From GPTPromptSpot to AI-Driven Strategy: How AI Shaped My Approach to Marketing

Jan 287 min read

Key Takeaways

How early adoption of AI reshaped content marketing strategies.
The fundamentals of prompt engineering and why it matters.
Wins, failures, and lessons learned from using AI tools.
The transition from using AI for efficiency to creating custom AI tools.
What SMBs, entrepreneurs, and creators can learn from this journey.

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Introduction: A New Chapter Begins

The world of marketing has been in a state of rapid change over the past couple of decades, but recent AI advances accelerated that transformation exponentially. Before ChatGPT became a widely known tool, I was already testing its capabilities, exploring how it could enhance my workflow and improve efficiency for content marketing. This blog continues the journey from Part 1, focusing on how I discovered AI’s potential, learned its limitations, and began building custom solutions to bridge the gaps.

My early attempts with AI weren't always smooth sailing. Some early results were frustratingly generic, and the promise of AI didn’t always match reality. But through trial, iteration, and an understanding of how to guide AI properly, I uncovered a way to make it a valuable part of my marketing strategy.

Early Adoption of AI in Marketing

The Problem AI Needed to Solve

Before AI, content marketing required significant time and effort—research, drafting, refining, optimizing. It was effective but labor-intensive, especially when handling multiple projects at once. The challenge was scaling high-quality content without sacrificing originality.

When I first encountered AI tools like ChatGPT, the potential was obvious:

Could AI help draft blogs, social media content, and marketing copy faster?
Could it generate fresh ideas and assist in brainstorming?
Could it optimize SEO elements without needing constant manual refinement?

AI had the ability to do all of this—but not without learning how to use it effectively.

First Steps with ChatGPT

Like many early adopters, my first attempts with AI-generated content were underwhelming. It produced text that was technically correct but often bland, lacking depth or originality. It needed direction—a human touch to shape it into something valuable.

Through experimentation, I found that the quality of input dictated the quality of output. This realization led me to focus on prompt engineering, the art of structuring prompts in a way that elicits high-quality responses from AI.

What is Prompt Engineering?

Prompt engineering is the practice of crafting clear and specific instructions to guide AI models, like ChatGPT, toward generating high-quality responses. Think of it as giving directions—vague instructions lead to unpredictable results, while precise details help AI produce content that aligns with your goals.

With my background in communications, I approach prompt engineering as both an art and a science. I push the limits of language models by testing different structures, tones, and styles to see how they respond. Through trial and refinement, I’ve developed several novel techniques that make AI-generated content sound more human—capturing natural flow, conversational rhythm, and authentic brand voice.

Instead of relying on generic AI outputs, I’ve fine-tuned methods that bring personality, nuance, and strategic intent into the process. This has allowed me to create content that not only engages audiences but also maintains brand consistency, proving that AI is most powerful when paired with a strong understanding of communication principles.

Just like learning to speak different dialects of the same language, each AI model responds differently to prompts. A technique that works well with one model might not yield the same results with another. That’s why I continuously refine my approach, adapting to the nuances of each language model to maximize effectiveness. Understanding these differences allows me to craft prompts that extract the best possible output, ensuring AI-generated content aligns with specific business and brand needs.

This is where the concept of prompt engineering became critical. Instead of asking AI to simply “write a blog about digital marketing,” I learned to provide detailed instructions, tone preferences, structural guidance, and even examples of the type of content I wanted. The difference was night and day.

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Breakthroughs and Setbacks: Learning to Work with AI

The Wins

After refining my approach, I began seeing real benefits:

Speed & Efficiency: Drafting blog content in minutes rather than hours.
Idea Generation: AI helped overcome creative blocks by providing multiple perspectives.
SEO Optimization: AI suggested metadata, keywords, and structured content effectively.

One of my biggest successes was using AI to assist in social media marketing campaigns. By generating multiple variations of copy based on audience personas, we could A/B test at scale and refine messaging much faster than before.

