Selling Enterprise AI with Context, Adoption, and Measurable ROI with Daniel Simon

Summary

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Revenue Builders Podcast: "Selling Enterprise AI with Context, Adoption, and Measurable ROI"

Guest: Daniel Simon (Strategic Account Executive, Glean)
Hosts: John McMahon & John Kaplan
Date: June 18, 2026

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Episode Overview

This episode features Daniel Simon, Strategic Account Executive at Glean, discussing the evolution and challenges of selling complex enterprise AI solutions. The conversation explores how enterprise sellers can use AI to sharpen deal qualification, expose deal gaps, personalize outreach, and deliver measurable ROI—without losing the essential human skills that drive sales success. Daniel draws on his journey from traditional hardware sales at Dell EMC to SaaS security at Lacework, and now, leading-edge AI at Glean. Key topics include outcome-based selling, the importance of context and adoption in AI, best practices for prospecting, and why AI will amplify the gap between average and elite sellers.

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Key Discussion Points & Insights

Daniel Simon’s Career Journey: Storage to Security to AI

• Early Career (EMC/Dell):
  • Focused on selling hardware (storage refresh cycles).
  • Sales motion was transactional, with clear buyers and value props.
• Pivot to Lacework (Cloud Security):
  • Moved from transactional selling to selling business outcomes—driving revenue, reducing risk, and cutting costs.
  • Required developing new skills: multi-threading, mapping organizations, and qualifying rigorously with frameworks like MEDDIC/MEDPICC.
  • “If you're not talking about the business outcomes and the thing that the CEO, the CFO care about, you're really going to be doing small deals.” (Dan Simon, 05:27)
• Current Role at Glean (Enterprise AI):
  • Applies outcome-driven and multi-threaded approaches to enterprise AI, emphasizing context and measurable ROI.

Evolving Sales Skills for Enterprise SaaS & AI

• From "Speeds and Feeds" to "Outcomes":
  • Shifting focus from technical features to how offerings deliver quantifiable business value.
• Multi-threading:
  • Essential for complex sales—building a groundswell across IT, business users, and executives.
  • “Multi-threading is non-negotiable today. If you tell me you have one champion selling Glean, you ain’t gonna make it.” (John Kaplan, 12:20)
• Qualification (MEDPICC/Force Management):
  • High qualification rigor is more critical than ever, given the complexity of buyers and the proliferation of AI tools.
  • Tools like Glean and AI agents can accelerate and automate deal inspection and action planning.

How AI Transforms Selling

• Deal Qualification and Gaps:
  • Automation and AI agents (e.g., a “John McMahon Agent” in Glean) allow reps to assess deal health, identify gaps, and generate recommended actions rapidly.
  • “Now I can just say, ‘Where are we at in Opportunity X? Give me a score in MEDPIC. What are two or three actions to close gaps in 48 hours?’” (Dan Simon, 07:56)
• Personalized Outreach & Research:
  • Leveraging AI to quickly research a prospect’s business, craft tailored points of view, and scale value delivery.
  • Dan’s outreach: “Hey, I know you’re building an AI platform… Here’s how Glean specifically helped another customer… Would love a couple minutes to share.” (48:28)
• AI as a Double-edged Sword:
  • AI will make great sellers better but amplify "slop" and laziness in mediocre sellers.
  • “All this AI is going to make lazy sellers worse and great sellers better. Don’t stop learning the human fundamentals of sales.” (John Kaplan, 58:51)

The Critical Role of Context in Enterprise AI

• The “AI Slop” Problem:
  • Enterprises are buying multiple point AI solutions (Copilot, ChatGPT, Claude), resulting in disconnected systems and inconsistent experiences.
  • Context (role-specific, permission-based, workflow-aware) is the differentiator for effective enterprise AI.
  • “If you don’t rebuild the context engine, you’re going to have a really tough time finding the most accurate answer.” (Dan Simon, 28:20)
• Glean’s Value Proposition:
  • Glean’s context engine unifies data from multiple apps, delivers accurate, permission-aware results, and enables rapid, secure agent creation.
  • Analogy: “Casting a net might catch everything; Glean is like having a fish finder with the right lure for the exact fish you want.” (Dan Simon, 17:48)

Making ROI & Adoption Measurable

• Proof Points & Business Metrics:
  • Focused on quantifying specific use cases for multiple stakeholders (e.g., product, finance, HR).
  • Example: Quantified time savings and calculated $7–10M business loss from status quo in a large e-commerce deal; Glean’s ROI = 50–100x. (31:38)
• Consumption-based Pricing:
  • Shift to usage models—tokens and consumption directly linked to value.
  • “The more they use, the more value they get, the more they consume—it’s up to us to drive their success.” (Dan Simon, 42:57)

Security & Compliance

• Integrated Security as a Differentiator:
  • Glean Protect scans for sensitive content, enforces permissions, and allows custom rules.
  • Security concerns are key, especially as companies realize the risk of exposing internal data in broad AI models.

