Growth Activated · 2026-08-18 · 28 min
Key moments - from our scoring
Substance score
39 / 100
Five dimensions, 20 points each
Mandy Hornaday, a fractional CMO and marketing leader, walks through her process of building a Momentum Maker AI partner to solve a pervasive problem: work stalling due to unclear ownership, approval chains, and scope boundaries. Even with existing RACI charts and documentation, her 15-person team kept hitting friction points - overlapping skill sets created confusion about who should do what (e.g., event emails vs. paid social copy), and constant low-level decisions pulled her into a referee role. She spent 20 - 25 hours using voice notes, Whispr Flow, and iterative prompting to load the AI with job descriptions, decision-making frameworks, commercial rights, business strategy, and team capacity insights. The resulting Gem became a real-time decision engine that reduced decision fatigue, unblocked work, and - critically - improved clarity between overlapping roles like sales enablement and marketing sales enablement. She emphasizes that this approach works at any team size: solo fractional CMOs can use it to map external partners and advisors, small teams can document internal networks, and large teams can scale clarity across complex stakeholders. Implementation matters; she launched live demos, iterated daily the first week based on team feedback, and adjusted prompts so the AI could serve team members with varying skills.
Start restrictive (only confirmed documentation, flag unknowns to a fallback person), then iterate after live team use. Mandy found this approach too limiting and loosened it to let AI use logic and reasoning based on documented frameworks, then adjusted the prompt and documentation based on team feedback screenshots of incorrect answers.
Job descriptions, RACI charts, decision-making and approval rights, scope of work and commercial boundaries, business strategy and priority segments, team capacity insights, and clarity on overlapping roles. This emerged snowball-style from real problems; start narrow and expand as friction points surface.
Mandy held a live demo where team members threw out real questions they'd had, then encouraged skeptics to ask the AI to list five scenarios where they'd need it or five reasons it would help their role. This helped people understand their own boundary confusion.
First iteration: AI could only share explicitly documented information and default to the senior PM for anything unclear. Second iteration: AI was allowed to use logic and reasoning to infer answers (e.g., inferring copy responsibilities based on team member skills), which required more iteration but delivered more value.
Mandy saw immediate answers to daily questions (within minutes), freed up roughly 10 hours per week within the first two weeks, and the tool was 85% accurate at launch, reaching 95% after one week of daily updates.
Our reviewer’s read on each dimension, with quotes from the episode.
The episode contains a handful of genuinely practical ideas - using AI as a capacity-planning sparring partner, the two-iteration approach to prompt constraint vs. inference, and the 'AI as referee' framing - but large stretches are padded with obvious advice about documentation, change management platitudes, and repetitive encouragement to 'start somewhere.' The ratio of novel-to-filler is modest.
I actually used AI as my sparring partner to help me understand where would work fail. So based on our operating models and our systems and the roles that we had, where was work destined to fail?
it actually dove into things like capacity planning, and it told me which team members were going to be stretched and ultimately turn into bottlenecks
The 'AI as organizational referee for role conflicts' framing is a genuinely fresh angle, and the honest account of two prompt iterations (over-constrained vs. too permissive) adds some non-obvious nuance; however, the overall thesis - document your processes and feed them to an AI tool - is well-worn, and phrases like 'to be clear is to be kind' are borrowed aphorisms rather than original thinking.
AI makes a pretty great referee
I didn't want it to hallucinate whatsoever...and so what that looked like was, in the first version of the AI partner, I essentially said, you can only share information that is clearly documented
This is a solo episode by the host herself, a fractional CMO; there is no external guest. She is a legitimate practitioner with a real case study at a named scale (~$500M client, 15-person team), but the absence of any outside perspective, and the self-promotional references to her own course and cohort, limit the authority signal substantially.
the Momentum Maker AI partner that I built for one of my clients is actually for one of the largest teams I run. It's roughly a $500 million company, and the marketing team there is roughly 15 people
if you listened to last week's episode on this $9,000 AI course that I took
There are concrete data points - 20-25 hours of build time, 5-10 hours/week recovered, an 85%-to-95% accuracy improvement after the first week of rollout - and specific tooling is named (Gemini Gems, Wispr Flow, Claude). However, the numbers are all approximations ('anywhere from'), no business outcomes are measured, and the examples (ad copy ownership, sales enablement overlap) are illustrative anecdotes rather than rigorous evidence.
