Episode #103 Sh*t Data IN, Sh*t Data Out. You CAN'T Achieve Autonomous Revenue Without This - with Elio Narciso

Ready to eliminate the dreaded “manual work tax” in your go-to-market strategy? Dive into this episode of Bridge the Gap, where Elio Narciso—CEO of Scale Stack—breaks down how his autonomous revenue engine uses AI agents to clean CRM data, enrich lead intelligence, and prioritize the RIGHT accounts—so you don’t have to waste hours on spreadsheets. Discover why leadership, solid data foundations, and strategic orchestration (not just automation) are your secret weapons.

Whether you’re a founder, RevOps specialist, or sales leader, this episode is your blueprint for a cleaner, smarter, faster revenue machine.

What you’ll learn:
 • What “manual work tax” really means—and how to kill it
 • Why bad CRM data is silently sabotaging your GTM
 • The difference between automation vs. orchestration
 • How AI agents autonomously clean, enrich, and prioritize data
 • Leadership strategies for aligning RevOps, ICP and GTM vision
 • When and how often to pressure‑test your GTM foundations
 • Why recording every sales call is non‑negotiable
 • The emerging role of CEOs as chief marketers

Follow Elio - https://www.linkedin.com/in/elionarciso/

PS - huge shout out to Sendoso for sponsoring our show.

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ZoomInfo is also a proud sponsor - check them out here!

🎁 Lastly, we have a gift for you! We’re tired of seeing people getting critical GTM components wrong. Need help with your ICP, Buyer Persona, and Value Prop? Tired of the shitty “resources” people “give away” to gain followers?

We’ve developed a tool that creates your basic GTM Foundations (ICP, BP, abd Value Prop) for you. Snag it here.

Transcript

This is Bridge the Gap powered by Revenue Reimagined, the podcast where we dive into all things revenue. Each episode, we bring you the top founders and go-to-market leaders to challenge how you think about growth and help you bridge your biggest go-to-market gaps. I'm Adam Jay. And I'm Dale Zwizinski. 

As always, thanks for hanging with us. There's a million ways you can be spending your time and we're grateful for you choosing to spend it with us. Be sure to check out our newsletter if you want the show notes and tactical advice on how to bridge your GTM Gaps. Let's get to it. 

Welcome back to another episode of the Bridge the Gap podcast powered by Revenue Reimagined. Today's guest is Elio Nartiso, the co-founder and CEO of Scale Sack, where he's leading a team building what he calls an autonomous revenue engine. It's a system that doesn't just automate GTM work, it actually eliminates the need for most of it altogether. He's run GTM for startups at AWS, sold companies, advised high-growth teams, and now he's focused on killing the manual work tax that slows revenue teams down. This isn't going to be a fluff episode. We're going to talk rev ops, AI, what GTM could look like if we actually got out of our own damn way. Elio, thanks for joining the show. 

Thank you, Adam. Great intro. Nice to meet you both and happy to be here. 

Awesome. Elio, thanks for joining. I love that the first part of the intro that I really sparked my interest was the manual work tax and what that is. You've called the current state of rev ops a manual work tax tax. What does that look like in most companies today? 

I think it applies not just to rev ops, but to many, many go-to market teams. The inspiration for this was born out of my time at AWS, which I joined after a couple of startups, companies that I created. Before joining AWS, I thought, okay, I'm going to join one of the best companies in the world. 

They're going to have everything figured out, every system, every tool is going to work perfectly and data will flow magically. Then it wasn't the case. We had the same problems. Obviously, there were certain things that they do and they were doing extremely well. But also, a lot of the things that I had experienced in my own companies were similar. For instance, I run, as Adam said, a program to support the go-to market for middle-age startups. They were customers of AWS and we were supporting them in their go-to market. In order to decide which startups would deserve more support, would deserve more resources, more AWS credits, marketing, etc., we basically had to prioritize. 

To prioritize, we had to look at a huge list of startups and decide based on a number of criteria which were worthy of our attention and support. I tried to do this on Salesforce, which is AWS CRM. The data in the CRM was terrible and it was outdated. 

Yes, I tell you, unique. Basically, what I started doing is a spreadsheet. I put together a spreadsheet manually with some VAPIR connectors to CratchBase and to LinkedIn and to ZoomInfo in order to map the market and understand what startups would be worthy of that support and additional marketing and sales or co-selling support by AWS. The list became huge. Tens of thousands of companies, I mean, imagine startups that are created every year and then prioritize them and try to make sense of this data. It became a huge mess. 