Prospecting in the AI Era

• No More "True" Cold Calls:
  • AI enables “warm” outreach—sellers have relevant, tailored insights for every call.
  • “Anyone picking up the phone right now isn't really cold calling—they’re way more effective because AI research stacks the deck.” (John Kaplan, 47:10)
• Best Channel Remains Cold Calling:
  • As emails and LinkedIn messages become saturated and filtered, phone remains under-utilized but impactful.
  • “The number one way to get meetings still is cold call. People are stuck optimizing written outreach, but picking up the phone works.” (Dan Simon, 46:44)
• Avoid "Half-Swing" Outreach:
  • Generic, surface-level personalization (“I listened to your podcast...”) without a value tie-in stands out as lazy selling.
  • “You did a half swing… It’s almost insulting.” (John Kaplan, 49:20)

Enterprise AI Adoption & Change Management

• Agent Sprawl & User Adoption:
  • Proliferation of AI agents can become overwhelming—need management layer and visibility into which agents drive value.
  • Real adoption happens when multiple stakeholders would “scream” if the tool were turned off.

Human Skills Matter More Than Ever

• Face-to-Face Still Differentiates:
  • “Showing up in person—you can read the room, use your intuition, and build trust far faster.” (John McMahon, 59:13)
  • “You can understand quickly if you have a real deal just by looking at how the person reacts.” (Dan Simon, 60:01)
• AI is an Accelerator, Not a Replacement:
  • The best sellers will use AI to amplify human abilities, not substitute for them.

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Notable Quotes & Moments

• On Business Outcomes:

  • “If you’re not tying to revenue, risk, or cost—and speaking the language of the CFO or CEO—you’re doing small deals.” (Dan Simon, 05:27)

• On the Importance of Multi-Threading:

  • “Multi-threading is non-negotiable. If you only have one champion, you’re in trouble.” (John Kaplan, 12:20)
  • “I want multiple people to scream when [Glean] turns off.” (Dan Simon, 30:02)

• On Qualification and Rigor:

  • “No pain, no champion, no deal. That principle does not change.” (Dan Simon, 10:16)
  • “If you think MEDPIC is a check-the-box, and don’t know how to get more than one champion, you’re in a lot of trouble.” (John Kaplan, 13:34)

• On the Next Level of AI Sales:

  • "Copilot’s great in Microsoft, ChatGPT is great for general use—but bringing actual company knowledge is where everything fails.” (Dan Simon, 10:16)
  • "Context is really king. Otherwise, you have a bunch of AI products that don’t talk to each other.” (Dan Simon, 21:00)

• On Value and Proof Points:

  • “If I can share a relevant proof point with an outcome, it adds clout to my pitch.” (Dan Simon, 14:41)

• On Productivity with AI:

  • “My research time saves is enormous. Every call is a warm call now—I know exactly how I can help.” (Dan Simon, 48:28)

• On "Lazy Sellers" vs. "Great Sellers":

  • “AI is going to make lazy sellers worse and great sellers better. But don’t stop learning the human behavior of sales.” (John Kaplan, 58:51)

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Timestamps for Key Segments

| Timestamp | Segment | |-------------|----------------------------------------------------------------------------------| | 02:40–04:23 | Dan’s career journey: EMC/Dell→Lacework→Glean | | 04:39–06:13 | Shifting from features to outcomes; the power of quantifying value | | 06:32–08:58 | Multi-threading and qualifying complex buying groups | | 10:16–12:20 | Keeping sales hygiene: MEDPIC, business outcomes, custom qualification | | 12:20–13:34 | The non-negotiable nature of multi-threading | | 14:41–16:06 | Proof points, trust, adding value at scale | | 17:48–19:31 | Glean explained: context engine & fishing analogy | | 21:00–22:00 | Why context is the differentiator in enterprise AI | | 26:53–27:55 | Why Slack AI (or Copilot) isn’t enough—need for cross-app, permissioned context | | 30:02–32:23 | Multi-threaded adoption & quantifying ROI for every stakeholder | | 42:54–43:41 | Shift from seat-based to consumption-based (token) pricing | | 44:04–45:04 | Addressing agent sprawl & managing adoption | | 46:44–47:10 | Prospecting: why cold calling still works | | 48:28–49:10 | How AI research turns cold into warm calls | | 54:39–56:02 | Configuring agents to be critical—not do “AI pleasing” | | 58:51–59:13 | AI will widen the gulf between lazy & elite sellers | | 60:01–60:21 | Human connection: why in-person meetings still differentiate |

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Summary Takeaways

For Sellers:

• Leverage AI to research deeply, qualify rigorously, and multi-thread accounts—but never drop the fundamentals of relationship building.
• Use proof points and quantified metrics for every business case, customized by stakeholder.
• Face time still matters—show up to build trust and read the room.