I probably spent anywhere from 20 to 25 hours, and I went deep on this
I easily got anywhere from five to 10 hours a week back, just on this one client
This is an uninterrupted monologue; there is no interviewer, no guest, no follow-up questions, and no productive disagreement possible by design. The host does occasionally steelman objections ('if you don't run a large team, you might be tempted to tune out') but these are rhetorical rather than genuine challenges, and the episode ends with an extended promotional pitch.
Now, I realize as I talk about this, this may feel overwhelming.
And if you're fractional, or your team is small, or you don't have a team at all, stay with me.
Computed from the transcript - who did the talking, and the words that came up most.
#52 - I spent about 20 hours building an AI partner for one of my marketing teams, and it gave me back five to 10 hours a week and got my team moving work forward without waiting on me. The team is roughly 15 people at a $500 million company, and work kept stalling on everyday questions. Who owns this. Who has to approve it. Is this even ours to do. We had RACI charts. We had SOPs. We had process flows. None of it stopped the questions, and I was the one answering them. So I went under the hood and built what I call a Momentum Maker AI partner. In this episode I walk through the whole thing.
Transcribed and scored by The B2B Podcast Index.
Mandy Hornaday: Welcome to Growth Activated. I'm Mandy Hornaday, your host with 15 years of experience leading marketing teams ranging from small startups to large service organizations. I've built high performing teams of all sizes and have seen firsthand how fast the landscape is evolving, making marketing leadership more complex than ever. Today, I help marketing leaders elevate their strategies, lead with confidence, and build careers they love.
If you're ready to drive impact and unlock growth for yourself and your company, you're in the right place. Let's get started. Mandy Hornaday: One of my senior leaders told me she feels like she has 24/7 access to my brain now. What she really has is a documented map of how work moves through our team, and it took me about 20 hours to build.
Mandy Hornaday: And I built it because work kept stalling. Not because anyone on the team was slow, and not because we didn't have process. We had RACI charts. We had process flows.
But work still stalled on everyday questions. Who owns this? Who has to approve this? Is this even ours to do?
Each one was a pause in the work, and the pauses added up. Mandy Hornaday: So if your work is getting stuck somewhere on your team, or between your team and sales, or on your desk waiting for you to weigh in, this one's for you. Mandy Hornaday: Today I'm going solo to take you under the hood of the AI partner I built for my team. What it does, how I approached it, what I'd do differently, and the thing I didn't see coming, which is that AI makes a pretty great referee.
And if you're fractional, or your team is small, or you don't have a team at all, stay with me. This isn't a big team problem, and I'll get specific about the other ways this helps in the first few minutes. Let's get into it. Mandy Hornaday: So just to set the scene here, the Momentum Maker AI partner that I built for one of my clients is actually for one of the largest teams I run.
It's roughly a $500 million company, and the marketing team there is roughly 15 people. And that's through a combination of both in-house individuals as well as outsourced contractors through the agency. Mandy Hornaday: So needless to say, there are a lot of different stakeholders, both inside the client and through the agency that I'm working with on this project. Lots of moving parts, and work that touches almost every department in the company.
Mandy Hornaday: And because this is such a large client and a large team, there were several different areas where the marketing team on the day-to-day was getting caught up. One example was that this was a pretty large scope, and we are embedded as their full marketing team and partner. And so often the lines are blurry about what is considered in scope as a part of our commercial rights and what is technically out of scope. And even if you're running a full-time team, you might also have these same questions of what's on our roadmap that we're committed to doing, and what is outside of that roadmap that shouldn't really be a priority right now.
