---
title: "AI Is Breaking Sales — Here's How to Fix It"
episode: 24
podcast: "The LeanScale Podcast"
publisher: "LeanScale"
guest: "Mustafa Saeed"
guest_title: "Co-Founder & CEO, Luella"
date_published: 2025-09-18
date_modified: 2026-07-22
duration: 00:25:07
word_count: 4447
topics: ["ai-in-gtm", "outbound-sales", "revenue-operations", "brand-positioning", "gtm-strategy"]
canonical_url: https://leanscale-knowledge-hub.netlify.app/podcast/mustafa-saeed-ai-breaking-sales/
source: "LeanScale Podcast Knowledge Hub — https://leanscale-knowledge-hub.netlify.app"
license: "Free to quote and cite with attribution to The LeanScale Podcast."
---

# AI Is Breaking Sales — Here's How to Fix It — Full Transcript

> Episode 24 of The LeanScale Podcast, with Mustafa Saeed.
> Published September 18, 2025 · 00:25:07 · 4,447 words.
> Machine-transcribed and **not diarized** — speaker attribution is inferred, so verify
> attribution against the audio before quoting a specific person.
> Structured breakdown: https://leanscale-knowledge-hub.netlify.app/podcast/mustafa-saeed-ai-breaking-sales/

## 00:00 — Intro: Mustafa Saeed and Luella

**[0:00]** (logo whooshing) - Today we have Mustafa Saeed, co-founder and CEO of Luella. Mustafa, really excited for what you're gonna show today because I think the new world of AI has created so many opportunities and at the same time, so many new challenges and so many new problems that I don't think a lot of people are even aware of. So I would love if you could lay the context of what the new AI world has created and some of the problems that come along with it and how you guys are solving it at Luella. - Yeah, of course. Anthony, thank you so much for having me on the podcast and yeah, a big reason for why we're building in this space

## 00:42 — The AI consequences reshaping GTM

**[0:42]** is because of a lot of the recent consequences of AI and automation that we're now seeing. My founding team and I really came together because of our shared background as former agency founders, go-to-market leaders, security engineers, and we all saw a lot of the same challenges. We all saw a lot of new AI sales tools entering the market, a lot of AI SDRs that were making it easier than ever to spam very large volumes of emails and just content in general without consequences or without limits and we started to see very early signs of larger policy changes that are happening in this industry. Google and Microsoft making very aggressive changes

## 01:20 — LinkedIn bans Apollo overnight

**[1:20]** to their spam filters, for example, to combat abuses of AI and automation and now LinkedIn, like, Anthony, did you see what happened with LinkedIn and Apollo? - I did, I did. And no warning, basically overnight and so many companies had to immediately shift strategy and shift gears to accommodate that. But I think-- - Exactly. - You probably know more of the details of it than I do and would love to share how that's a good example of how some of these things can change so quickly. - Yeah, so Apollo, this unicorn, this billion dollar company, their company page was removed from LinkedIn. If you go to LinkedIn right now, type in Apollo.io,

**[1:58]** it takes you to a dead page and we saw the same thing happen with Seamless, with Ava Boost for so many of these companies that have been really going aggressive when it comes to web scraping, especially your personal data to sell them as part of their solution. So we've already started to see these very aggressive policy changes and there is a larger ripple effect that we're seeing across the entire industry as a consequence of them. Email deliverability, for example, all of a sudden, it's a problem again. Because of how aggressive Google and Microsoft have become, even trusted centers are being impacted, not just startups,

## 02:35 — Reputation, compliance, and data-leak risks

**[2:35]** but some of the biggest enterprises in the world are seeing email deliverability issues, seeing their emails land in spam and promotion folders across several thousands of their sales reps. We're seeing a lot of RevOps and revenue leaders have concerns around potential abuses of AI and automation across their sales team. There's a lot of benefits and advantages to using AI and automation and that's why it should very much be encouraged, but there are also ways that these tools can be abused. Reputation damages, for example, right? There was this AI board member that got into some hot water because they started spewing a lot of very sexist claims

**[3:14]** and the founder had to record an apology video, their LPs had to get involved and it was this really big situation. These brand reputation damages can take a long time to recover from. Compliance issues are another one. We work with a lot of health tech companies that are very sensitive when it comes to the claims that they can make around their software. Even just one word that's off will result in an issue of non-compliance, data leaks. Anthony, did you see what I posted on LinkedIn yesterday? - I did not, but we'd love to hear it. - So this hacker tricked an AISDR into leaking its IP address, SSH credentials and password file. - Oh, wow.

