S17 E6: Why Your Company's AI Chats Are a Total Mess (And How to Fix It)

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That's nik.co/tatari. Welcome back to another episode of Limited Supply. I'm your host Nick Sharma, and today I've got a very special guest with me, and he himself is an AI expert in somebody that I've learned a bunch from when it comes to AI. And you know, one of my goals here is to bring constantly, whatever I'm learning, bring

it to you guys, and in a way that's easy to digest, easy to understand. So today, I brought on a friend of mine, Jacob Puzzle, who I met recently, and I've actually learned a lot from him, and the company that he is building, which is really around creating kind of an operating system, an AI operating system for your brand or your company, your organization.

And so we talk all about how to get on with AI, how to start using it as a company, where there's onboarding failures or what succeeds when you're onboarding, and just really like how are different people within the org also using it to their advantage. So check out today's episode. Let me know what you think.

Shoot me a DM on Twitter. You can also DM Jacob if you've got any questions for him, and I'll see you in just a moment. All right, Jacob. Welcome to Limited Supply. I'm excited to have you here today.

You've been all over the Twitter feeds.

“Now, honestly, we never really connected until recently either, but we've been Twitter friends.”

And obviously, you know, we've seen all this, everything on the timeline talking about HQ. So I thought, you know, why not just bring you in and let's talk about HQ is also somebody who's now been a user for a couple months, and started to learn a little bit more about what you guys are doing. I thought it would be really cool to share what you're doing and how, you know, other

brands and other operators can leverage it. Yeah, I'm excited to be here. Thank you for having me. Of course. So why don't we start with some, you know, kind of like the one thing that I think will

get people excited about hearing more about HQ too is what happens, you know, when a whole company starts using Claude or chat GPT, and what doesn't happen, you know, like, I was at, I was, I didn't recently, and somebody was telling me about this new logistics tool that she built in Claude, and unfortunately her direct reports can't get access to it, because she built it in Claude.

So I want to start with that, and then I want to go into more HQ and your background, and then let's talk about how different functions are using AI from what you're seeing as their clients of HQ. Yeah, yeah, I mean, I've seen, I've seen the insides of lots of businesses as they try

roll out these tools, and it always results in this extremely weird fragmentation, which

is obviously what we're trying to solve, but there is this extreme gap in certain individuals in their ability to pick up the tools, and so you can give 50 people Claude or 20 people Claude, and the distribution of how they would actually end up using that tool is completely different, and so you'll have the person like you just described a build something great, they'll build something cool, and they'll have no way to be able to share that with their

team that often results in a huge amount of duplication of workflows and of work, which is kind of the opposite of the efficiency that you hope to get with AI. You also have this, like, weird phomo that happens where people start to get scared, and they like see other people accelerating past them, they can't quite catch up, they get scared of the tool when it's not really necessary, and because it's so new and you kind

of have to go to the edges to figure out how to use these things, you just the differences are like very wide, and so what I've seen happens is you try and you roll these out with

an accompanied, but you never really get that nice compounding benefit that you expect.

You get people being more efficient and more effective, but you don't see it moving the

problem, and so that's obviously what we have tried to solve with HQ.

“Yeah, and are you seeing companies becoming AI native?”

I actually, you know, like obviously I feel like the answer is yes, like one, one, whatever

I asked that, but this, this past weekend, I met up with a friend of mine who's a YouTuber, and I just randomly brought up AI to him, and he's telling me that like from what he sees, you know, among call it normies, not us, you know, podcasts, listeners or people like elsewhere, he said that more normies are like very anti-AI, and so I wonder if that's trickling its way into the business world outside of our bubble, I can curious what you're

seeing. Yeah, I haven't seen businesses that are fully AI native and enabled, unless they're very recently found the businesses, or you have, you can have majority AI enablement, but that has to come from an extremely strong CEO found to figure, I'm always surprised by the lack of AI proficiency that I still see.

The tools are gotten easy and gotten more powerful, so it's easy to be good with AI, but

you don't see, I'm still surprised. It's of my circles, I try, when I try, when I socialize with friends, I try not to talk about AI, it's my only one time that I can, but it's obviously not possible, but yeah, I haven't seen that same penetration outside of the like, Twitter see a day I live with in.

