The Art of Prompting with AI - From Hesitation to Action

Why It Matters

Clear prompting frameworks reduce wasted effort from poor AI outputs and help teams operationalize AI reliably, accelerating the shift from individual experimentation to scalable, business-grade AI capability. Improved prompts can cut errors, raise output quality, and unlock more predictable value from AI initiatives.

Summary

Scrum.org hosted a webinar where professional scrum trainers Rob Vanlannon and Anastasios (Taso) Sorrowos introduced the “Art of Prompting” to address common AI shortcomings—generic, shallow, off-topic or hallucinatory outputs. They framed prompting as a practical technique (starting with defining the task or “assignment”) and shared lessons from client work and a live attendee poll showing “too generic” outputs as the top pain point. The presenters positioned the framework as a simple, repeatable way to steer AI toward more useful, specialist-grade results and discussed applying it to scale AI across organizations. The session combined theory, examples and interactive Q&A to help practitioners move from ad-hoc use to deliberate AI capability building.

Original Description

Prompt engineering is often described as the key to unlocking better results from generative AI, but it’s frequently framed as a skill you either “get” or you don’t. That misconception stops many professionals before they even begin. The real barrier isn’t technical complexity. It’s the belief that you need the perfect prompt on the first try. In this practical, application-focused webinar, PSTs Rob van Lanen and Anastasios Psarros move beyond theory and demystify prompt engineering.