Experimenting With AI as a Creative Assistant: How I Created My Recent Videos

Over the last few weeks, I have been playing with AI as a creative assistant. Since my multimedia creative skills are - let's say sub par, I have used AI as a partner, or assistant in. The goal is to enhance content to promote knowledge sharing in manufacturing. Not AI as a replacement for expertise, but AI as a way to translate expertise into formats people actually absorb.

As part of this, I created two videos and I wanted to share the behind-the-scenes story of how I made them, what tools I used, and what I learned along the way.

Digital-First & Composable: The Future of Pharma Manufacturing Design

 

Grandpa Learns AI.

Why I’m Doing This

A few months ago, I was interviewed by a research team connected to the World Economic Forum. They’re studying the future of work and education in the digital age—specifically how people learn and adapt in environments that are changing faster than ever.

That interview got me thinking: Manufacturing is changing. Digital tools are changing. But our learning models haven’t caught up.

And if I’m being honest, my own communication style tends to be direct, dense, and sometimes… too straight to the point. Great for experts, not always great for everyone else.

So I wanted to see what happens when I let AI help me explain the concepts I care about—but in a completely different voice. So I leveraged the generative AI tools (specifically I used NotebookLM from Google for no other reason than availability - its free for now) and I’ll admit: I expected the usual AI fluff but the results was… surprisingly good.

With some well thought out prompting and iteration NotebookLM didn’t just rewrite my explanations—it transformed them into something more approachable, more story-driven, and dare I say it, more human. It brought out a teaching style that’s very different from my natural tone.

Transforming the Content

The first video was really just a "let me just feed some content and see what I get...". I recently wrote a whitepaper titled "Digital-First and Composable— A NewParadigm for ConceptualFacility Design in Pharmaceutical Manufacturing" about why its critical to take a digital first approach to the design of pharmacuetical manufacturing facilities. (Its not published publicly yet, but let me know if you are interested in a copy)

I wanted to test whether NotebookLM could help explain this somewhat deeper and more technical topic in a different way to non technical people. Basically as if you are explaining this to your grandmother. This is a known exercise that is commonly used to create a simplified and easier to understand content of technical topics. It was something I typically asked my students to do when defining their research topic, e.g. the The Feynman Technique. 

Here AI surprised me again. It took my content and created a narrative that felt clear, structured, less consultanty and was like a guided tour of the future of manufacturing It delivered the same intellectual payload—but in a format that's easier to digest for people who aren’t neck-deep in these topics every day.

For the second video I fed it the transcript from my WEF conversation about how people learn, and the AI picked up on a few of the stories that I used to exemplify how to explain new digital concepts to the industry. It took the my grandpa story  and created a story about a grandpa discovering AI for the first time. It turned a complex topic into something relatable and a little emotional. 

I shared both the whitepaper and the video I created with customers and colleagues and the feedback was that the video is by far more valuable than the whitepaper. The surprising part was that people actually learned from it. They weren’t just “getting the point.”, they were experiencing it - maybe even feeling the point. 

Why Use Personas?

One thing that became clear through this experiment is that who explains something matters just as much as what is being explained.

In manufacturing, we’re all guilty of communicating like… well, manufacturing people. Precise. Direct. Dense. Focused on efficiency. It’s great for experts, but not always for learners who don’t live and breathe MES architectures or Pharma 4.0.

This is where personas come in. Sometimes the most effective way to teach a technical idea is to have it explained by someone who is not you.

• A grandpa.
• A mentor.
• A line worker.
• A curious newcomer.
• A future digital assistant.

AI helped generate voices and storytelling styles that I simply wouldn’t have used myself. And that difference matters. It’s disarming. It opens people up. It creates emotional connection. It makes the content stick.

But—and this is important—it didn’t invent anything on its own. It worked because I gave it:

• the right context
• the right source material
• the right stories
• and a clear intention
• grounded in my decades of experience

AI can’t fabricate expertise but it can translate expertise into a form that reaches people where they are. The personas made the learning accessible and my context made it accurate. It’s a powerful combination.