Yeah, but not together, that sphere is mostly found as CEO types, you know, like, even within their companies, it's not the same, it's not, it's not, it's just the people at the top that are really trying to push it because they're the ones who experience the ROI from it. Yeah, I feel like too, like, that is, yeah, that's actually probably what I've seen

to. There's usually a few people in the org who are super AI-pilled, and they're trying to bring everybody else with them, and kind of get the org set up. Okay, I want to go into your backstory a little bit, so you were, you were in engineering, and then you sort of made your way into the marketing sphere, or the kind of like the

tech sphere, then, you know, and I feel like you were journey with AI probably involved in curious, like, what, what did you think you were getting into at the beginning versus

“like, where did it evolve to, and like, how did you guys get to HQ?”

Um, I mean, my AI journey started very early. I was, um, I was doing a basically an AI machine learning master's degree when I graduated right before a chat GPT was launched, and so I was already in the machine learning space. I got to job as a software engineer and data scientist at an e-com logistics company, and I was helping them build basic forecasting models, like sales forecasting models to help

forecast demand within the warehouses, and then chat GPT was launched, and I basically just quit my job instantly. I was like, I think I saw the writing on the wall, but soon, and because I saw how powerful this was, and so I literally instantly quit my job and try to study AI company, um, and I was trying to build an AI logistics company for e-commerce, which is very different

to where I am now, but it just wasn't that powerful back then, and I think you could

always see where it was going, but it wasn't quite there.

And then, in a roundabout way, I got connected to coming thread collective with Taylor Holiday. He kind of took me in, took me under his wing, and I worked at them for a while. And again, like, we always had these super ambitious visions of what we could do and what we were trying to do.

Um, and we, if I were always waiting for the next model to release, like, again, now we're going to be able to do it. Now, we're going to be able to do it. And then that actually happened, like around December last year, that actually happened with, like, the Opus 4/7 Opus 4/8 launch, and then we had this amazing moment where

we were able to just do everything we wanted to do, build what we wanted to build, um, and I kind of just want crazy just doing as much as I possibly could. The way that HQ came about was Corey Epstein, who, um, who I was connected with again, also through the same, like Twitter world, him and I had been in touch for a while. He had actually created this personal tool called HQ at the time.

It wasn't a team tool. It wasn't a company tool. It was his way of being able to manage AI, personally, more efficiently and more effectively. And he had started converting all of his friends onto it. So that's how he got me onto HQ.

And I was like, Corey, this is sick, but this needs to be a different tool, this needs to be for companies. This would be so much more powerful if all this contest could be shared across companies.

“And that's how we teamed up co-founded this company and now that's how we have HQ.”

And now it just feels like we're able to do whatever we want, like it's just, it's unbelievable

And now we're building infrastructure because we've experienced so much across so many of businesses. I have seen so much across so many businesses through that journey. So now we're just trying to build the best infrastructure companies to run on.

Yeah, that's pretty amazing.

“And can you explain, like, to a fifth grader level person, how the product works?”

Yeah. So when you have a whole company using claw, using charge of BT, you're using AI, what happens on my charge of BT is just on my computer, it's in my personal account, what happens in yours is just on yours. And we have no clean and easy way to share that with one another.

And HQ basically connects all of our different AI tools together so that we're operating on top of shared context. So if I do something, I can share it with you. If I build a workflow, I can share it with you. If I connect to a new system, I can share it with you.

And so that allows us to work together. That allows us to compound what we're doing across an organization. And it allows us to get those people who are lagging behind to be on the same level as us, because if they just use charge of BT connected to HQ, they're automatically inheriting everything else that we've already put in there from the rest of the company.

Yeah, I also describe it as drop box sink across the company for all things AI related. Yeah. Yeah, it's a good one. If you, there's a good way to compare it to other companies. It's like drop box for agents, one password for agents.

And then like agents for agents kind of thing as well. But yeah, there's like a good way to think about it. Yeah, I use it to basically just stay up to date across all devices.

And all team members across all projects, it's pretty amazing.

“And the other thing I think is cool and not talked about enough is your memory system.”

Is like the way it's built, is it called vector memory? Is that right? Yeah. Yeah. Vector memory.

So it's not just reading markdown files. It's like a whole different way to recall memory, which just makes all the context and makes the output so much better. Yeah, like it's really important that let's just say you built that logistics tool. And I started building logistics tool.

