In this episode of AI Productivity Workflow, we explore how the next generation of counselors views AI in education and clinical practice.
Deja McCullough – Template Generation for Clinical Use
Goal: Create reusable note templates for different client diagnoses.
Workflow Steps:
1. Start with an existing case note or simple structure you’ve already written.
2. Prompt the LLM (e.g., ChatGPT) with a request:
“Help me adjust this note into a generalizable template for clients with [diagnosis].”
3. Iterate interactively — refine the language through back-and-forth chat until it fits your clinical style.
4. Save the polished version into a master document (e.g., Google Docs) as a collection of templates.
5. Use and adapt these templates across clients (e.g., generalized anxiety, depression) as time-savers while maintaining clinical accuracy.
Core principle: Iterative collaboration between counselor and AI for structure, not substance.
Dr. Leo Gonzalez – Prompt Engineering and Peer-Review Workflow
Goal: Improve prompt quality and leverage AI for academic and evaluative tasks.
Workflow Steps:
1. Create a “Prompt Library” — store tested prompts categorized by use (teaching, research, writing).
2. Use AI to generate prompts by asking the model:
“Help me make a prompt for [specific task/topic].”
3. Test prompts interactively until results are consistent and useful.
4. Apply prompts to complex tasks, e.g., having the LLM act as a peer reviewer for a journal manuscript.
5. Evaluate model outputs for bias, tone, accuracy, and usefulness.
6. Compare different LLMs via lm-arena.ai, which blind-tests responses from multiple models to see which performs better.
Core principle: Use LLMs not just for answers, but to design better questions and refine workflows through self-generating prompts.
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Dr. Eric Perry speaks with Marty about how anyone can bring AI into their daily workflow — from drafting syllabi to generating reports — with simple, practical steps.
Eric Perry’s Step-by-Step Directions for Using AI
1. Define Your Goal
Decide exactly what you want AI to help with — for example, drafting a syllabus, designing an assessment, creating a project workflow, or producing a report.
Knowing the purpose clarifies how to use the tools effectively.
2. Choose the Right Tool
Pick a platform suited to the task: ChatGPT for writing and planning, Perplexity for research and profiles, Zoom AI Companion for meeting notes, or other specialized apps for images or data.
Not every AI tool does every job equally well.
3. Set Up and Learn the Tool
Create an account and, if needed, use the paid version for full capabilities.
Spend time practicing to understand how the tool responds to your prompts.
Comfort with the tool improves results.
4. Use Specific, Constrained Prompting
Give clear instructions about the format, tone, scope, and sources.
For example: “Act as if you are creating a 15-week counseling syllabus with one weekly reading from this textbook, one discussion prompt, and a grading rubric.”
The more explicit the instructions, the more useful the output.
5. Provide Your Own Source Material
Upload or paste the reference materials you want the AI to use — such as past show notes, rubrics, or course outlines.
Feeding it the right content reduces hallucinations and improves relevance.
6. Verify and Test the Output
Check that references, facts, and other details are accurate and current.
Never assume the AI’s first draft is automatically correct.
7. Refine and Iterate
Edit the AI’s draft as needed and save prompts that work well for reuse later.
Over time, many tools learn your preferences and style, requiring less detailed prompting.
Refinement turns a rough draft into a polished product.
8. Integrate AI Across the Workflow
Don’t use AI only at the end.
Example: Capture meeting notes with a tool like Zoom AI → feed them into ChatGPT → generate task lists, timelines, or assignments → review and refine.
AI can assist throughout the process, improving both efficiency and quality.
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Dr. Yusen Zhai joins host, Dr. Marty Jencius to talk about AI, faculty adoption, and looking at student properties as predicted by AI models.
Yusen's tips
1. Treat the chatbot like a person/RA and converse naturally. He "talk[s] with chat bots as [he'd] talk with a real person," using it like a research or graduate assistant.
2. Don't expect a full answer from a one-sentence prompt-ask it to work step by step. He explicitly says: "I will go step by step. Let's work on this step by step."
3. Ask for clarification when you don't understand something. Example: "I don't understand this concept. Can you clarify for me?"
4. Provide more instructions and iterate; don't treat it like a one-shot search. He contrasts vague asks with giving further instructions and then proceeding step by step.
5. Fact-check what it returns-especially on niche questions. He always verifies answers and consults other sources when something "doesn't add up."
6. Work collaboratively and refine with follow-ups. He uses it to get an initial list (e.g.,"10 articles..") and then asks further questions to drill down and clarify.
7. Use it to plan teaching tasks with its own step-by-step walkthroughs (e.g., outlines and class activities) and request engagement ideas.
8. (Optional technique) Give it a persona/background for simulations (e.g., client role-plays) to practice unlimitedly before real sessions.
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