In-Ear Insights How to Help Marketers Adopt Agile and Prompt Engineering

In-Ear Insights: How to Help Marketers Adopt Agile and Prompt Engineering

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris explore the human side of how to adopt Agile and prompt engineering. Learn how to build trust within your team and address anxieties surrounding AI and automation. Discover strategies for fostering open communication and encouraging ownership among team members, even those hesitant about adopting new technologies. Finally, understand how aligning individual purposes with company goals is crucial for successful implementation of Agile and AI initiatives.

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Machine-Generated Transcript

What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.

Christopher Penn 0:00

In this week’s In-Ear Insights, we’re on part four of our series on agile and AI.

This week, we’re going to put a bow on everything by talking about the one part that we really haven’t talked about so far.

In the five Ps of agile and AI, we’ve talked about what Agile is, we’ve talked about prompt engineering and shown some examples, and we’ve talked about applying Agile to prompt engineering.

What we haven’t talked about is the people.

Katie, how do we create and empower people with both agile and prompt engineering? For a lot of companies, this stuff is still so new, and it feels like implementing both agile and prompt engineering at the same time could be overwhelming.

What’s the pathway to getting an organization or team up to speed on both without causing them to cower under their desks in fear?

Katie Robbert 1:03

Even asking the question is overwhelming because it is a lot.

It’s a culture shift.

Introducing a new technology that you want to infiltrate into everything is a culture shift; introducing a new methodology for getting things done is a culture shift.

And so we absolutely should be talking about the people.

I always start at the top: What is the purpose? Why are we doing this? Anytime I’ve been faced with some kind of change management, I always know that the hardest part of the project is going to be getting people on board.

The reason for that is because people naturally want to know why.

“Why are you asking me to do this? What is in it for me? How does this impact me? What does this mean for my job? Do I have a sense of ownership in this? Can I have an opinion in this?” These are all normal, natural questions.

Companies that are prepared to have those conversations are more likely to be successful with their implementation, versus companies that say, “We’re going to do this thing,” and that’s it, that’s all the information you get.

Chris, we’ve both been in both scenarios.

So, how have you felt as a person, as a human, as a team member, when someone comes to you and says, “We’re going to do this thing”?

Christopher Penn 2:35

It depends on who’s asking and what the situation is.

If it’s a stakeholder that I like working for, I’m like, “Okay, cool, we’ll figure it out,” it’s a fun challenge to solve.

If it’s a stakeholder I don’t like, it’s like, “Oh, great, more pain.”

Katie Robbert 2:47

I think that’s fair.

Christopher Penn 2:50

I mean, it’s, again, it’s all about the people, right? And so it’s not even just what’s being asked, because presumably, as long as you’re working for rational, sane stakeholders, there is some clear purpose that is either implicit or explicitly declared, like, “Yeah, we’re doing this because we need to be more efficient, we need to make some more money, we need to do this.” If you’re working for an irrational stakeholder, well, you know, all bets are off.

Katie Robbert 3:18

What’s interesting is what you’re talking about is trust.

This is, again, where a lot of companies get these types of big change management projects wrong: they are overestimating the amount of trust they have built within their teams, within the company culture.

I would like to believe, Chris, if I said to you, “Hey, Chris, today, we are going to start manufacturing pancakes,” you’d probably be like, “That’s interesting.

All right, let’s figure it out.

Where at?” And because I feel like you and I have built up that trust, where if I’m asking something, there’s probably a good reason.

And you know, you feel comfortable asking me what the reason for this is.

Whereas in previous roles, if your previous supervisor came to you and said, “Hey, Chris, today we’re going to build pancakes,” you may not have felt comfortable saying, “Why? What does this mean?” You probably would have dug in your heels and been like, “Well, eff that, I’m not gonna do that.

That’s dumb.

I don’t even know why they’re asking me to do this, they can’t give me any context.” And that is where that relationship is so important.

Especially in enterprise-sized companies where there’s a good chance you’ve not even laid eyes on 70% of the workforce, right, you’ve only maybe ever seen their name mentioned in an email, it’s really hard to build that trust when someone is asking you to do something.

You’re like, “Who is this person? Why am I supposed to do something for them? What’s in it for me?” Those are really normal questions to ask.