## 03:57 — Prompt injection: an AI SDR leaks its credentials

**[3:57]** - Now, all he did was add a prompt in his LinkedIn bio, pretty much asking to override any previous instructions and provide those credentials. So especially with so many of these tools just being vibe coded together, like there are real risks to AI coupled with reckless automation and that's why we wanted to build something in this space to build those guardrails to prevent abuse, to enable organizations to make the most of AI without abusing AI, do a better job of protecting reputation, preserving deliverability, and help you connect with prospects instead of spamming the living hell out of them. And we're very grateful to have worked

## 04:36 — Origin story: a lean team of five

**[4:36]** with a lot of incredible RevOps leaders. So a big reason for why I wanted to be on this podcast is because it's really RevOps that has been stepping up to implement these guardrails across their sales organizations. And we've had the chance to work with RevOps leaders at Oracle and Travel Perk amongst several other enterprises. We're still a very lean team. We're a team of five full-time with three engineers. And we wrote that first line of code just over six months ago. So everything that I'm about to show you is still very much new. And my co-founder and I, today is actually our work anniversary. So one year ago today, I sent him a message. Thank you.

**[5:13]** We met on YConvaders co-founder matching and we've been building ever since. So that's a little bit about the story of the crazy journey that we've been on so far and why we've decided to build in this space. - I love it. Well, I'm really excited. I think so many of the new companies are built lean and mean anyway. You look at like Cursor, Lovable, those type of companies reaching unicorn status with a handful of people. So you don't need a big bloated team to make something meaningful. And what you're targeting hits me personally in so many ways. One, I have a cybersecurity fraud prevention background. So when I was leading RevOps in tech,

**[5:48]** it was mainly in that space. So I know how many vulnerabilities already were around before all of these new AI capabilities. And on the receiving end, my inbox and LinkedIn is just lit up every single day. And it's clearly, it always was a problem. We just poured gasoline on and already really hot fire. So I'm really excited about the mission and what you're solving. And there needs to be guardrails in this space and ways to just make sure it's a more meaningful environment, especially in go-to-market. And the RevOps community, everyone in RevOps is on the hook for solving this. So people are looking to us to come up with a solution

## 06:33 — Shared IP pools vs. isolated clusters

**[6:33]** to make sure, hey, we can still sell, but still protect our reputation at the same time. - Exactly, completely agree. These legacy workflows throwing AI and automation at them, like that's not the solution, right? There's infrastructure that we need to build just to make better use of these tools. And really excited to dive into that. Anthony, should I share my screen? - Yeah, let's do it. - So it really all starts with the infrastructure that we're actually sending from. So Anthony, if I was to say shared IP pools, do you know what that is? - I'm not sure of it. Maybe I should be, but I'm not. So these are massive shared servers

**[7:11]** with several thousands of unvetted senders in them. And in these servers, you're gonna have both good actors that are running called app-bound tastefully and ethically, but also those bad actors that don't give a shit, that are spraying and praying. And when you're sending outreach out of the majority of these legacy outreach tools, you are unfortunately using these shared servers, and that exposes even the most trusted senders to spammers and grifters. So that is a larger piece that hurts your sender reputation and makes you more likely to land in spam because of it. So we, instead of these really big servers, Anthony, we will create your own mini server.

**[7:49]** And we call these mini servers clusters, and this is exactly what they look like. This is Evan's cluster over here. This is my cluster. Each of these clusters has its own IP address. Just so, if one sales rep goes rogue and starts pushing a lot of BS, it doesn't contaminate your entire infrastructure. It is isolated to the cluster that we've created. So this is a larger way that we're isolating risk across your sales organization. And if you click into any cluster, you'll be able to see its corresponding metrics. Another larger challenge that we're seeing in this industry is transparency. A lot of organizations don't know what percentage

## 08:27 — Placement tests over vanity deliverability scores

**[8:27]** of their outreach are actually landing in the primary inbox versus spam or promotions folders. The reason for why is because Google and Microsoft only give you self-reported spam metrics, which is a small fraction of the data that they actually have. And most outreach tools will give you like a deliverability score, which is a made up metric. They have full control over what goes into that deliverability score, and it's more often than not inflated. So we, to bring back that essential visibility for your team, are running placement tests. Anthony, do you know what that is? - I'm not sure, but I'm getting a great education today.