For Sales Leaders:

• Enforce outcome-based, multi-threaded selling methodologies.
• Equip teams to leverage AI for speed and insight, but reinforce the need for human judgment and social skills.
• Track ROI by stakeholder adoption/impact and anticipate the need for management layers as AI “agent sprawl” grows.

Final Thought:
AI is a force multiplier for motivated sellers, not a crutch for the unskilled. Use it to augment your energy for research, outreach, and qualification—but remember that, in the end, people still buy from people.

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Transcript

[John Kaplan]

You have the ability to build that context in, which is role specific. And then when I kind of really looked at the industry, I'm like, no, that's a big deal.

[Dan Simon]

It is. It's a huge deal. Where I'm starting to see the main traction is you come back to somebody like, like I said it before, no pain, no deal. There wasn't a lot of pain because they're like, oh, our AI initiative is Copilot. And they're like, well, Copilot only works really well in Microsoft. So let's like buy ChatGPT. ChatGPT says they plug in more into that and now we're seeing a big pivot to Claude. So now all of a sudden these companies have three different licenses and maybe they've got some point products for like call center, like legal, but they don't have a platform. Like you really need to have the context to have your AI be effective in the enterprise. Otherwise you're going to have a bunch of different AI products that don't talk to each other.

[Podcast Narrator]

Welcome to the Revenue Builders Podcast, a weekly show featuring B2B sales leaders and executives. Hosted by five time CRO John McMahon and Force Management co founder Jon Kaplan, the show takes guests in the barrel behind the scenes with the people who've been there, done that, and seen the results. Revenue Builders covers best practices for scaling and growing your business while sharing the pitfalls to avoid. Today, John McMahon and John Kaplan sit down with Dan Simon, strategic account executive at Glean, and they have a timely conversation on what it really takes to sell complex enterprise technology in the age of AI. Dan walks through his path from Legacy EMC and Dell emc, where he started selling storage, to Lacework, where he then became one of the first sales reps on the east coast and learned to move beyond speeds and feeds into business outcomes, metrics and executive level value. Today at Gleaning, Dan is applying those same fundamentals to the fast moving world of enterprise AI. In this episode, Dan shares how elite sellers can use AI to sharpen qualification, expose deal gaps, personalize outreach and move faster without losing the human skills that actually win deals. The conversation covers Medpic champions, proof points, multi threading, executive relevance, and why AI will likely make lazy sellers worse, but great sellers even better. Here we go.

[John McMahon]

So Dan, you're currently strategic account executive at Glean. For the audience, just walk us through your career path at like a high level. Going from Dell, then Lacework and Glean and talk a little bit about why you moved from selling storage at Dell to, you know, doing enterprise software SaaS.

[Dan Simon]

Yeah. So I started at. At actually legacy EMC and we were part of the acquisition of Dell. So I was still in storage boxes like VNXES, extreme iOS, and then was able to make my way from the SDR incubator program to inside sales. Was covering the DC territory for a couple of years and moved. Moved my way down to D.C. to cover in the field sales. And then while I was at. In the field at. At Dell emc, I got a call from Chad Peets, if you guys are familiar with him. One of the recruiters at Stone Hill at the time, Legend, obviously, in the space. He hit me up. And one of the things I'd always heard from my customers, hey, we're moving to the cloud. Right? So that was the new movement and wave that I heard happening. And I heard that everybody's scared of security in the cloud. So really me trying to look ahead in my career, I saw obviously a pay bump was important to me. So I saw a bigger W2 at the new role, but also trying to get to where the puck is going to be. And I saw everybody moving to the cloud, and I wanted to make sure that I was part of that movement and security was going to be very important there. So I spent some, probably about five and a half years there. I was one of the first sales reps on the East Coast. Worked under Andy Byron, Mike Hoss or two. And my really strong mentors loved working for those guys. And they were the ones that really helped me adopt the force management and command of the message process. That was something that we really stuck to diligently there, frankly. We had trainings come in and, yeah, that was a huge part of the advancement in my career. And that led me to getting this job here at Glean as being the. The first strategic sales rep in Southeast.

[John McMahon]

So, yeah, good for you. And then talk a little bit about how you had to change or your skills had to change, your knowledge had to change as you went from, you know, selling storage to selling security and now selling, you know, AI enterprise software.

