A process safety engineer turned a years-old idea into a safety training site

Achievements - Generated a website that I would have never been able to create without AI and the learnings from the AI Mastery! The Right Call exists to help crews pause at the moment where a safer decision is still possible — so they can go home safe at the end of the shift. - Brought to light an idea that I had for several years but never felt confident on how to do it the little time that a full-time job and an active 8 years old son leave. - Created and MVP website ready to be launched and tested as soon as I receive approval from my current company that there is no conflict of interest. - Designed a novel decision-focused safety framework that aims to shift training from rule-following to conscious choice under pressure - Transformed real industrial incidents and near-misses into actionable learning micro-cases for frontline workers - Integrated neuroscience, human factors, and process safety into practical, field-ready tools - Developed early prototypes of Choice Point cards, micro-scenarios, and toolbox-talk formats - Established a foundation for AI-enabled learning and evaluation without increasing administrative burden Tools - ChatGPT: for discussing the idea and identify the target audience, the integration of neuroscience to change the behavior of front-line workers, to adjust language to the target audience, to develop micro-scenarios from recent incidents. Also the Lovable initial prompt was generated and adjusted to add more pages to Lovable later. - Custom ChatGPT: do search for recent incidents and extract relevant information. - Lovable: to design the initial website, and database. Pictures were created in Lovable and then adjusted or modified through prompting. Text modified and generated within the app. Created the database to collect information - Unsplash: to search for images and ideas. Methodology The Right Call methodology is built on a simple but powerful idea: modify the automatic behavior of front-line workers to modify their responses in high-risk situations by: 1. Pause – interrupt automatic behavior in high-risk moments 2. Perceive – recognize weak signals, uncertainty, and pressure 3. Choose – make the safest viable decision, not the fastest or most convenient 4. Act – execute with clarity and shared understanding 5. Reflect – convert experience into learning before the next decision It combines: - Process Safety principles - Human Factors & Cognitive Load theory - Neuroscience of stress, habit, and decision-making - Storytelling and experiential learning Learnings - YES I CAN! - With AI tools I finally have the means to help workers in a way that empowers them to make the right decision when it is the most important: before the accident. - Colors on website are try to reflect the content of each page, - Most serious incidents are preceded by ordinary decisions made under pressure, not lack of knowledge - Rules alone fail when time pressure, authority gradients, or production stress dominate - Emotional engagement dramatically improves memory, recall, and behavior change - Frontline workers already know many hazards — what they lack is permission and structure to pause - Learning is most effective when people experience the tension of the decision, not just the outcome URLs - The page is not published yet because I need permission from my company to ensure there is no conflict of interests.