What I Learned

In the end, this experiment taught me that AI can significantly expand my creative range—but only when it’s grounded in the right context. AI didn’t magically produce valuable content; it was effective because it worked with my whitepaper, my WEF interview, my research, and my own stories from years in manufacturing. When AI has that depth to draw from, it becomes an amplifier rather than a generator of fluff. 

I also realized how essential storytelling is for real learning. The emotional layer—whether it was explaining a digital-first facility as if to a grandmother or turning my grandpa anecdote into a touching narrative—made the concepts stick in a way traditional technical writing rarely does. And using personas was far more powerful than expected: having someone unlike me tell the story didn’t dilute the expertise; it made it more approachable and meaningful. What this ultimately reinforced is that AI isn’t the expert—it’s the assistant. It can translate, reframe, and humanize ideas, but only when guided by intention and supported by real experience. And that, I think, is exactly how AI will create value: by helping us communicate better, teach more effectively, and unlock new ways to share the knowledge we’ve spent years building.

The Power of Teams

I have always inherently felt that there is immense power in teamwork with well-defined team roles. Done well, ie well functioning roles within teams, enhances collaboration and increases productivity. We have to recognize that complex projects and innovative solutions often require the collective effort of diverse skill sets and perspectives. However, the effectiveness of a team is not merely a function of bringing people together; it hinges on how well the team is organized and how clearly the roles within the team are defined. Well-defined roles enhance collaboration and increase productivity by providing clarity, fostering accountability, leveraging individual strengths, and streamlining communication.

I know this topic is a bit of departure from my normal themes around digital transformation and intelligence in manufacturing. I see many companies struggle with how to organize their digital initiatives and sometimes the essence of a good team that can help move the needle get's lost between all the technology and change management topics. 

What Constitutes a Well-Defined Team

A well-defined team is one where each member has a clear, specific role that complements the roles of others. These roles are carefully crafted based on the individual strengths, skills, and expertise of team members. In an engineering team, differentiating roles is crucial because it ensures that all necessary functions and tasks are covered without redundancy. For example, the team might include a project manager to oversee timelines and resources, a technical lead to guide the technical direction and resolve complex issues, and engineers to handle specific aspects of the design and implementation process. Each role is distinct yet interconnected, allowing the team to work efficiently and cohesively. The differentiation of roles prevents confusion and overlap, ensuring that each team member can focus on their specialized tasks and contribute uniquely to the team’s objectives.

Clarity and Direction

One of the foremost advantages of well-defined roles in an engineering team is the clarity it brings to the group. When each member understands their specific responsibilities, the overall direction of the project becomes clearer. The project manager ensures that timelines and resources are managed effectively, the technical lead provides technical guidance and oversight, and the engineers focus on their specific tasks, such as technical build, demoing, configurations, testing, and system integration. This clarity prevents overlap and redundancy in tasks, ensuring that team members are not duplicating efforts or working at cross-purposes. With clear roles, everyone knows what is expected of them, which reduces confusion and allows the team to focus on their collective goal. This focus enhances the team's ability to meet deadlines and maintain high standards of work.

Accountability and Ownership

Clearly defined roles foster a sense of accountability and ownership among team members. When individuals know their specific responsibilities, they are more likely to take ownership of their tasks. The project manager is accountable for project deliverables and timelines, the technical lead is responsible for the technical integrity of the project, and engineers are accountable for their respective contributions. This ownership translates into higher levels of commitment and motivation, as team members feel personally responsible for their contributions. Moreover, well-defined roles make it easier to track progress and identify any issues that arise. Accountability mechanisms can be put in place, ensuring that each member delivers on their commitments. This accountability not only boosts individual performance but also enhances the overall productivity of the team.