It's really important that cloud is able to recognize that you built it first and to find it. And to do that, we had to give this great this company wide memory, which uses some really cool searching and retrieval techniques that we've built. Yeah, very cool.

Now, I feel like a lot of companies right now are popping up with their, or, you know, like everything started in the chat window, and then a bunch of other softwares have integrated models within what they already do. So like, you know, influencer searching software now has a model to help find better creators, maybe.

And then it's going toward more like open source software where you plug your models in and you, you know, have your thing work, however, which is probably where it sits with like cloud code and codex. And then I feel like the next version of this is maybe, actually, I don't know what the next version of this looks like, but AI employee is starting to pop up now a lot more.

And I think because the quote, quote, quote agents are easier to visualize or build or create. Is that what you're seeing right now? Yeah. Yeah. I mean, it's too, that there's two sides to it, is definitely the code code codex,

like the harness agent, agentic tools for slightly more technical people. But then the AI virtual employees are really, really easy to adopt and understand for less technical people because if you give it a persona and you drop it in Slack, then people are able to pick it up easier. So I'm seeing that a lot, especially with like the grock, but launch that came today,

like there's a lot of these companies that are doing really well. I think it's a combination of the two that to work, like I don't think one works without

“the other, you have to connect the two together.”

Yeah. And how does like a company when they are getting started on all of this, right? Like I felt like with my own AI setup, I spent definitely a month or two intentionally

trying to create knowledge files or, you know, basically ways of where I would be different.

So like if the prompt was, you know, build a wire frame for a landing page, my personal one would be way different than like if you just asked generic chatGPT, how does that whole process of like creating and downloading context and sharing context work in companies that are, you know, like they have multiple employees and they're doing things in different platforms.

Yeah, um, in order, so you have to give people a workspace where they can work without friction basically, like let's just say you're creating a task, like you're creating our landing page or something like that. You need to give people a workspace where they can do that end to end, because when you try and tell people write a perfect prompt to generate a landing page, it's very rare that

It's basically impossible that someone can just do that.

Right. But if you give them a way for them to generate that landing page and to end and then iterate on it and iterate back and forth with the agent, then what you get at the end of that, if you just say, note down all of the adjustments that I made and all of that is that I made and turned this into a skill, then you actually do end up with something useful.

And they also don't need to understand the concept of what a skill is up front or like they get stuck in this decision paralysis, because they don't know what I just learned what a skill is last week. Yeah, exactly. Like you really need to know, right?

“Like you don't all you need to know is like the agent knows what to do or the harness knows”

what to do. All you're going to do is do the task and give a feedback. So the best way that I like to do it is connect all the systems for people up front so that they can at least do work and to end unencombed, give them that workspace and then just tell them to do the work and when the work is done, then turn it into something reproducible

or at least do it in a place where I or someone else has access to it or it's saved down some way so that you basically have that as training data and then someone else can aggregate that into a repeatable workload. But these things fail very quickly when someone comes in like an AI consultant pretend to understand your business, interviews a couple people and tries to create a skill to do

something which is hard like to create a great landing page is hard many years of experience. Right, especially maybe you have like certain documents that you know have legal constraints or how you can work things and yeah. Yeah. And if I told you just write that down up front, you wouldn't miss things.

“You would be, you would forget that you have your brand guidelines and some random”

Google dark one notion. Yeah. You know, but if you did it and you credit and you will like, oh, this doesn't look like my brand, you'd be like, oh, wait, I actually, I usually share this with the credit strategists and that's how it comes together.

Yeah. And our most people like, like, in this process of creating skills, is this something that like HQ is doing on its own for as you're using the product or is this something that people are setting time aside and saying, okay, like, these are all the skills I need to build out.

Now let me go and build out these workflows and try to train HQ on it. Uh, it happens in two ways. So one is when you set up HQ, we will ask you, what are the things you want to create or are the repeatable workflows you want to create and it will go through that process with you.

The other way that it does it is the one that I just described where at least guarantees that all work is captured and recorded somewhere and then sometimes people will go back and create those skills or those workflows automatically. But the interesting cool thing about HQ is because that's all stored somewhere. The kind of just creating reproducible workflows that I've been having to really think

about it because I can just say do that thing that I did last week and HQ will be able to find it for me and now it's become a reproducible workflow in a way. So people, they get lazy.

Like, I'm, I'm like a victim of this too where I'm not even like creating the skill always.