That was the point where for me, the idea that this is not just me, my startup, or growing companies, but this is also me at AWS, one of the best companies in the world, then this must be true for a lot of other people. It's not just RevOps. It's like reps that need to do research on their prospects or marketing teams that need to make sense of leads and signups and decide which one should be sent to sales because if you send them all to sales, like unengraged or unprioritized, sales is not going to work on them. 

Or RevOps teams who are tasked with making sense of all of this data and build sort of like a foundational model. That's what the manual work tax is. It's like the time that I had to spend building that spreadsheet, the time that the rep needs to spend researching stuff on sales navigator, which is not the easiest tool to use and you can spend like hours. 

Yeah, this is easy. 

It's a Microsoft product, y'all. 

Down the rabbit hole. It's funny you say this, Leo, because I worked at Oracle and I had that same Aha experience moment where it's like things should be working much more efficiently or effectively. And they own their own CRM and they own it. It's the same thing. Why haven't all the RevOps tools actually fixed this before this problem? Shouldn't have this already been fixed? 

100%. And I think that the CRM industrial complex should have fixed it because we call CRMs, people call the CRM like the source of truth. But if the source of truth is full of outdated or bad data, then what source of truth does that represent? So I do think that the CRM should have solved this. 

They haven't. The problem is complex. And I think that AI presents both the catalyst for understanding that the old model where like, you laugh when I said, oh, the data in the CRM was bad. This is true for every company. 

And until very recently, there isn't much that you could do about it. So now with AI, your competitor will start getting better at data in their CRM and will start prioritizing their sales and marketing efforts better. And it will become a competitive advantage. So in the age of AI, data will impact outcomes, this proportion. So if your data is bad, then like, even if you feed it to the best AI, the results are going to be bad. And so AI represents a catalyst for change. But also the reason why we can now work on that data because the scale stack platform would not have been possible like four years ago. Yes, we could have done like, you know, automation and workflows and all of that. But without the agent components, I mean, we have agents that go into the CRM. 

Decide like, what data source is best for any data point that decides, you know, like when they have enough confidence level about that data point and when they need to release other agents to do research to complement and improve the confidence level about that data point. So all of this was not possible until very recently. And now it is. And AI represents, as I said, also the catalyst for change. I love that. 

So it is a big catalyst for change. But when you look at specifically like why the CRM haven't fixed this and where AI is or isn't being used, is this more of a tech problem or is this more of a leadership problem? 

So I've done like a number of like round tables with CROs over the past like six months. And I have to say that it is not always clear to the CROs what the role of RevOps should be. RevOps is really important. And it's like, you know, the core of systems and processes and technologies, but also it's a very strategic component of the go-to-market machinery because it owns the data model. And so I've heard CROs like, you know, talk about their RevOps as like systems or processes or like handling tickets. 

And that's the wrong attitude. You want RevOps teams to be strategic. You want to rely on them for like the data that will be used to prioritize sales and marketing efforts. So like CROs know that they have to distribute an equitable book of business across the sale. 

Right? So they know that and they do that. But they do it like very manually. 

They do it like once a year. Like everybody is rushing to like say, okay, how do we distribute the account? In order to do it well, you should rely on a RevOps team that is empowered with the tools and systems and the data to say, okay, this is what this account is worth. And so how the way I patch the territories of the account or distribute the book depends on what is the value of each account. 

And so I can distribute that equitably. And so I think that there is a leadership problem in that sense that sometimes there is like a misconception of what like the RevOps role is. But then there is also a technology gap. I think, you know, until very recently, essentially there was either data, plenty of data out there, zoom in for Crunchbase, LinkedIn, you know. But the key is how do I align that data to my ideal customer profile and to my go-to-market strategy, which will change, you know, for each of us, right? 

A hundred percent. And that ties exactly into where I want to take this for a moment. So we talk a lot when it comes to AI and go-to-market about automation versus orchestration. And I think a lot of folks just think, oh, we're going to automate it. We're going to automate it. 

And we say all the time, I think Dale, you posted about it this week, if not two or three times, automating, forgive me, shit is just going to get you more shit, right? If your ICT is wrong and you automate outreach, you're reaching out to the wrong people. If your buyer person is wrong, it's the wrong people. 

If the RevOps data is wrong, you're automating bad data. Where do you come in when you look at what you're building specifically? Where do you automate versus where do you orchestrate? 