Mandy Hornaday: Another problem that we had was that because we had such a large marketing team, a lot of those team members have overlapping skill sets, which is really great for coverage when someone is out on vacation or they're at capacity and they need help. But it also led to a lot of confusion on who should do what. Mandy Hornaday: So for example, if our events team has a demand generation background, should they be writing all of the event promotion emails, or should that come from our email team?
Or if we have a lot of different paid social ads, should the ad copy be written by our paid social team? Should it be written by our organic social team? Should it be written by our content writer who handles a lot of different content across the entire team? A lot of these different day-to-day decisions seem small, but the more and more that we were operating in the gray, the more it was causing confusion and stop gaps for the team.
Mandy Hornaday: And last but not least, one of the things that we really struggled with was final approvals. There were a lot of questions around who needed to approve which work. What could go live or into production without approvals at all? What needed some peer review approvals?
Or what ultimately needed my approval or the C-suite's approval? Mandy Hornaday: There was just this constant flow of questions in and out on the day-to-day, as we had multiple projects, multiple initiatives, multiple programs running all at once. And I was ultimately pulled in a lot to essentially referee the day-to-day and make decisions on a consistent basis. And while they aren't hard questions to answer, they're super distracting and they pull us out of high level strategic work that really takes our judgment.
Mandy Hornaday: And not only did it lead to decision fatigue for me, but it caused work to stall a lot. Because by the time someone got stuck and they went and jumped to a different project and then they got the answer, they have to come back and restart. And there was a lot of lost time. So this was definitely a problem I was really eager to solve.
Mandy Hornaday: And what I should also say is that we had a lot of documentation. One of my senior project managers, who's amazing, had done a lot of work to document RACI charts and SOPs and process flows. But I think the problem became twofold. Mandy Hornaday: One was that there was so much documentation that it was almost inaccessible.
If someone had a quick question, the answer was not, let me go read 15 pages of documentation. That was just way too hard. Mandy Hornaday: But the second thing that I noticed as I went through doing this work was that we actually had a lot of gaps in the thinking and in the documentation. So for example, we might have had specific workflows like, here's how we run an event, here's who does what, here are all the roles that need to be played, here's the approvals.
But what we were missing was the macro picture. In that instance, we had the micro picture of how to run an event, but we were missing how does this fit into our macro decisions and approvals, the macro SOW and commercial rights, the macro job descriptions and teams, and how work moves forward overall. Mandy Hornaday: So needless to say, I had my work cut out for me. But I was really excited to dive in, because I knew this would be a huge momentum maker, not only for me and my personal workload, but for the team, and ultimately for getting work to market faster.
Mandy Hornaday: Now, before I dive into the mechanics of what I built and how I approached it and what I learned and what came out on the other end, I want to just pause here for a moment. Because if you don't run a large team, you might be tempted to tune out at this point and say, this isn't relevant to me. Mandy Hornaday: And I want to push back for a second and really encourage you, whether you are a solo marketing leader in an organization, or you have a small team, or you're a fractional CMO.
I want you to ask yourself the question, and really think, what is causing work to stall within each of my clients or within the team that I run? Where is work getting stuck? Where is there friction or bottlenecks? Mandy Hornaday: Because it likely exists.
I think this is a huge problem. Even when I was in-house, this was a massive problem for us. And in talking to a lot of my peers, so many people resonate with this problem. Mandy Hornaday: And it could look like a lot of different flavors in your environment.
Maybe you have a lot of agencies and fractional partners and contractors that you work with. Do you have your network documented so that both your in-house team, or your agency partners, or your outsourced partners know exactly who's responsible for what, and who they can work with in tandem to get work done? Mandy Hornaday: And certainly this could be more about who within the organization are key stakeholders, and what are their roles, and when should we be tapping them and getting them involved?
Mandy Hornaday: One of my clients is a pre-revenue startup, and so I am the solo fractional marketing leader. But what was incredibly helpful for me in my version of this momentum maker was documenting all of her external partners and her scientific board of advisors and the roles that they play, so that I understood who I could tap for important context and messaging feedback and brand project work. Mandy Hornaday: She wanted it to be a highly collaborative environment, but didn't necessarily know who should be pulled in for what.