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We have a lot of stories here about where somebody has done something on HQ or created some kind of like a skill or process and then the whole company has been able to benefit from it. Yeah, we have hundreds of examples in our company. I can also talk about all the companies too, but I mean, a good example for our company

is something I'm experiencing right now is I'm like an analytical person, but creatively I'm not quite that. I can't create a beautiful deck like I'm not going to put beautiful assets together, but

we have someone on our team who is incredible at that and I created this one page for something

we're trying to show and it looked terrible. It had all the right numbers there, but it looked absolutely terrible and then she made one and it looked amazing, it looked great and now she made this one deck and now this is the template for all decks that we create inside of HQ and I just took that one page I created, I told Claude, I said reference, the deck that she made and just combine them

And now all of these assets that we're putting together like partnership decks and sales

“decks and invested decks and everything like that, they all look amazing because they created”

through her artistic eye, but everyone else gets to benefit from that. So that's one example and that extends out to all different decisions or things created in the company, like all the engineering things that we do are based on what the guidance

was about best engineers basically and it's not just the code itself, but it's the rules

and policies that they put in place for our code base that live within HQ or the way that I analyze data which is a little bit different, like HQ is a quite complicated system and so the way that I analyze data, everyone else can adopt and look at through the skills and workflows that I've created to make sure they're looking at the right data. So that just extends in many, many different ways to everything we do in the business.

Yeah. How do you see different roles within a company like leveraging AI in their own ways to be advantageous in what kind of business and like I kind of business or like yeah

“in a brand, yeah, I think like more on the brand side, I guess.”

So a lot of it is around there's like two sides to it and it almost depends if you are revenue generating or like a proper generating role or not, like what I see for a lot of

marketing teams is that they're able to generate a lot more, they're able to basically

extend themselves outwards and generate more and do more revenue generating activities or people are able to do that with smaller teams, they're able to maintain the same amount and smaller teams so it's basically more per team member to the extent that I know single people who are excellent marketers doing like two or three or four roles themselves just with AI and creating agents and that's really, really cool.

So these people are doing more with less and it's resulting in growth for their company like more ads, more landing pages, more emails or leaving it to handle it themselves. And then when it comes to other roles like backhand roles, finance roles, stuff like that, I'm seeing of course like it's just more efficient, there's a lot of efficiencies, people

“are getting more disciplined about data and about infrastructure like everyone's a data”

warehouse now because they know they can have access to do all these things, but I'm seeing more sophistication or level of analysis that they're doing like before someone may have just had, they were just like creating some kind of inventory for a car, so basically opening their PNL together, but now with some really young brands without a ton of resources, I'm seeing them put together super sophisticated like LTV to hack analysis, pop, skew,

subscription cadence because they're able to run these analyses that are really like significantly impacting the protection of their brand because they have so much access to data because if they just use Fable 5 and Claude, it's like a state of the art AI like data analyst, you know? So it's resulting in people able to do more with less and a lot more sophistication

and what they're doing as well. Yeah, I feel like there's the notion that AI is going to replace people's jobs, but AI either on its own or AI being run by somebody who doesn't have domain expertise is

never going to compare to like, like you're saying, these brands probably have somebody

who's like a sharp shooter at what they do and then being, you know, being able to use AI now they have all the leverage in their own pocket. Yeah, and I mean, I never agree that AI was going to take a bunch of jobs. Like, I, to me, that always assumed that brands were operating at capacity already, like everyone was just operating at 100% capacity with 100% efficiency and there was no room

for growth, but I never saw that in the company that ever worked with. So I feel like these people are just doing more, they're just doing more and better. Like the silly mistakes that I used to see people making, like putting a ton of ads has been behind products that are out of stock all like really like really messy tags inside of Shopify and like, excuse, like these mistakes on happening as much because the ability

for AI to just clean it up for you is very, very easy. And so the sophistication that they running at is more and so they're just doing better, but these people haven't gone anywhere, the people that can use AI, they're not getting fired. Yeah.

We've seen that one chart too, it's got all the dots and it's like, this is how big the world is and then the last dot is just like, this is the people who've just discovered AI. Yeah. It's like, yeah.

We've still got a long ways to go. We do. Yeah. And I, like, I think companies are just going to do very, very well.

they have. Yeah. What do you think like brands that are looking to be, you know, like, they're not looking to be in a spot next year, where they feel like now they're behind on AI, you know, but maybe they're not fully AI-pilled yet.

