Category: Data-Framework

AI, Business Models, Cybersecurity, Data-Framework

Structure of High-Quality AI Prompts

Colin Henderson

From various online sources – refer sources below Effective AI prompting is foundational to maximizing business value from generative AI systems. The quality of a prompt directly determines the relevance, accuracy, and usefulness of the AI’s output. Below is a structured guide to constructing expert-level prompts, highlighting mandatory elements, discretionary enhancements, and common pitfalls to avoid. Mandatory Elements of a Good Prompt ———————— Discretionary (Enhancing) Elements ———————— Items to Avoid in AI Prompts ———————— Summary Table: AI Prompt Structure Element Mandatory Discretionary To Avoid Clear Directive ✔ Vague/ambiguous instructions Context ✔ Irrelevant or excessive details Output Format ✔ Unspecified or … Continue reading Structure of High-Quality AI Prompts

Data-Framework

4 Essential Steps to Enhance Your Organization’s Data Capabilities: A Roadmap for Success

Colin Henderson

Data sits at the core of any modern organization. It drives key decisions, shapes strategies, and ultimately determines success. Yet, for many companies, data remains underutilized, and its full potential untapped. Silos of information sit fragmented across departments and systems, critical insights lay buried, and opportunities are missed. It doesn’t need to be this way. With a data maturity assessment, a clear roadmap, and a commitment to building capabilities, any organization can transform how it leverages one of its most valuable assets – data. We’ve outlined a 4-step approach to enhance your data capabilities and maximize the business value of … Continue reading 4 Essential Steps to Enhance Your Organization’s Data Capabilities: A Roadmap for Success