That’s why when you start to think through introducing agile, or introducing generative AI, or introducing both, you really need to understand how every single person involved is going to feel about it.

A lot of companies, they don’t want to care about that.

They’re like, “No, it’s what’s best for the company, let me do the thing.” But at the end of the day, it’s still people who are executing against the plan.

So one way—because I know you’re gonna ask me, “Well, what do we do about that? How do we fix that? What does that mean?”—so first and foremost, you should probably hold what a lot of companies call a town hall and allow people to bring their questions, or submit questions ahead of time, or whatever the process is, you want to do that.

But a more efficient way to do that is to gather user stories.

What you would do is you would say, “Hey, Chris, I think that our company is going to start being more agile.

Okay, here’s why we want to do it.

Here’s what I’m thinking.

I want to know, from your perspective, what that looks like.

And here’s a user story exercise: ‘As the chief data scientist, I want to use agile so that I can code more efficiently.

I want to borrow from Agile methodology so that there’s more transparency.’ I want to start to hear from you, from your perspective, what that means and what questions you have.

You know, and if you don’t know what you want from agile, that’s okay, but let’s have a conversation about it.” By going through this exercise, it does a couple of things.

One is, you start to understand, beyond just your perspective of what you need, what other people are going to need, because their needs from agile or generative AI may be different from what you need from agile or generative AI.

So that’s an important thing to know.

The other thing is, it starts to give the people who are actually going to be executing a sense of ownership.

They’ve been heard, they’ve been listened to, you are taking their opinions into consideration.

I used to have a stakeholder who wanted all kinds of crazy things when we were talking about software development.

He did not understand software development, but he had very strong opinions about what he wanted.

And I would always come to—he would, you know, he would bring this thing to me, and I’d be like, “Well, we can’t do that.” And one day, he got in my face, and said, “You need to stop saying no so fast, you need to hear me out, listen to me.” And what it told me was that he just wanted to be heard, whether or not his thing was ever going to make it into production was really kind of irrelevant.

He just wanted to know that he could at least voice his opinions in a way that weren’t immediately going to be shut down.

And that helped us start to rebuild that trust that was so desperately needed for us to keep moving things forward.

And so that’s a big part of this: the more people you have involved, obviously, the more complicated it’s going to be.

But even if it’s just between two people, even if it’s just between myself and Chris, we have to build that trust, he has to understand why I’m asking something, and he has to understand and feel like he can voice where he’s going to hit roadblocks or he has opinions or he wants to do something a different way.

Those conversations have to happen.

You can’t skip over them.

Christopher Penn 8:28

I think it’s a really interesting point too because generative AI in particular can, if improperly rolled out, cause a lot of anxiety and fear and concern, like, “Is this machine going to take my job?” And that is a valid concern because there are cases where yes, that will be the case.

By anticipating the likely objections, the likely questions people are going to have, you stand a chance of getting ahead of that, of saying, “Okay, here’s how we’re going to be using this thing.

Hey, you know, those expense reports you love writing every month? We’re going to teach generative AI how to do that.” And almost everyone that comes to me is like, “Yes, that’s a great use case, I hate doing that, it’s not a good use of my time.

And if I can just talk to a machine for five minutes and have it do the report, I’m on board, like, you give me as much generative AI as you can send me if it means not having to fill out that bloody form every month.” And I think part of that rollout and empowering people with it is saying, “Here are the use cases where this is going to make your life better.”

Katie Robbert 9:38

It’s an interesting example.

However, the part of the conversation that was missed is, okay, we’re gonna use generative AI to write your expense reports.

And maybe 90% of the people are excited about it, but that one person whose sole function is to collect and process expense reports is now probably pooping their pants, saying, “I don’t know if I’m going to have a job tomorrow.” That is probably the person who is most important for you to talk to.

Because they need to understand, okay, if you’re taking away a core function, what does that mean for me as a person? What am I going to do instead? And then, you know, it’s an opportunity to have the conversation of, “Here is higher value work that you could be doing, but right now, you’re so in the weeds with expense reports that you can’t get to that stuff.” Or, you know, “Hey, you know what? You processing expense reports is just not a job function that we’re going to need anymore, so let’s have a conversation about how we can either rewrite your role or, unfortunately, in some situations, it’s just no longer a function that we need, so I’m giving you a heads up so that you can start to make those plans.” There’s a lot of different outcomes for those kinds of conversations.

