Latest Thoughts
Houston Community College Guest Lecture 05/07/2025
“AI in the Creative Spaces” Guest Lecture for Houston Community College
What happens when you bring AI from the lab and into the classroom?
You inspire the next generation of creators to see AI as a collaborative tool, not just a curiosity.
On May 7, 2025, I was invited to guest lecture a senior-level Web Design IV capstone class at Houston Community College. My session, AI in the Creative Spaces, introduced students to practical, career-relevant ways to integrate AI into their workflows across image, video, code, and content.
From Static to Dynamic: Bringing AI into the Creative Toolkit
The lecture was part demonstration, part dialogue. I showcased real-world use cases of:
- ChatGPT for brainstorming, rapid iteration, and prompt optimization
- Midjourney and DALL·E for visual generation and concept development
- RunwayML for motion graphics and frame interpolation
- Cursor AI for code generation and real-time debugging
- Canva for AI-assisted layout design and presentation building
Students saw how each tool could amplify their skills — not replace them — helping them create faster and smarter while retaining their unique voice and aesthetic.
“AI doesn’t replace the designer, it expands what the designer can do independently.”
Designed for Engagement: How I Structured the Session
Because I was presenting on a classroom projector with limited whiteboard space, the lecture followed a focused structure:
- Part 1: AI for Images — turning prompts into custom visuals
- Part 2: AI for Video — using RunwayML to animate and enhance
- Part 3: AI for Web — showing real-time HTML/CSS output from ChatGPT, Grok, and Cursor AI
- Part 4: Whiteboard Recap — visually connecting tools to outcomes and student goals
The whole presentation deck is embedded below and available to explore in its entirety:
“Your portfolio can’t just look good; it needs to show how you solve problems. AI helps you do both.”
Resource Guide: A Living Reference
To complement the session, I created a downloadable Canva-based resource guide students could access anytime, complete with tool summaries, real prompts, and example workflows:
This guide now lives in my portfolio and serves as a template for future AI-focused presentations.
Why This Matters to Future Creatives
This wasn’t a tech lecture. It was a creative empowerment session, showing students how AI can become part of their everyday workflow without compromising originality.
They learned how to:
- Write effective prompts for visual and written results
- Use AI to accelerate feedback and iteration
- Turn AI output into polished, personal, portfolio-ready work
By making the lecture interactive and anchored in real work, I helped students develop not just awareness but agency. They left with tools they could use immediately.
AI Fluency as a Creative Skillset
This guest lecture represents more than a single event. My broader mission is to demystify AI, make it accessible, and show how it enhances creativity when used with intention.
For employers, collaborators, or educators, this presentation shows how I:
- Translate technical tools into creative workflows
- Build engaging educational materials in multiple formats
- Help others gain confidence using AI, starting where they are
Let’s talk if you’re looking for someone who can teach, lead, and produce creative results while staying at the forefront of AI tools and practices.
“This is the kind of guest lecture that stays with you. AI is no longer a mystery, it’s a method.”
AI-Powered Workflows
Turning Everyday Workflows into AI-Powered Process Improvement

Before AI Can Help, It Needs to Understand Your Workflow
“61% of organizations manage half or more of their content outside official systems, leaving critical processes undocumented and informal.”
Ask five people how they complete a routine task, and you’ll hear five different stories. These aren’t tales of inefficiency; they’re snapshots of reality. People find their way. They rely on memory, sticky notes, screenshots, and instincts honed over time. The real magic of getting work done often lives between the lines of your company’s SOP.
This is where AI meets its first obstacle. No matter how sophisticated the AI tool, it can’t improve what it doesn’t understand. If your workflows are scattered, improvised, or undocumented, your AI investment may only end up perpetuating confusion.
Even tried-and-true methodologies like Lean or Six Sigma depend on having reliable, observable processes to analyze. Without visibility into how people actually work, neither humans nor AI can make meaningful improvements.
Why SOPs Aren’t Enough Anymore
Standard Operating Procedures (SOPs) outline how things are supposed to work. But in most organizations, what’s documented is only half the story. What’s not written down, the side conversations, the tab-switching rituals, the workaround scripts, is where most of the real workflow lives.
If you try to layer AI on top of an SOP without understanding how people actually do the work, you’ll get unpredictable results. Optimizations will be misaligned, reports will be formatted incorrectly, and automation bots will click the wrong buttons. Tools like NotebookLM can’t surface what hasn’t been captured.
Think of SOPs as stage directions. What you need is the actual performance.
