI

Perhaps the most innovative way to fix a “bad” prompt is to proactively stop the AI from making assumptions. 

Chris Varner, Head of Results Innovation at WebFX, suggests that people should not assume the Large Language Model (LLM) they’re using fully understands their prompt and its intentions.

He recommends adding a deliberate pause to your prompts. 

“Add to your prompts: ‘Before you write anything, ask me 3-5 clarifying questions about what would make this most useful.’ This lets you understand any assumptions that AI may have based on your prompt and lets you clarify it before getting a response,” Chris shares.

Takeaways from our AI experts

At its core, getting the best results from your AI prompts isn’t about learning to code. It’s about learning to communicate. 

The next time you sit down to prompt your chosen AI tool, remember the advice from our experts: put yourself in the machine’s “shoes,” offer context, and never be afraid to let the AI ask clarifying questions. 

When you offer more details and provide smarter prompts, you don’t just get faster results — you get better ones. 

Mastering the art of the prompt means you’re mastering the future of your business’s digital strategy.