Like, where do you recommend they go or look into or like, where should they even start? I mean, people, most people who ask me this question, I say to them, are you using it every

“day and they say, no, and it's like, well, that's, that's what you have to do.”

You have to open-cloud code or open code acts or create a Hermes agent or an HQ agent. They should be definitely using HQ, but just like use this thing every single day and try and do everything with AI. Like, I can't imagine almost any task that I do in my day today that I wouldn't go to one

of these AI tools for first.

And so it just blows my mind that people are like, that people don't know what to do or where they can work. And I've worked in, I've worked at brands, I've worked at agencies, I've worked with software companies. I've worked in, like, the biggest and smallest companies in the world.

And there's everything that everyone does. If you set it up the right systems and you understand how to use them, code code can do it just as well as you. And so if you are the leader of your company, you have to be doing that every single day.

“Once you have a good grasp of how to use it, you should sign up for HQ and then get your”

whole team on HQ so you can roll this out to the rest of your team. But if you're not doing it every single day, if you're not training yourself, then there's nothing else you could really do. It's not going to magically come to you. I think people assume that it's just going to magically come to them.

Yeah.

I heard this head of HR for pretty large consumer brand recently, basically be like, you

know, we can't discriminate against people when we hire, but like, if you're not using AI and this day and age, you're basically just not fit for a role at any, you know, any more. Yeah. Like, that's almost just a given, but at the same time, I feel like there's so many companies I talk to that are just still, you know, so far away from any sort of real adoption other

than, okay, let me, you know, take a CSV dump it in here and ask some questions. Yeah. Yeah. I mean, even if that's where they start, like, even if that's just where they start and they just do a little bit more every single day, they'll get it good eventually.

Like, I wish I could shake people and just tell, like, if I took the average employee and I taught, if you use Claude Code every day for the next two months, you would probably the most valuable person in your company. And I see that every single day, time and time again, and people just don't do it. I think it, in Todd, it requires a different level of thinking people are busy, but I wish

people realize that. Yeah. Um, okay, a couple of questions I have. So like now, going back to, to, um, you know, HQ and, and having kind of your, your brands or your company's second brain, you know, agentic and ready to access, how do you make

sure that this thing is always staying up to date?

How do you retire, stale context, you know, how do you make sure that if like, there's one thing that's wrong and there gets caught or fixed so that the whole company is now not operating off of this, like, how do you think about that or how does that work?

“The best way to deal with that is to use it every day, like, the more people you have”

using it every day, the quicker you would uncover and pick up and fix incorrect context. Like if I'm doing something inside of HQ and it says something wrong, that I see related to my job, but I pick that up very quickly and now I can remove it, and it's kind of the same with every, it's like this, it's the same with all work, like it's not very different to pre-AI work, like if I was creating an SOP and the SOP had a wrong step in it and then

I did it and it was wrong, then I should go and fix it and so that same kind of responsibility is on people, although that's not always a good enough answer and so we have a couple ways of automatically dealing with it. We have something called a gardening agent and the gardening agent basically will automatically go into HQ, look for, it can look within the actual message sessions themselves and trying

to determine this. Like if someone said something was wrong or incorrect and it wasn't solved, then it will automatically remove that. It will look for contradictory context and they're trying to remove that and then it will also age context based on date and so if something is old, it can expire it or out of

date, it can expire it and it can do this with the full context of your company. Like for example, a really good example is let's just say we work together and then you leave the company and it's like and then it says you should go talk to Nick about this but HQ should know that you left the company because somewhere inside of HQ, somewhere inside of a cold trans group, somewhere inside of a Slack message or an off-boarding session, there

and then fix that context and that's what the God and agent is supposed to do.

Yeah, that's pretty cool. I'm curious, like where do you see the future of HQ going? Like we were talking a little bit earlier today about some of the other companies in the space but yeah where do you see HQ's future? The future of HQ is two pieces to it, one is that it should be the default option for

a collaborative AI work so when we work together, when we do something with AI, there's no really great way for us to truly collaborate, like to be truly multiplayer in that working on something at the same time, working on a project at the same time, right? There's like it just doesn't, it's not built for that and so HQ should be the way to do that across multiple different agents, across multiple different people, across different

teams and vendors, if anything requires any kind of collaborative work, HQ should be the default solution to that and then the other one is that what we're collecting inside

“of HQ is all the important context that you need to do to run your business and has”

context on every single thing that you do in order to run your business and so what we should be able to do is tell you, proactively, once we recognize it, what are the best models that you should be using, what are the areas of opportunity for automation, what are you missing, that you could be doing, what are agents that you could be creating and then also let you train your own models to be able to do that.