**[9:02]** So we on a regular basis are sending emails from your mailboxes to ours to see where they land. The inbox, the spam folder, the promotions folder, sometimes they don't get delivered at all. And this becomes the best indicator that we have through the overall health of your email infrastructure. Whenever there's a problem with your email infrastructure, we'll always see a spike in spam rates reflected over here. And Luella is using these data points to regularly diagnose your email infrastructure and surface alerts to both your team and ours. So let's say authentications break. Let's say Google and Microsoft make a change that they are more public about

**[9:36]** that does warrant action on yours. Let's say you have a sales rep that has gone rogue. Luella is constantly looking out for you and surfacing those notifications, not only from a deliverability perspective, but also to catch instances of abuse before it actually becomes a problem for your organization. - So by the way, I have seen that exact use case happen at every single company I've been at. An overzealous SDR, ripped 100,000 emails out of Zoom info, threw them out of their inbox right away. I mean, I've seen that exact thing happen every single time. - Yeah, it's crazy. Literally millions of sales reps all over the world.

## 10:15 — Simulating natural mailbox activity

**[10:15]** Like that's how they're operating. They pull these massive lists from stale databases and following static supers where on day one, you send a template in email. Day five, you send a template in. Day 10, you send a template in email. Like it's a very robotic way of doing business. And like we urgently need to move away from it because even without AI, it was super spammy, but now with AI and automation, it's made it 10 times worse. And in addition to the placement tests, we're also simulating natural mailbox activity. So when you're sending cold outreach, that isn't very natural, right? Because you're sending a larger number of emails,

**[10:50]** but with a much lower response rate. So Luella will simulate natural mailbox activity with real corporate mailboxes, just to do a better job of balancing your response rates, just to not trigger a red flag in the eyes of Google and Microsoft. So this is the piece that helps build trust with email service providers over time. And this is what we can also use if you have burnt mailboxes and domains and are looking to shift to an approach that is more compliant. - I love it. - So those are the range of things that we're doing on the deliverability side. We also do mailbox management. So Google, Outlook, Custom SMTP, we can manage the mailboxes

## 11:31 — The collapse of send-volume caps

**[11:31]** and the corresponding authentications to make sure everything is correct. You can also send emails out of Luella as well. So a few larger differentiators here. The first has to do with automation limits. So a lot of the changes that we are seeing from Google and Microsoft have to do with volume caps. Gone are the days of sending hundreds of emails every single day out of just one mailbox. Last year, we reduced our volume to 50 per mailbox per day. Today, we've reduced to 15 to 25 emails per mailbox per day. That is how aggressive Google and Microsoft have become. So Luella, unlike other platforms that will let you set whatever volume caps that you want,

**[12:14]** Luella is the one that controls your volume every single day just to maintain that compliance. Another guard that we've built has to do with how we're scaling that volume over time. It's really important that you're not going full guns blazing on day one and sending hundreds of thousands of emails. You really wanna make sure you're testing your messaging across a much smaller sample size before you do press your phone in the gas just to make sure you're providing value to the prospects that you are reaching out to. You're seeing positive reply rates. - I think this is one of the biggest mistakes, first-time founders,

## 12:52 — Sales is a quality game, not a volume game

**[12:52]** when you get your first A/E into a company that they make. They think, one, they think that their ICP and their messaging is blocked and loaded, and they just go nuts with the volume of communication. And I don't think people realize that you're doing more harm than good. You're hurting your brand. People will immediately start to associate your brand with someone that spams them. And then when you realize you iterate and you need to improve your messaging, you've kind of burned that bridge already. So I think people think sales is a volume game, and yes, in some ways, but really it's a quality game.

**[13:38]** And you don't really get an opportunity to get that quality unless you're doing it in the manner that you say. Small batches, iteration, testing, very thoughtful messaging, very personalized messaging, not just blasting 100,000 people. - Exactly, completely agree. And in order to be able to achieve this, we've also built a lot of the same algorithms as many of the traditional ad platforms. So Anthony, do you guys run Facebook ads or LinkedIn ads internally? - We do some LinkedIn ads. We actually do some YouTube ads as well. So we're a little familiar with it. - Yeah, so the way that LinkedIn ads work is you give them 10 different ads.