The Challenges

Of course, AI isn’t perfect. Some major challenges included:

Generic Output: AI-generated content often lacked emotional nuance and required heavy editing.
Inconsistency: The same prompt could yield different results, requiring fine-tuning.
Bias & Limitations: AI sometimes reinforced biases or misunderstood context, needing human oversight.

AI wasn’t replacing creativity—it was enhancing it. Once I embraced that mindset, I saw AI as an assistant, not an author.

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From User to Builder: The Transition to Custom AI Tools

Beyond ChatGPT: Finding More Efficiency

While using AI for content creation improved efficiency, I realized there were still gaps that off-the-shelf AI tools couldn’t solve. The next step in my journey was building my own AI-powered solutions that catered specifically to marketing and content creation needs.

Building Custom AI Solutions with Bubble.io

Before Lūmaix, I launched GreenSplashSEO, a digital marketing venture focused on helping businesses improve their search visibility and content strategy. This was where I started refining my approach to automation and AI-driven content generation, testing how AI could integrate with SEO best practices.

I then turned to Bubble.io, a no-code platform that allowed me to build custom AI-driven tools tailored to my workflows. This opened up a world of possibilities:

Automating Repetitive Tasks: From content scheduling to generating keyword-rich metadata.
Creating AI-Powered Prompts: Designing structured prompts that generated high-quality outputs consistently.
Integrating AI into Client Workflows: Making AI tools accessible to businesses that lacked technical expertise.

What is Bubble.io?

Bubble.io is a no-code development platform that allows users to build web applications without needing extensive programming knowledge. For me, choosing Bubble wasn’t just about ease of use—it was a strategic decision to lower the threshold for bringing my ideas to market quickly. Traditional software development can be time-consuming and expensive, creating barriers for entrepreneurs who want to innovate fast. By using Bubble, I was able to prototype, test, and refine AI-powered marketing solutions without getting bogged down in complex coding.

Beyond just accelerating my own development process, Bubble.io also ensures that the AI solutions I build are accessible to SMBs, entrepreneurs, and creators. Many businesses want to leverage AI but are intimidated by the technical side of implementation. With Bubble, I can create user-friendly, intuitive tools that integrate AI into everyday workflows—without requiring a steep learning curve for end users.

This approach allows businesses to focus on results rather than struggling with complex technology, making AI-powered solutions more practical and impactful for a wider audience.**

This marked a major shift—from using AI reactively to designing AI solutions proactively. Instead of working within the limitations of existing tools, I could customize AI to fit real-world business needs.

Lessons for SMBs, Entrepreneurs, and Creators

The takeaway from my journey into AI is that it’s not about replacing human creativity but about augmenting it. Here are key insights for businesses looking to integrate AI into their workflows:

Start Small: Test AI with low-risk tasks like content repurposing or data analysis.
Focus on Quality Inputs: The better the instructions, the better the output.
Customize When Possible: Off-the-shelf AI is powerful, but tailored AI tools can create game-changing efficiencies.
Always Maintain a Human Touch: AI can assist, but storytelling and brand voice still require human oversight.

Learn more about how custom AI tools can improve your company's productivity.

Conclusion: Incorporating AI-Driven Strategy: The Next Evolution of Lūmaix

AI transformed the way I approached content marketing, but the journey didn’t stop with efficiency gains. The next chapter of Lūmaix was about leveraging AI to drive innovation—helping businesses not just automate, but strategically enhance their marketing efforts.

Coming up in Part 3: The integration of AI into Lūmaix’s full strategy, case studies of AI in action, and how businesses can prepare for an AI-driven future.

AI isn’t just for big corporations—it’s a tool that can empower small businesses, entrepreneurs, and creators to work smarter, not harder. At Lūmaix, we help businesses like yours integrate AI into marketing, SEO, and content strategies without losing the human touch that makes brands stand out.

Let’s talk about how AI can support your goals. Whether you need a smarter content strategy, a website that converts, or AI-driven automation that saves you time, we’re here to help. Reach out today and let’s explore the possibilities