From Prompt to Standard Work
This six-module virtual workshop is for people focusing on process improvements in their organization and want to use AI tools the right way, not just poke around and hope for good results. You’ll start by learning how AI language models actually work and what makes them useful (or not) for your work. From there, you’ll build your own simple, reusable files that AI can use to help with the recurring CI tasks you already do, like writing reports, standardizing templates, or summarizing data. Think of it as building standard work for AI collaboration: a repeatable process with built-in checks, so you can trust the results. Everything is taught through hands-on exercises based on real CI work, not abstract AI theory.
Learning Outcomes
By the end of this workshop, participants will be able to:
- Explain how AI language models generate output by predicting likely words rather than pulling facts from a database, and identify why a fluent, confident-sounding response can still be wrong.
- Apply a structured prompt framework to get reliable, task-specific results from AI tools, including a clarifying-question step that catches missing information before the model gives an answer.
- Analyze how the amount and quality of context you provide affects the output, telling the difference between a thin prompt and a well-supported one, and judging what source material a given task actually needs.
- Evaluate AI outputs against clear criteria and your organization’s governance standards, using human review as a consistent, repeatable check rather than a one-off glance.
- Create reusable markdown artifacts, including a personal context file, tested task files, and a prompt playbook, that turn recurring work into standard work anyone on the team can run.
- Design a maintenance routine that keeps those artifacts accurate and useful as tools, processes, and team members change over time.
Participants get the most value when they bring a recurring task from their own work, a summary, a briefing, a categorization, or a first draft, to build into a working AI tool during the sessions. All exercises use fictional datasets, and the workshop teaches a data-governance gate before any participant applies the methods to real organizational information.
Who Should Attend
This workshop is built for practitioners who own processes and develop people: Continuous improvement and operational excellence leaders, along with those supporting production, quality, and HR/L&D. It’s also great for supervisors and team leads responsible for standard work and problem solving.
Facilitator Bio
Dr. William Harvey teaches continuous improvement practitioners to work with AI the way they work with everything else: with a method and a standard. He built GAUGE, a prompt framework for high-quality outputs, and a system for turning AI prompts into reusable files. Two decades leading plants taught him the thesis under all of it: gains decay when they live in people instead of structure.
Dates: Sept 21, 24, 28, Oct 1, 5, 8
Time: 1-2pm Pacific
Venue: Online via Zoom
Cost: $175 members/$300 non-members
To register, email jennifer@nwhpec.com with participant name(s), email(s), and job title(s).