## 14:18 — Ad-platform message testing

**[14:18]** LinkedIn will test each and every one of those ads against a smaller subset of your audience. And only after LinkedIn sees customers are liking the ad, clicking on it, engaging with it, like showing actual value that's being delivered to the end user where LinkedIn will show the ads more and more and more and more and more people. The weather will do the exact same thing. So you may add 10 different message variations to a campaign and the weather will test each and every one across a much smaller sample of the context that you do have. And only after she sees positive replies where the weather will scale the version that is performing the best.

## 14:54 — Reinforcement learning as the optimization layer

**[14:54]** So you can't push volume in cold outreach. It's just very important that you are delivering value to those prospects. If your messaging isn't providing value, then you are spamming your users and you deserve to be in the spam folder. So that's why we've built those necessary limits just to prevent bad actors from spammer, people spamming our platform. Another piece has to do with reinforcement learning. Do you know what reinforcement learning is, Anthony? - Gonna learn another thing today. (both laugh) - So this is a branch of artificial intelligence. There are multiple different branches of artificial intelligence. LLMs are just one of them, right?

**[15:35]** LLMs are really just glorified copywriting machines. Reinforcement learning is another branch. This is the optimization layer. This allows us to look into the past, understand what has performed, what hasn't performed in order to better predict the future. So in order to help teams better improve their messaging over time, we're using reinforcement learning just to run a lot of mini experiments with your messaging to get a better understanding to the hooks, the lead magnets, the offers that did resonate and provide value, just so we are optimizing the best messaging with the prospects that you're targeting. So that guardrail makes sure

**[16:13]** that only the highest performing messaging that you have added to Luella gets shown to customers. And over time, once Luella does have enough data, she'll be able to recommend new message variations with new hooks, new angles, new lead magnets, new offers that are likely to outperform what you have tested in the past. So that is a piece that is very important to make sure you are improving your messaging, especially for those startups that you talked about that just haven't cracked it as of yet, right? They're sending small volumes and they're seeing low response rates. Luella will help you improve that messaging

**[16:50]** just so you can reach a point where you are providing a value and you can push more volume. - That's really unique. And normally a lot of RevOps teams will be behind the scenes crunching a bunch of numbers, trying to make sense of the data. And then, I mean, it's one thing to say, hey, this sequence is outperforming this one. It's another thing to really understand why and then replicate that or take components of that and create new sequences from that. So I think having an AI powered analytics function plus helping you create new messaging based on what's performing really well, like knowing the components of the why it's performing well

## 17:30 — Intent signals, integrations, and Octave

**[17:30]** is really important. - Yeah, and that's an area that the entire industry really needs to do a better job of because there are a lot of companies using intent signals and we're strong advocates for intent signals, but there are thousands of them, right? And like most platforms are only doing a good job of like unifying like a couple of dozen, like if not just like one or two. So like the entire industry has a lot more work to do when it comes to that messaging piece. And there's a reason for why we've built very developer friendly APIs just so we can integrate with like-minded partners. One company that we're in the process of building integration with is,

**[18:08]** do you know a company called Octave? - Yes, yeah. They've actually been on our podcast in the past. So great, great company and love the founder as well. - Yeah, we love what they're doing, what Julian and Zach are doing on their side. And they also come from a like very strong like anti-spam background. So like we really share the same mentality over the space and we confirmed our native integration with them just last Friday. So right now we have a really big integrations push. We have over 150 integrations on the roadmap and building developer friendly APIs. Like we're very strong believers in data interoperability, but Octave does a really good job

## 18:46 — Human oversight and why software isn't enough

**[18:46]** when it comes to aligning the right messaging with the right prospect. Phantom Buster is doing a really good job when it comes to intent data. Same with Clay, RB2B, Trigify. There's so many incredible companies in the space that we are looking to integrate with. And Anthony, the last piece that I'll mention is human oversight, right? There are a lot of AISDRs that are advocating for like a fully autonomous experience where these AI agents will just do everything and just hand you these opportunities on a silver platter. And like, not only are we very far away from that, like I don't believe that's where this industry is going.