But the human side of this is having those conversations because people have a lot of high anxiety.

When people have high anxiety that is not being addressed, they start to create real and fake scenarios, and they start to make assumptions, and they start to concoct situations that may or may not happen, and they start to spiral.

When that starts to happen inside of an organization, the culture as a whole becomes very toxic, whether or not it was intended or just sort of accidental that you didn’t have these conversations.

When you start to have that toxicity in your culture, it is very hard to remove, because now you’re trying to address situations that are never going to exist, but people have started to think about them, and now they’re starting to worry about them, and it’s keeping them up at night.

And you may have that side effect of, “Well, I don’t want to be a part of that, so let me just go ahead and proactively leave the job.” Or, “Let me tell everybody else that they need to be leaving,” and you have these undesirable outcomes that you did not plan on having because you didn’t have those conversations upfront.

Christopher Penn 12:12

With a technology like generative AI, though, how do you even know that that’s a possible outcome? Because in a lot of cases, it comes into something like, “Hey, write more blog posts,” with no agenda, right? And then, as people start using it, they go, “Oh, I can use it for this, and I can use it for this,” and it—it gets scope creep of its own, but because of the nature of the tool, it can handle that.

And it has applications across the entire lifecycle of a business.

How do you manage that? How do you message that to people? How do you get people’s buy-in for a tool that when they read the headlines, it’s like, “Yeah, this is gonna take 95% of all jobs, you know, that’s,” the crazy thing is that people, some of the tech bros like to say,

Katie Robbert 12:55

It’s a lot like requirements gathering, a lot like development and testing—it’s very rarely a one and done.

If you’re having these conversations, it’s not a, “Well, we had this conversation three quarters ago, so why are we revisiting it?” Because the technology is changing, because the expectations are changing, you have to continue to have the conversation, and maybe you build it into part of the requirements gathering process, part of the prompt engineering lifecycle.

Maybe part of the lifecycle that’s really important to your company for success is having that conversation, or setting aside time for R&D—research and development—giving people the opportunity to explore it on their own and bring back what they’ve learned, their ideas, to say, “This is how I think it might benefit my job.

I know that our business outcomes, our revenue, customers, retention, whatever the thing is, I took a look on my own, I did the R&D on my own and found maybe I could do this, and this could help.” Again, it gives people that sense of ownership, versus being told what to do without any context as to why.

And you may find—because, you know, Chris, you’re just one person.

Believe it or not, you’re just one person.

And even though your expertise in generative AI is expansive, you may never come up with the same ideas that I will, because I’m a different person, I have different experiences, and I’m going to look at it from a different perspective.

And you need those different perspectives to really understand what generative AI can do.

But you also need to create the space where people are allowed to share what they’ve learned or have questions in order for it to become a really strong part of your culture.

Christopher Penn 14:45

So how do you get people to do that, though? How do you get people to recognize the opportunity that’s in front of them and to proactively take that ownership? Because a lot of people—for good or ill—a lot of people are not that proactive, they just kind of wait for things to happen.

And to your point, that can create a very toxic culture, but at the same time, a very small minority of people are going to be like, “Yeah, I’m going to get ahead of this and do that thing.” A lot of people are like, “I’m just trying to get my to-do list done today, I don’t have the bandwidth, the maybe even the motivation, like, yeah, I work at this company because it’s a paycheck, and that’s all I care about, and I’m not going out of my way to do extra work for them when it’s not going to get me any more money.” How do you tackle that because this is the thorniest part of AI—the people?

Katie Robbert 15:41

It’s the same thing, you know, if you take generative AI out of the conversation, replace it with any tech, because that’s all it is, it’s really just a piece of technology, it’s just a piece of software.

Let’s say we’re talking about your CMMS, let’s say you’re talking about your payroll system, let’s say you were talking about the system in which you input your expense reports, to go back to that example.

People are going to do it, or people are not going to do it.