So we believe that the orchestration should be automated. Tell me more. I think that the instinct in the go-to-market space has been, oh, let's automate like sending emails. Let's automate, let's say, the rush to create like AISDRs. 

So to automate a lot of like the last mile elements. And frankly, a lot of the things that humans should be doing, like a good email or like a good outreach or a good engagement should be, and it is, like what humans know how to do. And instead, we haven't devoted enough attention on like automating all of that, like frankly, boring work that goes into cleaning your CRM data, removing duplicated accounts or leads or like building better hierarchies between like accounts or assigning contacts to the right accounts and then calculating the time in each account or like de-anonymizing leads, et cetera, et cetera, et cetera. 

All of that frankly is extremely time consuming, repetitive, boring work that I don't really want people to do. And so to me, like if we can achieve, and that's why we call Scale Stack an autonomous revenue engine, because we want to automate all of that, which is an orchestration. And so we have agents that compose and then run workflows to achieve like that cleaning, that enrichment, that prioritization of the data across the CRM. 

Are there tasks that should never, ever, ever require human intervention at all? 

I mean, a lot of this stuff I think that can be and should be delegated to AI. There was an artist, I forget her name unfortunately, recently, like a few months ago, like became viral because she said, I want AI to do my laundry, not to write my poetry and stuff. And that's sort of true, no? So they're like, if I push onto AI all of the stuff that people frankly don't want to do and find boring, I think that that's a good place to accelerate a lot of the stuff and relieve people like rebels. If a rebel team needs to spend like three months to clean and deduce the data, their mental power... 

Going through this with a client right now is driving me nuts. Right. 

And so at the end of that process, you're not going to have like the same energy that you had when you started. And so maybe to the most strategic last mile component, you're going to devote less energy. Instead, what we aim and what our customers achieve is that they input the business logic and the criteria that they want to achieve or the use cases that they need to solve. We absorb all of that complexity with the platform. And then they, meaning the customers, monitor the outcomes. Is the data hygiene increased? 

We have like a good hierarchy. We removed all of the accounts that are duplicates or like if we reassigned contacts to the right account and then clean all of the contacts of like bad data and updated and added like new data only when the foundation of data model was done right. So we think that all of this can be done by agents. And now the platform is heavily run by agents but supported still by like humans, like ops people that like run the workflow and make sure that everything is running smoothly. I see a future like, you know, around the corner, literally where like our workflows will be composed and run autonomously by agents. 

Awesome. Is there a place to make sure automation doesn't create too much noise? Are we generating too many noise pieces? And along with that, as you were just saying, people still need to like strategically think on the input to put into these systems because I think that's where people are like, I'm just going to download something and we're just going to run it. They haven't done the strategic thinking part of it. But maybe they combine together where you may be getting noise if you don't do the upfront work. 

So I think that until now the instinct has always been, oh, our CRM data is terrible. And so let me add more data, which adds noise. Let me create a new list. Let me add like new prospect. Let me add like new companies. Let me add more data and signals and intent and all of that stuff. 

And that creates a lot of noise. Our stance is that like, and mine, you know, like we work with larger go-to-market teams. We work with companies that have at least like 15, 20 reps an app, companies that have a few years in market already way beyond like product market fit. 

So they have like already an established presence and go-to-market in the market. At that stage, if you don't figure out like the prior data first, just adding more data will add more noise in our opinion. And so first figure out the data model, like figure out like what worked in the past and how and what are the best customers and how to prioritize the efforts of the sales and marketing teams going forward. 

But then once let's say you've cleaned your data and built that data model, I think that we believe, you know, like strongly that like in the new world, the spray and play is gone. And so the best teams are those ones that really know how to prioritize. And so to prioritize for larger companies, you need to rely on data. And so how do I equip the sales and marketing teams with great data to tell them these are the accounts that you should focus on today, this week, this month, which will dynamically change is not something that you only do once a year during the sales, you know, annual sales planning, but will dynamically update itself over the course of the year, depending also on your changing like marketing strategies or go-to-market like strategies and all of that. 

And so it's all about prioritizing. For instance, we just deployed like a fantastic super like complex, a gente-work flow for one of our customers, MongoDB, and they have a free tier product called Atlas. Atlas is super popular. And so they let anybody without a credit card register because like they have used it historically as a pipeline. But the way they have used it is that like there are hundreds of thousands of people that register on Atlas, developers, they would not really act on that data until like somebody would raise their hand and say, hey, I want to talk to SIPs. But what we have done for them is deploying like a workflow that enables them to first filter and de-anonymize profiles at scale, leveraging data from multiple data sources, internal, external, third-party data, agentic research that is done within the workflow, and only a very small subset of these signups are then like fully enriched with a lot of insights and signals around like the company, the person, if we find value in those signups at least. And then this becomes a subset that sales can work on or marketing and sales can collaborate on or they can do like social media campaigns or ABM campaigns and all of that. And so it's not sending an email to the hundreds of thousands of like Atlas signups, but only to those for which like you have a high degree of confidence that could be an interest and why. 

