Why Your AI Prompts Are Failing You (And What to Do About It)
In the age of AI-powered everything, you don’t need to be a coder to build software, write content, or analyze data. Tools like ChatGPT, Claude, and Gemini have made advanced language models accessible to just about anyone.
But if you've ever typed something into an AI chatbot and ended up with generic fluff, broken code, or irrelevant results, you're not alone.
It’s not the AI that’s failing you. It’s your prompt.
Welcome to the world of prompt engineering, a skill that’s quickly becoming essential for modern entrepreneurs and builders.
What Is Prompt Engineering?
Prompt engineering is the practice of designing effective input instructions (prompts) that get the best possible output from AI models.
In plain terms: it's learning how to talk to AI so it gives you what you actually want.
Just like asking a vague question in a Google search won’t get you a useful result, asking AI the wrong way can lead to lackluster, confusing, or flat-out incorrect answers.
Common Signs Your Prompt Is the Problem
You get overly generic answers that lack depth or context.
The output is technically wrong or completely misaligned with your expectations.
The AI “hallucinates” information that doesn’t exist.
You’re doing way too much editing or rewriting after the fact.
You keep trying different prompts and still aren’t getting closer to what you need.
Sound familiar? You’re not alone, and the good news is, you can fix it.
Why Prompting Matters More Than You Think
Large language models (LLMs) like ChatGPT and Claude are powerful, but they’re also deeply contextual. That means they rely heavily on how you ask your question to determine how to respond.
A poorly written prompt is like handing a contractor a napkin sketch and saying “build me a house.”
You’ll get something, sure. But probably not what you want.
5 Prompting Mistakes That Are Sabotaging Your Results
1. Being Too Vague
❌ “Write a blog post about marketing.”
Too broad. The AI doesn’t know who your audience is, what tone you want, or what kind of marketing you’re talking about.
✅ Better: “Write a 1,000-word blog post about Instagram marketing tips for wellness coaches who are new to social media. Keep the tone encouraging and beginner-friendly.”
2. Skipping the Setup
Don’t assume the AI knows your business, your goals, or your product. Give it context.
✅ Example: “I run a software agency that helps early-stage startups launch MVPs. Please write a LinkedIn post about the cost of poor software planning, geared toward non-technical founders.”
3. Not Specifying Format or Style
AI can mimic styles and formats really well, but only if you ask.
✅ “Write this as a 5-bullet LinkedIn post with a hook, takeaway, and CTA.”
4. Expecting Perfect Code From One Line
AI can write solid code but you’ll need to break down your request, add comments, and include specifics.
✅ “Write a Python script that fetches weather data from OpenWeatherMap, logs the temperature every hour, and sends an email alert if it drops below freezing.”
5. Not Iterating
Great results often come from refining your prompt, not nailing it on the first try.
Start broad, then improve based on what you get back.
How to Write Prompts That Actually Work
Here’s a simple formula to follow:
[Role] + [Task] + [Context] + [Style] + [Output Format]
🧠 Example:
“You are a marketing strategist. Write a 3-paragraph email introducing our new mobile app to existing customers. The tone should be friendly and conversational. Include a CTA to download the app.”
Or for code:
“You are a senior Python developer. Write a function that takes a list of email addresses and removes duplicates. Add inline comments explaining each step.”
Real Talk: Why This Matters for Your Business
If you’re relying on AI to help you move faster, your prompts are either a superpower or a speed bump.
Prompt engineering isn’t just a fun trick. It’s a strategic skill.
For founders, it means more accurate research and clearer messaging.
For content creators, it means better first drafts and less cleanup.
For developers, it means cleaner scaffolding and faster prototyping.
For product teams, it means smarter automation and tighter workflows.
Whether you’re bootstrapping a SaaS or running a growing service-based business, learning how to communicate effectively with AI can unlock serious ROI.
Not Getting the Results You Need?
You’re not alone. At Tibsar Software, we’ve worked with dozens of founders and teams who tried to build with AI and ended up stuck with half-baked MVPs, buggy outputs, or time-wasting prompts that just didn’t deliver.
We offer expert AI debugging and technical consulting services designed specifically for founders who want to use AI effectively, not blindly.
Final Thoughts
AI is only as smart as the instructions you give it. If your prompts are failing you, don’t blame the tech. Level up your communication.
Think of prompt engineering like a new language: one that can save you hours of time and thousands of dollars when used right.
Want help crafting smarter prompts or fixing broken AI-generated workflows?
We’ll help you turn half-baked AI output into high-impact results.