That’s the reality, you’re absolutely right, you’re never gonna get every single person on board to do it, not everyone has that same desire to do it.

And that’s okay.

This is going to sound really callous, but then those opportunities are taken away from them because you have to decide, as the decision maker, as the person in charge of change management, as the person responsible for building an AI-driven culture, an agile culture, “Do I have the right people in the right seats to do this? Or do I have people who can do things outside of that?” And you may have room for both, you may not, those are business decisions, but it still comes from having those conversations.

You know, Chris, you have been all in on generative AI since day one.

I, on the other hand, have not been.

I’ve been more resistant, I’ve probably been more stubborn than I need to be, or it’s just not something that is as interesting to me as it is to you.

And so that is that sort of friction that you and I need to continually navigate, continually talk through.

I need to feel like I can voice my concerns about using generative AI, and you need to feel like you can voice your concerns about me not using generative AI.

And the goal is that we come to some sort of agreement of what we will and won’t do, but we’re continually, almost every day, having that conversation.

And it’s not that we’re sitting down, dedicating time, like, “Okay, today we’re going to talk about this,” it’s that it’s just part of our natural workflow, that we have that open and honest communication about the thing, we’re both learning from each other, our perspectives on this particular piece of tech.

That’s really going to be the key to success.

And so in this scenario, where perhaps I say, “You know what, Chris, I’m never, never ever—I’m not interested, I’m not proactive, I don’t want to use generative AI,” we then have to figure out what that means for the company.

Am I harming the company? Am I holding us back from moving forward? And if that’s the case, perhaps I am not the right person to be in this role to lead a company when I’m actively, willfully holding it back.

Let’s say the CEO—just to pick a different tech—let’s say SEO is really vital to the company, but we have people on our team who are maybe forgetting to do it, maybe subconsciously not doing it because they don’t think it’s important, we need to figure out what that means for the company.

Are they harming the company? Are they holding the company back? And what do we do about it to solve that problem? Maybe that person is not the right person to be addressing that particular piece of tech; there’s other things they could be doing.

So it’s—what’s interesting is this is not a new problem, it’s just new tech.

But we’re putting so many big expectations on generative AI, solving problems, but it’s not a new problem.

Christopher Penn 19:17

I liked the SEO example because in a way, it highlights how the five Ps are good as a diagnostic tool.

If you have—if theoretically, the person is the problem, then you have to ask: “Have we not documented the process? Is the technology too hard to use? Is SEO not part of their performance outcomes?” Right? You get what you pay for.

So if someone’s—if it’s not part of “This is how you’ll be evaluated as to whether you’re doing a good job or not, and will be held accountable for it,” then it’s probably not going to get done.

But the one that stands out to me is purpose.

If, in your example of adopting generative AI or not, if it’s something that is going to start harming the overall outcomes of the company, the overall purpose of the company, which is to grow, to provide work for its employees, to make, you know, to serve customers well, then that opposition means that your purpose is different than the company’s purpose.

If you’re saying, “I don’t want to use this thing,” and the thing, whatever it is—SEO, generative AI, CRM—is aligned to accomplishing the purpose, then I think that’s probably where you have the biggest challenge, because you no longer have purposes that are aligned.

You and I may disagree about specific implementations of generative AI, but we have the exact same purpose: we want to see our company do well, we want to see our employees do well, we want to see our customers do well, we want to continue to do all the things that we started from day one.

The technology, the platform, and some of the processes around it may be different, but our purpose is the same.

But when you have employees whose purpose is out of sync, then I think you’ve got a much bigger challenge to solve.

Katie Robbert 21:08

Well, and that’s where having that user story exercise is really helpful because you start to understand what their purpose is, what their perspective is.

If their perspective is, “I want to use generative AI to write all of my blog posts so I don’t have to do it,” that doesn’t really align with the company goals, like, “It might be great generative AI is going to do it because you don’t want to do it,” but you don’t want to do it because you don’t want to, you know, help us bring in more customers, help us bring in more revenue.

And so it’s a conversational tool, it’s an opportunity to start to dig into why there is so much friction.

People are tricky.

You’re absolutely right, the hardest part of all of this is people, because you have people who are all in, their team players, you have people who are independent contributors, they just, you know, they don’t want to work with other people for a variety of reasons.