What Is an Individual Workflow?
An individual workflow is the path someone takes from “task received” to “task complete.” It includes every decision, every shortcut, and every nuance, even the ones they don’t realize they’re making.
For example, submitting a travel expense involves more than uploading receipts. It might include digging through emails, renaming PDFs to a specific format, cross-checking with a personal spreadsheet, and waiting for an unofficial nod from finance. That’s the workflow. Unless AI can see the whole process, it can’t offer meaningful help.
This is the work layer where AI can become a brilliant assistant or an annoying interloper.
Why AI Needs Workflow Context to Be Useful
AI needs specificity. It needs a map. Drop it into a process with missing pieces, and it will start guessing. And guesswork is expensive in business.
We’ve all seen automation fail because it lacked context. Maybe a chatbot gave a customer the wrong answer, or a document generator filled in the wrong template. These aren’t technology failures; they’re clarity failures.
To make AI work for your business, you must teach it the rules and rituals. And that starts with documenting what your people are actually doing. NotebookLM can give AI that context, but only if the information is clear and grounded in real practice because it’s documented.
How to Capture Real-World Workflows
Here’s a five-step approach to documenting workflows in a way that actually prepares your business for AI:
- Pick a high-impact task. Start with something repeated often, like onboarding, responding to inquiries, or submitting reports.
- Shadow the people who do the task best. Observe their screens, watch their clicks, ask questions, and capture even the “this is just something I do” moments.
- Map the steps in sequence. Use simple language. Include software tools, bookmarks, email templates, folders, and physical aids.
- Ask: What’s manual? What’s repetitive? What requires judgment? This helps you distinguish between what AI can handle and should remain human-led.
- Compare this to your current SOP. You’ll likely find gaps, areas where your documentation needs to catch up with reality.
This is also a good time to pull from established frameworks like Lean or Six Sigma. These methodologies emphasize reducing variation, identifying bottlenecks, and eliminating non-value-adding steps, all critical when looking for opportunities to improve or optimize how work gets done. With AI analysis tools like Google NotebookLM, these frameworks can be tailored to fit your company’s actual workflows and SOPs. By grounding your documentation in real behavior and layering it with structured analysis, you create a powerful system for continuous improvement that delivers real-world results.
Once your workflow is mapped, consider loading it into NotebookLM to make it easier for AI to understand, search, and reuse.
Example: One employee uses a macro to reformat spreadsheets before sending them to leadership. This isn’t in the SOP, but it saves hours weekly. Once it’s documented, that task is ripe for AI assistance.
Why I Use Google NotebookLM
Once you’ve mapped your real-world workflows, the next step is making that information accessible to your AI tools. That’s where Google NotebookLM comes in.
NotebookLM is an AI-powered research and documentation tool that lets you organize your knowledge into source-based notebooks. You can upload SOPs, meeting notes, workflow observations, PDFs, and even entire knowledge bases and query that content using natural language.
Unlike traditional AI chat tools, NotebookLM is grounded in your sources. That means every answer it gives is traceable, contextual, and specific to your content. It’s not just guessing; it’s pulling from the material you’ve taught it.
NotebookLM gives AI the context to act like a smart assistant, not a clueless intern.
This makes it an ideal companion for workflow discovery. As you document how work is really done, you can feed that knowledge directly into NotebookLM and use it to:
- Generate accurate SOPs and quick-reference guides
- Ask follow-up questions across projects or tasks
- Collaborate with team members on shared knowledge
- Train other AI tools (like ChatGPT or Copilot) with better prompts
Integrating NotebookLM into your process makes your workflows visible, searchable, explainable, and scalable. Now, add documents to NotebookLM’s “Sources” containing well-documented methodologies like Six Sigma and tell the AI to look for ways to optimize your SOPs and/or workflows. You now have an extremely powerful consultant at your disposal. Optimization becomes achievable and sustainable.
Modern SOPs: Blending Structure and Flexibility
Once you’ve captured individual workflows, it’s time to upgrade your SOPs. This is not to rigidly lock everyone in, but to provide clear guidance on where AI belongs, and human flexibility remains essential.
A next-generation SOP might include:
- Clear, documented steps for both humans and AI
- Built-in flexibility for edge cases and exceptions
- Specific AI commands like “Use Copilot to summarize notes before submission.”
- Checkpoints for human validation
These dynamic SOPs become more than documents—they become playbooks for collaboration between people and their digital assistants, especially when paired with tools like NotebookLM, which turn those documents into interactive knowledge bases.