And so even just by me having that information and being able to document it, that was my version of creating momentum and moving work forward faster in a highly collaborative way, despite not having a big marketing team around me. Mandy Hornaday: So your version may look like something totally different. But I promise you, I think if we all spent a little bit of time, we would all be able to recognize where work slows down or stalls out within our organizations. Mandy Hornaday: Okay, so now let's get into what I built and how I approached it.
From a tactical perspective, what I ultimately built was a Gem through Gemini, because this particular agency uses Gemini. And so I built a Gem for my internal marketing team that I like to think of as a Momentum Maker partner. Mandy Hornaday: And it had everything documented and loaded up, including things ranging from our job descriptions, our RACI charts, our decision-making and approval rights, our SOW and commercial rights, where I wanted the team prioritized and focused, where I didn't want the team prioritized and focused, what the business strategy was, and what some of our priority segments and solutions were.
Mandy Hornaday: And your version of this may not have all of that, or frankly may not need all of that. But the more that I got into it and started solving the problems and taking real live examples of where work was stalling and what was causing it to stall, that's what led to this documentation that ultimately became a snowball in a way. Mandy Hornaday: It was kind of like the snowball effect of, I knew I wanted to start with job descriptions, and then I moved on to RACI charts, but then I realized I needed decision making and approval context.
And then I realized I needed the business strategy and the context around where the business was focused and where they weren't focused. And again, it just sort of led from one thing to another. As I kept throwing real work and real problems and friction into the mix, it kept leading to more and more answers that I needed to provide and decisions I needed to make. Mandy Hornaday: But ultimately what came out on the other side was this Gem that anyone on my team was able to get answers from very quickly, at the drop of a hat.
Is this in scope? Is this mine to do or someone else's? Who needs to approve this? Who do I need to loop in from the sales perspective or from the division leadership perspective?
What does the C-suite need to be apprised of as we're moving this project forward? Mandy Hornaday: So ultimately the entire team was able to get answers to what they needed in real time within minutes, and then ultimately keep the work moving faster. Mandy Hornaday: Now, I realize as I talk about this, this may feel overwhelming. If you listened to last week's episode on this $9,000 AI course that I took and how I approached it and my experience in it, and if you haven't had a chance to give it a listen, I would totally go back and do that.
Mandy Hornaday: But this was one of the AI partners I had decided to go all in on, because I recognized it was one of my biggest areas of fatigue within my day-to-day work. And I really wanted to be able to pull myself out of the day-to-day operation, so that I could focus on the work that only I can do as the CMO. Mandy Hornaday: And so I chose to go big on purpose. You don't have to do this.
And frankly, there's probably much easier documentation that you can whip up within a few hours and ultimately still get your team answers. But for me, I did this as a two-week sprint and I went all in. I probably spent anywhere from 20 to 25 hours, and I went deep on this. Mandy Hornaday: And I personally did this using tools like Wispr Flow, where you can just dictate into Claude or ChatGPT or whatever your AI partner is.
I would go on long walks with Bella, my dog, and pop in my earbuds and record long voice notes, and just talk about where work was getting stuck, what some of my friction points were, how I wanted work to be able to move forward throughout the organization, where I wanted to be involved, and where I didn't want to be involved. Mandy Hornaday: And what I realized as I went through is that even though we had great documentation, there were so many gray spots and so many areas that frankly I had to make a lot of decisions on.
And part of why the team was getting tripped up is because I hadn't made a really clear decision for everybody. Mandy Hornaday: And this isn't to say, by the way, that I don't want an agile team with me. Of course I do. I love that I have a team that is full of Swiss Army knives who can just jump in, great attitude, great agility, and get work done.
And that is something I will continue to hire for. But what I realized is that there's a difference between being agile and being clear. And to be clear is to be kind. Mandy Hornaday: As I was going through and documenting everything, I actually used AI as my sparring partner to help me understand where would work fail.