You have people who have their own agenda, you have people who have their own reasons for doing things or not for doing things, you have different levels of comfort, you have different background experiences, you have different reasons for even showing up for work every day.

To your point, maybe it’s just a paycheck, and they don’t really care, they’re just going to do the bare minimum so that they can collect the paycheck, they don’t care about advancement, they don’t care about being the best, they literally just need to keep the lights on at home.

And then you have people who are over-ambitious, “Give me everything, let me do the thing.” That’s the hardest part, is navigating, figuring out where all of those different people fit into this new organizational structure, into this new culture of agile and generative AI.

There may be jobs, there may be people that don’t need to use generative AI.

Does that mean that you are no longer a generative AI culture? Not at all, it means that you have found the right places to do this thing.

Again, think about it in terms of your CMS, your marketing automation.

Your accounting team may not need to ever touch your marketing automation system, probably shouldn’t.

Does that mean that you shouldn’t use it? Absolutely not, it just means that you are matching the roles and the purpose to the right people and the right outcomes.

Christopher Penn 23:30


To sum up, the technology itself isn’t as important as making sure that the people are aligned with the purpose and that any technology or any methodology is clear to the people—how it aligns to the purpose.

If there isn’t a clear line of sight to the purposes of a company, of a team, of a manager, of your job, then yeah, it’s going to be a very difficult task to get agile or generative AI or anything implemented.

Because ultimately people will see that it is not aligned with maybe their purpose and certainly not aligned with what the company is trying to do.

And so it will probably be an expensive waste of time.

Katie Robbert 24:21

When I was a product owner, I remember I would every week sit in, you know, product owner meetings, there were three of us, and then the CEO would come down and meet with us and sort of tell us everything that was going on.

And every time she walked into the room, she would make eye contact with me and just say, “Don’t you dare,” because she knew the first question I was going to ask is, “Do we have business goals yet? What are we doing? Why am I doing this? What am I working towards?” And so I struggled in my role because I didn’t know what direction I was going in.

And I did what was being asked, but I questioned it every step of the way, which made—way so—people, they didn’t like that I was asking so many questions, but nobody could tell me why I was doing this.

They were like, “You know, we need you to write a business plan.” “Why? For what? For who? To do what to?” And it was just, “Just write one.” And it was like, “Okay, we need you to, you know, build this thing.” “Okay, for what purpose? Who’s going to use it? What do they need?” And so it just—you need to give your team, your company, your culture, that “why?” Because they’re going to ask, they’re going to want to know.

And if you can’t answer why we need to be an AI-forward shop, or why we need to be agile, they’re going to dig their heels in, and they may not realize they’re being stubborn, but in their quest to get answers, to figure out what that means for them, they are stopping the process from moving forward because they need that information.

So at the very least, when you’re putting together your purpose statement, make sure you have your “why”: “I want to make our company agile so that I can do X.” Don’t just stop at “I want to make our company agile.” That’s where a lot of companies get it wrong, as they start to put together the user story and they chop it off before they get to the “so that.” That purpose and that performance, that outcome, is so vital to getting people on board.

Christopher Penn 26:25


And if you’d like help doing this, this is something that we do.

Go to, and we can help your company figure out how it’s going to implement generative AI, whether you should or not, and how well it is aligned to your purposes.

If you want to share some of your experiences with both agile and generative AI and its implementation with your company, with your people, pop on over to our free Slack group, go to, where you have over 3000 other marketers asking and answering each other’s questions every single day.

And wherever it is you watch or listen to the show, if there’s a channel you’d rather have it on instead, go to, where you can find us on most channels.

And while you’re on your channel of choice, please leave us a rating and a review.

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Thanks for tuning in.

I will talk to you next time.

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Trust Insights ( is one of the world's leading management consulting firms in artificial intelligence/AI, especially in the use of generative AI and AI in marketing. Trust Insights provides custom AI consultation, training, education, implementation, and deployment of classical regression AI, classification AI, and generative AI, especially large language models such as ChatGPT's GPT-4-omni, Google Gemini, and Anthropic Claude. Trust Insights provides analytics consulting, data science consulting, and AI consulting.

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