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Published on: Feb 12, 2026 10:00:01 AM by Caterina Mora
Updated on: February 12, 2026
ChatGPT has been around long enough that most people have used it at least once, and many now rely on it in their day-to-day work. It shows up in emails, meeting prep, schoolwork, marketing drafts, code snippets, and quick research.
And yet, despite how common it has become, a pattern keeps repeating.
Some users get consistent value from ChatGPT and keep finding new ways to apply it. Others feel underwhelmed or frustrated: the outputs seem generic and answers feel shallow. The tool is helpful in moments but never quite delivers what they expect.
In most cases, the issue isn’t the technology. It’s how ChatGPT is being used, and just as often, what users don’t realize it’s capable of doing. Below are the most common mistakes we see, why they matter, and how to avoid them so ChatGPT becomes a reliable, high-value tool rather than a novelty.
Many users approach ChatGPT the same way they approach a search engine: ask a question, scan the answer, and move on. That leaves a significant amount of value on the table.
ChatGPT can do so much more than just retrieve information. It can analyze documents, synthesize viewpoints, extract patterns, draft structured content, and help users reason through decisions. It can summarize a 40-page report, draw conclusions from internal data, or generate a first draft of a presentation based on your strategy notes.
When ChatGPT is used only for quick lookups, organizations miss opportunities to reduce time spent on analysis and synthesis, accelerate preparation for meetings, proposals, and decisions, and turn raw information into usable insight.
The shift required is small but important. Instead of asking, “What is this?” start asking, “What does this mean for us?”
There is no shortage of prompt templates circulating online and many promise dramatic results if you follow the formula exactly. In practice, this approach rarely holds up.
Strong prompts are not magic. They are structured. What matters is not memorizing a clever phrase, but understanding the components that help the model produce useful, relevant output.
A simple way to think about it is this recipe:
Persona + Context + Task + Constraints + Format
Each element plays a role:
While all five are useful, the most important by far are context and task. Most weak prompts fail because they skip them entirely.
We see this most often when people type: "Improve this email;” “Design a logo for my brand;" or “Make this more professional.” When there is little context and an unclear task, ChatGPT has no choice but to guess. The result may sound polished, but it is usually generic and misaligned with what the user actually needs.
ChatGPT improves dramatically with feedback. When users accept the first response and move on, they are effectively freezing the model at its lowest level of understanding. The real value emerges when users react, refine, and redirect. Using these types of phrases can help you drill down to more helpful outputs:
High-performing teams treat ChatGPT like a junior analyst or collaborator. They review the output, provide guidance, and push it to improve. Over a few iterations, quality and relevance increase significantly.
Most people use ChatGPT the same way every time: open a blank chat and start typing. It works, but it is inefficient. Custom GPTs exist to remove that friction.
ChatGPT is a general-purpose tool designed to answer a wide range of questions. A Custom GPT, on the other hand, is built for a specific job. When you create one, you decide how it should behave, what it should focus on, and what information it should use. You can give it instructions, set boundaries, and add relevant knowledge upfront. This turns ChatGPT from a broad, one-size-fits-all assistant into a specialized tool that delivers more consistent, relevant, and efficient results for a particular use case.
A Custom GPT, such as a "Proposal Builder," can streamline your process by generating proposals tailored to your organization's needs instead of starting from scratch each time. It could consistently:
Each time you use it, you begin with a draft that already reflects your expectations and standards, rather than a generic outline.
The GPT Store extends this idea further. It allows people to use or adapt GPTs that others have already built for common needs, such as writing, analysis, learning, or industry-specific tasks. Not every GPT in the store will be useful, but many can save time or serve as a strong starting point.
Ignoring Custom GPTs keeps ChatGPT in “one-off helper” mode. Using them turns it into a repeatable tool that works the way you expect, every time.
One of the most overlooked features in ChatGPT is also one of the simplest: personalization.
By default, ChatGPT knows very little about you. It does not know your role, your industry, how you prefer information presented, or what “good” looks like in your work. Without that context, it responds in the safest, most generic way possible.
Personalization settings allow you to change that baseline. When configured thoughtfully, they help ChatGPT understand things like:
This does not replace good prompting, but it raises the floor. Every interaction starts closer to what you actually need.
Using personalization is not about making ChatGPT “smarter.” It is about making it more aligned, and alignment is what turns a useful tool into a reliable one.
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Caterina works as a Business Analytics Consultant at SVA Consulting, where she partners with clients to connect data and AI to business problems and strategic objectives. She collaborates with organizations to transform complex data into clear, actionable insights that support informed decision making and measurable business impact. Caterina holds a Master of Science in Business Analytics from Duke University’s Fuqua School of Business and applies a strong analytical foundation to help clients achieve their business goals.