We see a future where companies themselves can have their own models that are hyper tuned to how they run their own language, their own workflows and we should give you the ability

to do that so you can get your edge based on using HQ and you should be able to basically

create this recursive self-improving loop where you do work, the model improves, you do more work, the model improves and we should be able to get that all to you through HQ. Yeah, and I think to the other piece there is like the or one thing to call out, it's not really the model that improves, right, because the model stays the same, but it's like your HQ operating system is what continues to improve and get smarter and smarter.

Well, we should be able to give you a model like is it going to be a future probably in about two years from now it's going to be cheap and affordable enough that rather than having a Hermes agent running your Mac mini, I can actually ship you a computer where a true

“model runs for your company, like inside of your office, right?”

Like this is an actual AM model that is yours and we should be the ones giving that to you because we have all the training data to make that possible based on what we have inside of HQ. And now like this is your IP, it's like it's like AI is more than just a tool, it's the intelligence of your company, like it's truly the it's the differentiator of your company, like it's

a reflection of you and your intelligence, basically as a team and so that's important and

I think people are going to be ambivalent to give that all to the model companies eventually and so we should be giving that we should be allowing you to truly own that, like truly physically own that for your company. Yeah, wow, that's pretty cool. What kind of like AI habits or use cases do you think are going to be looking ridiculous by next year that people do right now?

Um, what's going to be ridiculous? I mean, I think Claude Chattin co-work going to go away, like anyone saying they were using co-work instead of code, like that's just what we're going to collapse and go away. Um, I think any company that's stuck to any single LN provider, like we have companies that we work with that I just, I'm just a Claude teams company, those companies are going

to get in a lot of trouble, um, and that's going to look silly. Um, I think that in the future we're going to see more efficient model routing and I think it's just going to happen automatically and I think the whole thing of like, you know, if you go in a Claude code or code X and you like select the model, you select the effort mode, you select the like plan thinking like all of that. I think that just goes away and all of that complexity

goes away, um, and it just happens automatically. So I think all these automatic toggles that we have, um, but I think in general, like the whole prompt engineering thing, like that was, that was like a little bit premature and looks silly now, but I think we're at a more different level now where we're not doing too much crazy stuff, okay? So we're just talking to the models now, right? When I do any crazy, like hacky things, and so I don't see anything

“like that to superior. Yeah, I feel like prompt engineering, like I remember, I think maybe”

last summer, I talked to Billy Howell, we ever talked to Billy? No. Billy Howell was like, uh, he was vibe coding a bunch of apps last summer and like he was teaching me what a PRD is and how

you just rip a whisper flow for four minutes and like that's, that's about all you need to do.

Yeah, yeah, 100%. Well, I actually think something that might just be disappearing is

“all that, I think vibe coding is gonna stay and I think people are gonna be creating internal apps,”

but I keep seeing people creating and shipping SaaS companies that don't need to exist.

And I think, like a moment in time, like they do something cool. Totally. Also, there's gonna be like

“100,000 SaaS companies with no customers. Yeah, exactly. Yeah, exactly. You guys are way and I think”

people realize that there's more alpha and more value and sticking to the businesses that they

good at and just trying to apply AI to that. Totally. Cool. Well, Jacob, thank you for coming on, limited supply, um, and and talking about HQ, we should definitely, we should figure out something else to do with HQ because again, like I was telling you earlier, I feel like there's so much that it enables you to do that I still even haven't uncovered or understood yet. Yeah,

“I don't want to get to that. Should do some working sessions. 100%. Cool. And where can people find you?”

You can find HQ at hqfoark.com and you can find me on twitter, uh, Jacob on the scroll puzzle. POSL. Thank you for coming on. Thank you. Thanks for listening. We'll be back next time to cut through the noise on Cpg, retail and e-commerce. If you enjoyed this episode, why not share it with a friend and be sure to subscribe wherever you listen so you don't miss the next one.