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Yeah, that's I really like that that that flow because there is places where people are getting too much data and they don't know how to act on the data. So like getting really specific. A lot of places and it goes right back to what you were talking about earlier is like the structure and the real thinking up front because you have to do the thinking in the strategy up front before you build the system or else you're not going to get the day you want to. And people like this AI stuff doesn't work or it's not working the way out. You know, I feel the stuff on YouTube, whatever it is. 

So it's very interesting. Let's let's transition a little bit. You've worked out a bunch of startup and you've worked at AWS. So you've worked in many different places. When GTM isn't working, what's usually behind this? Like what's usually broken behind the scenes? 

I mean like there is a wide range of options but I do think I mean first of all it always starts with leadership for sure and that's why I think that if we talk about like B2B startups for instance why do we say like oh the founder should be like you know the key seller until at least like a million dollar in ARR. So I think that that's for many reasons but one reason is that like you know the leadership which is for a startup is like the founder needs to develop like that knowledge about the market and the customers and like include that knowledge in motions that become more and more established. So I take this example because like I do think it's always like from leadership like you know so if like a founder doesn't do a lot of sales or like delegates this too quickly like probably things are not going to go and work out or if in a larger company the leadership is not like setting like a goal or like you know like a vision for what they want to accomplish probably there is not going to work out. I mean at Amazon what I appreciated for instance is like one of the great things about Amazon is that like a writing culture. Amazon doesn't move unless like for any product launch or new program or initiative unless you write a doc. That doesn't need to be a PowerPoint it's actually a long form like typically six-page or like war document where like people go crazy in the sense that like you know they debate a lot around that document but that generates a lot of alignment about what to do and I think that that's very important especially for larger teams because you always have to have like you know a North Star and I think that this changes every year so like leadership needs to lead by example number one example of the founder and then like they need to set like a clear like vision and mission and goal which we will change we'll change during the year also but like for sure like every year but it needs to be clear understood and hopefully simple you cannot have like a myriad of goals you need to have like probably one or two goals that are the North Star for the action of all of the team and then I do think it's all about like the data I really believe that like especially a scale so for sure a scale but like in any go-to-market situation like once you have good leadership once you have like a good vision and goal like it's all about the data and knowledge about like who to target in order to make everyone very efficient and so like do we have for marketing teams do we have like a clear understanding of what's the ICP and what are the buyer I mean many times companies have like a wide range of interpretations and lack of clarity and maybe you know maybe somebody in the go-to-market team knows but the product team doesn't and so there is a lot of misalignment that generates 

problems and it hasn't been changed for two years right so it's like they're working off old data like yeah so so the follow-up on that question and I seem to be asking this every time how often should your RevOps your go-to-market team whoever it is be pressure testing those what we're calling GTM foundations which is ICP buying persona value proposition like what's that pressure test time frame like 

I think that with AI for instance we have been implemented now like you know very simple workflows that anybody can do so you don't need to buy skills for this but like we record every sales call we record every customer call and then we have like simple workflows to get the transcript analyze them and like you know what are the pain points what are like things that resonated what are the things that didn't what are and so this constant learning is so important and so for sure for like a company like us like you know let's say C to series A stage is like essential because every three six months we'll need to rethink this and make sure that we are like pressure testing ourselves that we're focusing on the right companies and people etc but I would say for anybody is like you have to listen to your customers and like we have so much data now that it's easy to be processed with AI that not to use that data is a fit and I'm learning I mean we just launch we launched our website recently a lot of the content of the website is the byproduct of like spending a lot of time on customer calls we have recorded hundreds of customer calls distilled them into what is that they said what is that is important what are the pain points and then take them and transform them into like some of the copy of the website and so I think that that's basically something that you have to do all the time but maybe in a more structured way like you know every quarter I love it 

