AI Thinking, Development & Design

Sean Wilson has developed strong practical capability in applying generative AI and prompt engineering to research, analysis, problem solving, strategy, communication, design, digital development and executive productivity.

His approach is focused on using AI to turn ideas and business problems into practical outputs, rather than treating AI as a technology exercise in itself. He has extensive hands-on experience with tools such as ChatGPT, Google Gemini, CoPilot and Claude, using them to explore problems, develop and test ideas, create content and visual material, build digital solutions and improve the speed and quality of his own work. This builds on more than 20 years of experience across technology, SaaS, data, commercial leadership and digital transformation, giving him a practical understanding of where AI can create value and where human judgement remains essential.

He has developed a strong practical understanding of the role of Large Language Models (LLMs) in generative AI, including how they process and generate language, the importance of context and instructions in shaping outputs, and why their responses need to be critically evaluated rather than simply accepted as factual. His broader background across technology, SaaS, data, commercial leadership and digital transformation provides useful context for understanding both the capabilities and limitations of LLM-based tools, and how they can be applied to practical business problems.

Sean has also used AI in a practical vibe coding capacity to turn ideas and business requirements into working digital solutions without needing to be a traditional software developer. This has included using AI to generate, refine and troubleshoot HTML and other web code, embedding custom functionality and presentation elements into Google Sites and other digital environments, and iterating through problems with AI until the solution works as intended. This reflects a practical ability to use AI as a development and problem-solving tool, translating an outcome he wants to achieve into instructions, testing the resulting code, identifying errors and refining the solution. It also demonstrates how AI can extend his existing technology and digital transformation experience without requiring him to personally write software from scratch.

He has also used AI extensively for design and visual communication, creating a wide range of practical business outputs including marketing material, infographics, presentations, visual concepts, executive reporting and other information designed for different audiences. This includes using AI to translate complex information into clearer visual formats, develop concepts and layouts, refine presentation of information and rapidly iterate different approaches. The emphasis is on using AI as a practical design and communication capability rather than simply generating images, helping turn business information and ideas into outputs that are easier to understand and more engaging.

His current AI skills are principally centred around the business, commercial and practical capability around AI, rather than being an an AI engineer, machine-learning specialist or coder.

His supporting AI skills include:

• Prompt Engineering: Crafting clear instructions, context, roles and constraints to get more accurate and useful outputs from tools such as ChatGPT and Claude. Refining instructions through prompt iteration when the initial output fails, rather than accepting default suggestions.

• AI & Data Literacy: Understanding how AI produces outputs, interpreting information critically, and recognising potential errors, hallucinations, limitations and inconsistencies.

• Practical AI Application: Exploring how off-the-shelf AI tools and emerging software can be applied to research, analysis, problem solving, productivity and practical business tasks.

• AI-Assisted Development: Using AI to generate, modify, troubleshoot and refine HTML and other code for practical digital solutions, including web content and functionality.

• AI-Assisted Design: Using AI to create and refine marketing material, infographics, presentations, reporting and other visual business communications.

• Critical Evaluation: Assessing the quality, relevance, reliability and potential risks of AI-generated information before using it in business or decision-making.

• Error Detection: Spotting hallucinations, logic gaps, or security flaws in AI responses.

• Business & Technical Translation: Bringing a business and commercial perspective to AI opportunities, helping identify useful applications and communicate business requirements to technical people and technology teams.

• Non-Technical AI Adoption: Developing practical understanding of how businesses can adopt AI without needing to become AI developers or build the underlying technology themselves.

Sean's interest in AI is driven by its practical potential rather than the technology for its own sake. He is particularly interested in how rapidly developing AI software can be used to turn real business problems into practical solutions, while continuing to build his understanding of the technology and its applications.