**[19:24]** Like there are advantages to having AI operate independently, especially being able to ingest a much larger amount of data sources. Like that's something I can't do, right? A couple of hours looking at a spreadsheet, I'm tapping out, right? But there's things that like a human can do that an AI agent can't, right? I can show up in person and do a more meaningful job of building a relationship with a prospect. So we really need to blend the best of both worlds. So like, that's why especially for enterprises and mid market companies that we work with, making sure that we do have opportunities to bring the humans back in, right?

**[19:57]** There are certain pieces of copy that are generated by AI that a sales rep should see before it actually gets to a prospect. There are certain things that an admin on the account should see before it even gets to the sales rep in the first place. So human oversight is something that is very important that will help prevent a lot of the previous abuses that I mentioned, brand reputation damages, compliance issues, data leaks. Having humans in the loop is a larger protection against that. And that's also a big reason for why, like we're not just a software company, right? We have a lot of like human beings that are there to support as well.

**[20:32]** Like I regularly host workshops with sales teams to educate on the ethical boundaries of these technologies, how you should have your brand be represented in this AI native world. We'll also have like Slack hotlines where sales reps can put like all the challenges that they are seeing in the trenches when it comes to a security, a safety and deliverability perspective. But yeah, Anthony, that's the platform. - I love it. And I just want to comment on keeping a human in the loop. I think it's fine if you're selling really low ticket item, B2C context. There's not a lot that company is gonna change for that consumer.

## 21:13 — Why high-ticket B2B needs a human

**[21:13]** I think why it's different in B2B and hired ticket item, you need to know that you have somebody on the other side that is gonna advocate for you at the company. As an example, when we engage with tools that we would use internally, I wanna know that somebody there is gonna support the customer if we introduce them to them, 'cause that's really important to our business. So building that trust and knowing you have somebody on the other end who can make some decisions around the product experience you're getting, the way it's priced and packaged, like you do need some customization where AI can't make those decisions for you.

**[21:55]** And AI doesn't have the authority to do some things that you need a human on the other side to do. So I think some people don't, maybe they don't understand that aspect of sales, like, especially if you're getting into selling like $100,000 plus type of sales,

**[22:19]** that's an expectation from the customer side. So it's not just, yeah, I can get some product information really quickly, but is somebody gonna have my back if something goes wrong? - Yeah. - I need that assurance that somebody's on the hook for making this successful. - We just recently closed our first really big enterprise six figure a year deal. So we've gone through that, right? Like it was a like four to five months profit process of going back and forth. And there's like, I can list all the things. It's a very comprehensive of all the shit that like an AI agent just will not be able to do that like we needed to have like our team present

## 22:56 — Closing the first six-figure enterprise deal

**[22:56]** to get over the finish line. - I'm really impressed with where you started with Wella and thinking about trust and safety and thinking about how you can protect the reputation of the company, creating those individualized IP addresses, individualized servers. Also the approach that you've taken and how you've embedded AI into this process. One, making sure it's testing different messaging, it's optimizing that messaging, putting the right guard rails on, because I think you need to protect your customers from themselves. They will have a rogue SDR, they will have a rogue AE who comes in and just completely lights up their prospect base

## 23:35 — Protecting customers from themselves

**[23:35]** and then puts the entire company at risk. So I think the way you've integrated AI, the guard rails you put in place, having it with trust built in the foundation and where you're going in the future, I think is just really, really impressive. And I think it's gonna be highly, highly competitive. - Thank you so much. And yeah, like we're just getting started, right? First line of code over six months ago. And like in this industry, like these models are gonna keep improving, right? And we don't know what we don't know, right? There are gonna be more risks that like, we're not aware of today that do come up.

**[24:11]** So like I would encourage your audience as well to comment as to what are the concerns that they have in disseminating AI and automation across their sales team, because like, especially when you go vertical specific, right? When you speak to health tech companies, for example, or companies in education, there are unique challenges with every industry and like every conversation is a new learning for us as well. Mustafa, what's the best way for people to get in touch with you to start getting their hands on a product? - Yeah, if you go to luella.ai, our website, my Calendly link is on the website. Feel free to schedule some time, always happy to geek out.

## 24:50 — Where to reach Mustafa

**[24:50]** My name is Mustafa Saeed on LinkedIn as well. Feel free to connect. - Mustafa, thank you so much for being here today. Really pumped for what you're building and what you're doing and can't wait to see what you guys build next. - Thanks for having me on the pod. Thank you so much.