Leveraging Individual Strengths

Every team member brings unique skills, experiences, and perspectives to the table. Well-defined roles allow engineering teams to leverage these individual strengths effectively. By assigning roles based on each member’s expertise and strengths, teams can optimize their performance. For instance, the project manager might excel in coordination and resource management, the technical lead might have deep technical knowledge and problem-solving skills, and engineers might have specific technical expertise in areas like integration, production control, data analysis, or quality assurance. This alignment of roles with individual strengths ensures that tasks are performed efficiently and to a high standard. When team members are engaged in work that plays to their strengths, they are more likely to be productive and satisfied with their work.

Streamlining Communication

Effective communication is the backbone of successful teamwork. Well-defined roles help streamline communication within an engineering team by establishing clear lines of responsibility and reporting. Team members know who to approach for specific issues or information: engineers can turn to the technical lead for technical guidance, and the project manager can address scheduling and resource allocation concerns. This streamlined communication is particularly important in large teams or complex projects where numerous tasks and sub-tasks must be coordinated. With clear roles, communication becomes more targeted and efficient, facilitating quicker decision-making and problem-solving.

Enhancing Collaboration

Collaboration is the lifeblood of any high-performing team. Well-defined roles create a structured environment where collaboration can flourish. When team members understand their roles and the roles of their colleagues, they can better appreciate how each contribution fits into the larger picture. This understanding fosters a cooperative spirit, as individuals are more likely to support one another and work together towards a common goal.

In a collaborative environment, team members are encouraged to share ideas, provide feedback, and build on each other's strengths. This dynamic exchange of ideas leads to more creative solutions and innovative approaches to problems. When roles are clear, team members can engage in more meaningful collaboration without the fear of stepping on each other's toes. They can confidently contribute their unique perspectives, knowing that their input is valuable and will be integrated into the team's efforts.

Moreover, collaboration enhances performance by creating a sense of shared responsibility. When team members collaborate effectively, they develop a collective ownership of the project. This collective ownership motivates everyone to put in their best effort, as the success of the project is seen as a shared achievement. As a result, the team becomes more cohesive and resilient, capable of overcoming challenges and achieving higher levels of performance.

The Power of Network Dynamics and Teams of Teams

The last perspective I wanted to bring comes when organizing multiple teams with well-defined roles into a larger, interconnected network can amplify these advantages. This concept is explored in depth in the book "Teams of Teams" by General Stanley McChrystal. McChrystal argues that in complex environments, traditional hierarchical structures are often insufficient. Instead, he advocates for a networked approach, where teams operate with a high degree of autonomy but are also closely connected and aligned with other teams through shared goals and transparent communication.

In an engineering context, this means that multiple teams – each with clear roles for project managers, technical leads, and engineers – can collaborate more effectively across organizational boundaries. For instance, a software development team can work in tandem with a quality assurance team and a user experience design team, with each team bringing its specialized expertise to the table. This networked approach enables rapid problem-solving and innovation, as information flows freely and decisions can be made quickly.

By embracing the dynamics of a "teams of teams" structure, organizations can respond more agilely to changes and challenges. The interconnectedness fosters a culture of continuous learning and adaptation, where best practices are shared, and collective intelligence is leveraged. This approach not only enhances the performance of individual teams but also drives the overall success of the organization, leading to groundbreaking innovations and sustained competitive advantage.

Bringing this All Together 

Working in teams with well-defined roles is essential for enhancing collaboration and increasing productivity especially with the increased complexity that comes with digital transformation. The clarity provided by distinct roles helps align the team towards common goals, while accountability mechanisms ensure that tasks are completed efficiently. Leveraging individual strengths maximizes the team’s potential, and streamlined communication fosters quick and effective problem-solving. Ultimately, well-defined roles create a collaborative environment where team members feel respected and valued, leading to higher levels of productivity and success. This collaboration not only drives individual performance but also elevates the entire team's performance, leading to innovative solutions and outstanding results. In a world where teamwork is increasingly important, the organization of these teams is paramount to achieving exceptional outcomes. By embracing the power of network dynamics and the "teams of teams" approach, organizations can further enhance their agility and effectiveness, paving the way for sustained success in an ever-evolving landscape.