I agree so many people don't like we talked to so many people who like we have a client now no joke they don't record any of their calls and to me like whether you're using that to create your website or like it is a sin in go-to-market to not be recording your calls and understanding what works what doesn't what are your customers asking for what is what's the product feedback like I literally I don't want to say nothing shocks me but like holy shit did this one shock like wait a minute you've been in business this long you have 10 reps and you don't record your sales calls what 

there are industries like finance or healthcare we're like that is yeah no not that yeah but if it's not then like it is like problematic I mean but I find this even in consumer I mean like you know when like they send you an email and you reply and like it do not reply I find that like so crazy like so those same companies that send those emails that have do not reply spend millions and millions of dollars in like you know marketing campaigns to target and then when a customer wants to reply to them oh this inbox doesn't like get you know doesn't get like analyzed like crazy too you want to gather every customer input and so if they want to reply to the email let them don't say do not reply which is crazy 

you common sense is only common to those who have it um so AI in your view and in our view as well isn't a feature I think a lot of people right now are thinking AI is a feature and I think we all agree that AI is much more of a foundation as we're halfway through 25 going into 26 it's not something that you're bolting on top of your workflow you're actually building from AI as a core what's different in the building approach in that sense and you know as you all are building like where does it where are you finding AI breaks most in that GTM stack that is requiring more effort to really get it right versus just like plug and play 

I don't know I haven't heard like you know like oh it's a feature I've heard like I think it's a systemic change back to the way we work and I I believe that like a hundred percent I think that like it will completely transform the way people work and it is already I started my career in mobile technology like in the early 2000 I I'm Italian originally so I started in Europe in Europe we had mobile phones before the US this is the only technology like recent technology that like Europeans got like earlier then you know the iPhone came in and like you know basically they own like Nokia and Ericsson all of those European companies that have been formed before that but it reminds me of that so like the sea change that there was when mobile phones were introduced but at a much faster clip and like you know instead of replacing like some communication methodologies that were used before like landlines or like fax or other stuff it's replacing and completely reimagining the way people work and like process data and so many more things so I think it's an incredible opportunity it has like a lot of risks obviously but the speed is what's impressing me I mean our platform you know let's talk about my little world that I know well our platform has made like an incredible progress over the past six months and every week there is something else that we couldn't do like a few weeks before and oh this is now like finally we can do this or we can like you know automate that or we can like you know increase the speed or even reduce the cost because also there's so much competition between all of these big platforms now much earlier than say the competition that started to come from like AWS versus Microsoft versus Google now like all of this platform are competing head to head prices are going down speed are increasing capabilities are like enormously advancing so I think it's gonna radically change everything and very very fast so the recommendation is that any go-to-market teams embraces this change because otherwise you're competitive as well and I do think like that RevOps is an interesting area I see many companies come into us and say or like RevOps is going to be the playground for a lot of AI initiatives because like you know it's central to that foundational data model it's central to go-to-market revenues and so like we want to start from there rather than say customer service or rather than say I don't know finance and all of that 

yeah I was um when I was at the gym this morning Dale will be shocked that I said that but when I was the gym this morning on Squawk Box the CEO of Lattice was talking and it was all about the effect that AI is going to have on jobs is not so much again eliminating but like if you are not embracing AI if you are not using AI if you are not deeply learning AI for everyone who sits at night and just scrolls through Instagram on on bullshit like take that time and like upskill yourself you are going to be at such a competitive disadvantage forget six 12 months from now I would argue three months from now that you're going to have major major problems yeah sorry Dale I cut you 

off no no and I'm curious as we as we progress like where's where's GTM headed next so fast forward a couple of years you know what's one part of GTM that's going to be completely different than it today besides you know besides what you're doing within Scale Stack and RevOps like where's another place inside of the GTM playbook that's going to be completely different 