Real Results: What You Unlock by Doing This
“74% of companies prioritize AI, but few align it to real workflows.”
(PwC Global AI Study white paper PDF)
The companies that invest time in workflow discovery and integration see real benefits:
- More useful AI tools: Optimizations that actually save time and reduce stress
- Improved training: SOPs reflect reality, so new hires get up to speed faster
- Fewer errors: Tasks happen the same way each time, with AI or humans following reliable steps
- Innovation: Employees can offload grunt work and focus on improving systems
Start With a Conversation
AI can’t guess how your business runs. It needs you to show it. And that starts by talking to your team.
“How do you really do this task?”
That one question can uncover the hidden knowledge you need to unlock optimization. It’s not about documenting every click; it’s about surfacing the logic behind the work and using that insight to make AI smarter, faster, and more helpful.
AI isn’t here to replace your people. It is here to learn from them; the sooner it does, the sooner it can contribute.
Check out my next post HERE for a tool I use personally to interview SMEs and document individual workflows.
AI-Augmented Real-Time Learning
AI-Augmented Real-Time Learning (ARTL) — Why I Can Learn Anything with AI
What if I told you I could learn almost any well-documented skill, standard, SOP, task, etc., in real time as I work on it?
That’s not an exaggeration; it’s how I work today, thanks to what I call AI-augmented real-time Learning (ARTL).
Learning on demand is more valuable than ever in a fast-moving world where tools, processes, and expectations constantly evolve. ARTL is a method I’ve developed (and refined daily) to acquire new skills and solve problems in real time using AI tools like Google NotebookLM, ChatGPT, Microsoft Copilot, and others without waiting for formal training.
What is AI-Augmented Real-Time Learning?
AI-augmented real-time Learning (ARTL) means learning as you work, guided by AI. Unlike traditional learning, which often happens before or outside of tasks, ARTL is about gaining knowledge while solving the problem.
This is powered by Interactive AI Learning (IAL), a conversational approach in which I collaborate with AI to break down complex tasks, ask targeted questions, and iterate toward solutions. AI isn’t just giving me information—it’s acting like a real-time coach, adapting its guidance based on my questions and feedback.
“What about accuracy? Give me a standard operating procedure or a well-documented reference to analyze, and its accuracy can be exact.”
So, what’s the secret to accuracy in this learning system? It’s all about building context and using the right sources. General-purpose AI tools like ChatGPT and Copilot are powerful, but I bring in Google NotebookLM, my AI research assistant, to go beyond surface-level answers.
With NotebookLM, I can upload and reference specific documents, standards, articles, and project files, turning them into a trusted, queryable knowledge base. This ensures that everything is source-backed and that my AI-driven decisions are anchored in fact, not just probability.
NotebookLM helps me:
- Extract insights from official documentation and SOPs instantly.
- Compare source material across tools or platforms during active problem-solving.
- Keep learning loops fast and accurate by grounding answers in official, curated sources (i.e., your company’s SOPs).
AI’s responses improve with every iteration as I layer in more context, helping it give relevant, targeted answers that align with my unique learning needs. This makes AI a true learning partner, not just a search tool.
Why This Matters to Employers
Most people struggle when facing new systems or unfamiliar tasks, but with AI, I don’t.
I’ve trained myself to use AI as a learning partner, meaning I can take on new tools, processes, and challenges with minimal ramp-up time.
“You won’t have to wait for me to take a course, I’ll learn it while doing the work.”
For employers, this means hiring someone who is:
- Self-sufficient and fast to adapt.
- Able to solve problems on the fly without waiting for support.
- Constantly improving, upskilling every day through real tasks.
- Ready to document what I learn for team-wide use, creating guides and training materials from my AI-driven discoveries.
To support this, I use Microsoft OneNote, a powerful tool for organizing AI-generated insights, curating source-based notes, and maintaining structured documentation. Combined with NotebookLM, it allows me to build living knowledge bases that are actionable and shareable across teams.
“AI has taught me more than any single course or book because it teaches me exactly what I need to know, exactly when I need it, and now it can do it with sources I trust.”
Conclusion: What I Bring to the Table
In today’s world, you don’t just need people who know things—you need people who can learn anything fast and apply it immediately.
That’s what I bring.
Let’s talk if you’re looking for someone who adapts in real time, solves problems independently, and leverages AI, including source-based tools like NotebookLM to get results.
Report problems with this page – Contact Me