So based on our operating models and our systems and the roles that we had, where was work destined to fail? Mandy Hornaday: And it was so fascinating, because it actually dove into things like capacity planning, and it told me which team members were going to be stretched and ultimately turn into bottlenecks, which it was correct on. It told me gaps on the team where work would stall because no one had clear ownership over certain areas. Mandy Hornaday: And so as I came out of this work, not only did I finally have a lot of clarity on my vision and how I wanted the team to be able to show up and work together collaboratively, but I also came out the other end having expanded people's roles, having clear coverage over things that we would need repeatedly, and having really clear areas of ownership.
Mandy Hornaday: So one of the things that I ended up doing coming out of building this AI partner was I met with everybody on the team one-on-one, and I told them about what their role is and how I had expanded it, and where I wanted them to step up and evolve, to make sure that we had the entire puzzle covered. Mandy Hornaday: And along these lines, one quick story I want to share. Within the organization, there's a sales enablement team that sits under sales. And then as you probably could expect, we within marketing have our own sales enablement function as well.
And there was a lot of overlap, despite the sales enablement function within sales being really sales support, and pushing actual deals forward and getting them to proposal stage and doing RFPs and RFIs. And our sales enablement team was really about creating collateral and making sure sales could sell into our priority segments. Mandy Hornaday: So for me, the lines felt very clear in terms of the roles that these two played. But for them, they felt like they were constantly operating in the gray, and they felt like there was a lot of overlap with their roles.
Mandy Hornaday: So if someone, as an example, needed a case study in order to close a deal, is that the sales support team that's creating the case study, or is that marketing that's creating the case study? And that's just one of so many examples that was leading to this friction and frustration between two highly talented team members around their roles. Work was stalling out, and there were instances where they were undermining each other, not necessarily on purpose, but because the lines and boundaries weren't clear.
It was becoming quite a problem. Mandy Hornaday: And this is where AI was such a great partner, because we were able to really clarify the roles and the differences between these two talented members. And then AI ultimately became the referee in a way. It was able to use these agreed upon roles and responsibilities and apply that framework to real everyday scenarios.
Mandy Hornaday: And so that was one of the coolest things. As we started getting more of these situations coming in, my team member was able to just put it into this Momentum Maker AI partner and get an answer, and get the logic behind who was supposed to own what, if they should both be involved, if one of them should be looped in, and why. Mandy Hornaday: And it has just relieved so much pressure in one part of our system. And so on a team of 15, you can imagine that there were so many more stories just like that one, where we instantly got clarity and got things cleared up.
Mandy Hornaday: Okay, so once the build was over, let's talk a little bit about implementation and activation. Because so often the activation of these tools and resources that we build for our teams is so incredibly important, and it's often where we spend the least amount of time. Mandy Hornaday: And so for me, it was really important. I had just spent 20 plus hours doing all of the work to build this clarity and make decisions, and I wanted to make sure that the team really benefited from it.
Because if nobody was going to use this AI partner, then nothing would really change. Mandy Hornaday: So the first thing I did was I demoed it live with the entire team. And it was actually kind of funny, because in the demo, I'd had the team members throwing out scenarios where they have questions. Tell me a question you had today, or tell me a question you have this week that you would love to get the answer to, that maybe you would have asked our senior project manager, maybe you would have asked me, maybe you would have asked your manager.
Give me those questions and scenarios. Mandy Hornaday: And I'm so glad we did that live, because ironically, some of the answers that came back were wrong. I'll talk about this a little bit. Mandy Hornaday: I had gone through two iterations of this AI partner.
And in the first iteration, I didn't want it to hallucinate whatsoever, or really make decisions that weren't clearly defined. And so what that looked like was, in the first version of the AI partner, I essentially said, you can only share information that is clearly documented within this documentation. I don't want you to infer. I don't want you to make your best guess.
I want you to be very specific and clear to what's clearly documented, and then have a fallback person. And that fallback person in my instance was my senior project manager. Flag everything that's unclear to the senior project manager. Mandy Hornaday: And while I thought that was a good idea at first, I quickly realized that that wasn't actually going to get me the most benefits from using AI.