well I think that we are seeing it um at the startup level like the old playbook or go to market of I don't know like the white papers or like the you know marketing campaigns or like search you know paid search and all of that is being like a quickly change for the CEO is the chief marketeer and and some examples came from the larger companies think about like Mark Zuckerberg he's the chief marketeer of Meta and and you know it's not that obvious it wasn't like that like you know 10 20 years ago right but like that we have this like CEO they are chief marketeers and so they need to embody and represent like the company the brand and the message and then in-person events are super important and like humans will keep buying from humans I think the best will stay the same and we just need to become better at like optimizing those experiences I think that there's going to be lots of interesting stuff around like events the events industry that are going to happen over the next couple of years because people are craving for like through like connection and better understanding and you know understanding the landscape understanding what's like noise what's important and who are like people from whom I want to buy and then like I think that we're seeing and this is already probably very advanced that like a lot of companies B2B SaaS are like content machines now and content is key in like you know that's why we're doing podcasts that's why we are like you know ourselves like we have our own podcast we do like clips and we do interviews and we do like roundtables and all of this stuff because like if humans keep exchanging this knowledge like you know we'll continue to represent what's like great about humans which is this like connections with other humans that generates ideas and then like and can get implemented maybe by AI you know that's probably that's how I see it like you know for us like I wasn't the chief marketeer of my last startup I was actually pretty quiet now do we have like CEOs building in public yeah and that's interesting it's an interesting trend no so like you know I don't think it's appropriate for like a company like Scale Stack that is like more enterprise focused I don't want to like you know clean wash my dirty laundry to my enterprise customers but I mean for other companies it's very appropriate and it's very interesting and it generates like a lot of attention and interest because there is a lot of noise and so how do you raise yourself about the noise which is the goal of go-to-market know how do you make sure that you identify people that will uh understand your message and feel that it resonates with them and they are interested in knowing more 

yeah I I agree with you 100% I don't know how I feel about the whole building in public thing it's not I get it but I regardless of you know whether it's enterprise or SMV I'm not a big fan of airing my dirty laundry to anyone um but that's just me um and I think I'm pretty open on like things like LinkedIn but like they my customers don't need to hear when Dale and I you know have a massive disagreement about something and like it doesn't matter when one of the AI agents that we're building broke for one of our customers and how we had a scramble to fix it like no one needs to know that shit um all they need to know is it works and we're doing great um all right let's go into some rapid fire as we wrap this up um I have some we both have some questions that hopefully we'll spur the brain 10 words or less uh the goal is to get through as many as we can what is one gcm tool that you think is massively overrated clay you're not the first second or even tenth person who's told me that 

yep yep no I let let so let me let's um clay we complete we clay and clay I need to take clay because without clay I think the need for scale stack would not have been understood I think that like last year we were fundraising clay announced like they're a huge round and you know some investors came to us and said oh like but then the clay raised actually what it generated is more curiosity around what we were doing because often we say oh we are clay for the enterprise and so I actually like them thank them for what they've done and they are actually based in New York like me so but on the other end I think that like you cannot be everything for everyone is not like it's a great tool for like startups and smaller companies I think is not the best tool for many other companies um and then like there's strategy of like uh increasing the awareness through like the agencies and the promoters and the influencers paid or not you know like it's been a little bit too much um frankly and like the advantages of the product are clear but they are not everywhere um yeah and so I think it is a little bit over hot right now 

yep um what's one GTM test that human should be doing in in 2025 

cleaning the duplicates in your CRM I 

love that that one came up what's uh what's one piece of SAF sales advice you just wish would friggin die 

one piece of SAF advice 

SAF sales advice that you just wish people would stop throwing out there 

I don't know I'm seeing a lot of uh stuff about pricing and like you know it seemed that for a long time uh like SAF pricing was very stable like that like a per seat and then like you know some additional features and like you know discounted pricing if you commit for like X amount of time I think that like all of that is like being thrown out of the window right now and I see a lot of people now like um suggesting lots of different pricing methodologies the reality is that like you know we don't know yet we it's very hard like uh to understand like where we will land if we will land to the same place as like oh it's a SAS price per seat and that's it you know I don't think we will land that way I see like you know we are pricing based on workflow plus like uh usage um but like evolving quickly I think around outcomes so like we'll see where we land so a lot of people are like uh sending advice around the pricing of AI I don't think that we know yes 

let's wrap up with a uh a bit of a lighter question what's your dream vacation destination 

yeah I love this question he doesn't travel anywhere really 

he doesn't he doesn't Adam doesn't know me I just don't travel now I used to travel a lot more yeah that's what I love when you have teenagers in college they'll learn that yeah 

I love traveling I'm from Italy's I'm lucky that I get to go to Italy like a couple of times a year um and I've been in many many countries but my one of the the best places I've been recently is St. Lucia I think I'll be back you know soon to St. Lucia um and um so it was it's an incredible magical place and like beautiful uh sea and water and like climate and all of that so I'll be back 

nice it is a gorgeous place I'm sensing a scale stack meeting in St. Lucia yeah an upside in St. Lucia yes Elio thank you so much for joining the show where can people find you where can people go learn more about scale stack 

it's uh scale stack dot ai actually super proud we just released a new website which I spent like three months obsessing about so please go see then and and check it out and then my name is Elio and I've chosen a rci itself and thank you for having me 

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