So for example, that last scenario I just shared around the sales enablement clarification. I don't know, nor do I want to guess, every single possible scenario and who should play what role in that scenario. And part of why I'm doing this is because I want AI to be a partner in this, and I want AI to take its best guess with logic and reasoning based on my thinking. Mandy Hornaday: And so I ended up making that change.
That was sort of my second iteration of this AI partner. I said, you know what, I want to actually loosen up the reins here. Mandy Hornaday: But in doing that, it was pretty interesting, because there were places where it didn't match with our day-to-day. So for example, on paid ads copy, that was one of the examples that was thrown out live to me, and it defaulted to our content writer who writes pretty much all of our copy.
And so that was a really strong inference by AI. But in our actual day-to-day, our paid ads person writes copy, because she's also a great writer. Mandy Hornaday: And so there are little situations like that that I had to go back and iterate on the documentation. And that's to be expected, by the way.
I wouldn't have done anything different. And actually I encouraged the team to send me screenshots of the conversations they were having, especially if anything felt wrong or off, so that I could go in and tweak the documentation. Mandy Hornaday: And while I probably could have spent a week just testing it myself and refining it before launching it to the team, honestly, I knew I would get way more feedback a lot quicker if I rolled it out to the team, and I'm really glad I did.
Mandy Hornaday: But knowing that, two things. One is, I would make sure that when you're going to roll something like this out, that you've planned and you've batched some time to fix and update the documentation as you go. So my first week of rollout, I did updates every single day, because that's when I was getting the most feedback. And then after the first week, it went from probably 85 percent of the way there to 95 percent of the way there.
And then I moved to a weekly cadence of updating. And now I just do brief updates and edits as things change, or as I get screenshots of weird conversations that my team has had with this AI partner. Mandy Hornaday: And the second thing I would just encourage you to think about is, don't be afraid to update the prompt. Mandy Hornaday: So this was another funny thing that happened.
I had originally had my senior PM as the default. If there are truly things that this AI partner can't answer, I didn't want it making things up if there wasn't logic or context to come up with a really clear answer for. And so there were a few things where my senior PM, who was the fallback person, she was using this AI partner a lot, and it kept saying, oh, you need to go talk to the senior PM. And she had to keep saying, well, I am the senior PM, and I don't know.
Mandy Hornaday: And so originally she thought, we need to teach people how to prompt this AI partner better so that they get better results. And what I helped her understand is, no, no, I need to tweak the prompt. I want anyone of varying levels of prompting skills to be able to get the answers they need. And so I kept messing with the prompts.
Mandy Hornaday: So it's just something to think about. Force AI to solve its own problems. It usually will have great solutions if you even just tell it and say, hey, my senior PM wants to be able to use this Gem a lot, but she keeps running into the fact that it wants her to be the go-to answer. And so that was an interesting learning that we had.
Mandy Hornaday: And the last thing for me that was really interesting was, I actually had a few people on the team say, I don't know when I would use this, or I don't think I need this, or, this isn't really something, like, cool that you built it, but I don't need to use that. Mandy Hornaday: And ironically, some of the people that said that actually needed it the most, because they had really blurred boundaries and were probably over delivering in some areas that weren't really their responsibility, but then under delivering in others.
And I've got an amazing team, so this is not about them personally. I think a lot of us have encountered that type of mentality in the past. Mandy Hornaday: And so one of the things that was really important that I did as a part of the rollout was to help them understand how to prompt. The great thing about AI is you can always just ask AI.
So what I'd encourage them to do is just tell it who you are, because this partner already knows who you are and what your role is on the team, and ask it to give you five reasons that you might need this, or five different scenarios where this Momentum Maker partner would be a great potential partner for them, and just help them get the juices flowing. Mandy Hornaday: And so that's something I would encourage you to do. And all of these best practices are probably great for activation strategies, no matter how you're using AI and bringing your team and resources and partners along with you.
Mandy Hornaday: So hopefully you're able to see and think about how something like this might be helpful in your own organization. Whether it's for people outside of marketing to know who is responsible for what and who they should go to, so that not everything is routing through you. Whether it's you thinking about all of your internal stakeholders across multiple departments, so that you can figure out, when you're doing project planning or thinking about rolling out a big initiative, who should be involved, who should be accountable, who do we want providing feedback, who's a part of this project.
It could be inside your team, and it could be cross-divisionally as well. Mandy Hornaday: And of course, if you're fractional, who's your entire network? Who can you pull in to different engagements or on different clients, if and when you need to get work done that you don't necessarily want to do yourself? Tons of different ways you can think about this.
And ultimately, again, think about it under the context of, how do we move work forward faster? Mandy Hornaday: Now for me, in terms of what this gave back to me, I easily got anywhere from five to 10 hours a week back, just on this one client, by the way. Now, it is my biggest client, but that was huge for me. Mandy Hornaday: I have since stopped receiving all the Slacks and the emails, and having to do quick huddles or quick calls to make sure that people knew how to proceed with a specific project or initiative or program.
It has been huge for me, and has ultimately helped pull me out of the day-to-day so that I can focus more on building and documenting our strategies and our plans and our roadmap, and continue to build the CMO Operating System across the organization and across my clients. Mandy Hornaday: And frankly, now that I've done the hard work of documenting all of this, there are so many different ways that I can activate all of that knowledge and intelligence in really cool ways. I can do capacity planning for my team against our upcoming roadmaps.
I can build automations into our project management systems to make sure that when new tasks or new projects are getting created, it's automatically getting assigned to the right people. I could do proposal building and project planning for new clients. I can think about team hiring and who I'm going to need to bring in next, and help these team members do some career planning and figure out where they can grow and evolve within their roles. Mandy Hornaday: There are so many ways that once we do the hard work, the foundational work of these decisions and this documentation, that you can really bring it to light in a lot of different ways.
And so I'm really excited to be able to dive into many of those across a few of my clients. Mandy Hornaday: And so if this has inspired you in any way, one place you can start immediately is opening up your favorite AI partner. You guys know mine is Claude. And just knowledge dumping a little bit with one of your clients or with your team, and sharing what some of the friction is that you want to get unstuck from.
Maybe share a few different scenarios of where work is currently stalling out, and ask AI to help you figure out, what do you need to answer, or what information can you provide to unblock some of that work, and start there. Mandy Hornaday: I went all in and documented a ton of things that can now be activated and used in so many different ways, but you don't have to start there. You might be able to just get away with starting with job descriptions, and that alone may be able to unlock a ton for you.
Mandy Hornaday: So take it small. But ultimately I think it has this snowball effect, and the more time that we're freeing up here, the more time we can focus and continue to pull ourselves out of the day-to-day across the entire marketing department, so that we can get back to doing the work that matters most. Mandy Hornaday: And if any of this sounded really intriguing and you'd love to learn more about this one piece of the broader CMO Operating System that I'm building, I will be having a fall cohort where a bunch of us, from both a fractional and full-time CMO perspective, will be coming together this fall to build out the broader operating system together.
And if that sounds like something you're interested in, I'd love to have you. Please check out growthactivated.com and join the waitlist to be considered for the founding cohort. Mandy Hornaday: All right, everyone.
So glad we got to catch up today. I hope this was helpful. And as always, in the meantime, keep activating growth for yourself and your company. I'll see you soon.
Mandy Hornaday: Thanks so much for tuning into this episode of Growth Activated. I hope this conversation sparked new ideas, challenged your thinking, and gave you practical tools to help elevate your impact as a marketing leader. If it did, I would love for you to pass it along to a friend or a colleague in B2B marketing. The more we grow together, the more we raise the bar for what marketing leadership can look like.
And as always, in the meantime, keep activating growth for yourself and your company. See you next time.
Other episodes covering the same guests and topics, from across The B2B Podcast Index.