[Dan Simon]

Yeah. So when I was selling storage, a lot of it was just around refreshes, so I'd be selling you a newer, faster box per se. When I got to Lacework, I'm selling, it felt like I made a pivot to selling more outcomes. Right. So everybody's moving to the cloud. There's a reason behind that movement, whether it's they're trying to save cost or generate more revenue. So I had to find a way to have Glean or have lace work tied to that revenue driver for them. And maybe, you know, obviously we all hear about driving revenue, reducing risk, reducing costs, like, those are the real outcomes that I had to focus on. And that was a new muscle for me. It took me probably a year to get going and probably lost a bunch of deals just talking about speeds and feeds. And then once I started to learn more about the business and talk about outcomes, that's where I really saw a big transition and how I sold. And it obviously affected my W2. Made more money at Lacework than I had ever made in my career. But that's what like my biggest learning is. If you're not talking about the business outcomes and the thing that the CEO, the CFO care about, you're really going to be doing small deals. And the moment that you start talking about really strong outcomes that tie to revenue or reducing cost, that's where I felt a huge transition into obviously using a lot of the force management methodology practices as a part of that med pick and really just diving into metrics. How do we quantify that business case? I have a finance background coming from Brian, so I got really interested in being able to quantify that business value and dive into the metrics. And what does that actually mean from a cost savings perspective? So that's the muscle that I started to develop really strong.

[John McMahon]

And at Dell, you knew like you did refresh, you knew who the buyer was. And then you step into a lace work and you go to an account, you're like, wow, I got to find out who the potential buyer could be here and who could be my champion and who could be the coach. And there's a whole bunch of things that you had to learn or skills that you had to for sure do that. Right.

[Dan Simon]

I think even like multi threading was part of that. Like, that was something that I realized was much more important as I got into these more complex software sales is storage. You're going to the director of it. Like, maybe the CIO is the decision maker, but the one who really cares about that is the director of it. Then when I'm at lacework, I'm starting to talk to security people because obviously they own security, but the person that has to implement that is on the IT or the DevOps or cloud ops team. And then we also had products that would weave into the software development life cycle. So then I'm going to talk to like the director of DevOps and the VP of engineering. And the more I can create a groundswell across multiple selling avenues, right? Like that translates to more business value, helps me sell a higher premium or higher deal size, and ultimately moves my deal much faster than just going single threaded into the account.

[John McMahon]

Yeah. So those multiple stakeholders, you talked a little bit about knowledge and then what about qualifying? Like, where am I in this deal right now? I've been calling on this account for three or four weeks. Where am I? How. How did you learn how to qualify where you were in the deal?

[Dan Simon]

I would always lean onto some of our principles we learned in Force management, like Med Pick. Right. Like, what is the decision process? Who's the buyer? And use that as kind of my gauge to really identify my holes. And I think what makes that a little bit easier today for me is using some things like AI to help me with that. Right. Like, it took a lot of think of how it works at Lacework. Like I'd probably hop on a call with my area director and maybe my vp Mike, and we would talk about the deal. I would maybe take me, you know, an hour of a discussion and then we'd leave that with Outcomes where today I have a lot of my calls on call recordings, so I can up and even use Glean, the company I work for today for that and I have my call recordings, all my notes so I can say, hey, in my John McMahon agent that I've built that actually inherited a lot of the principles in your book that we have embedded that into an agent. And I think what's really cool is I can just say, where are we at in Opportunity X? Give me a score worth where we're at within the Med pick. What are two or three actions that we could take in the next 48 hours to try and close some of these gaps. So before, like I am trying to identify that on calls and putting a team together with my SE and multiple sales leaders. And now I think what's cool is you can use AI to automate a lot of that, which has been really fun.

[John McMahon]

Can I get a royalty for that?

[Dan Simon]

I'll talk to Glean about that.

[John McMahon]

Yeah, for sure.

[John Kaplan]

Hey, Dan, you've progressed. You were lucky, I think, to have rigor around qualification at the first companies that you work for and all the companies you've worked for have been really methodical about rigor, about bringing skills and knowledge to the sellers. What advice do you have for salespeople out there today that says, yeah, I understand Med Pick, I understand command, the message. You know, I've been through that before. I'll just ask you a question. Is it. Do you believe it's more important now to really live and breathe those principles. Or if you've been through it, you know, 10 years ago, it's still, still the same as it relates to qualification inside of an account. So have you just thought about that? Like how much? And then by the way, if you're going to automate and you're going to use Glean to maybe automate create a John McMahon agent, what does your previous knowledge help you to do with your future performance and how have you found that? What's the cumulative effect?

[Dan Simon]

So what I found is I need to be, I guess, hyper specific with the agents that I'm building first and foremost. So when I'm saying like a John McMahon agent, I've embedded like what is a champion into that, right? So I think the first thing is like without a champion, you have no deal. That's always like no pain, no champion, no deal. That principle does not change. Even like we're obviously going Glean is a pretty big company at this point, but we're going against some of the biggest players in the space right now. We've got Microsoft with Copilot, you got chatgpt. Anthropic is the new baby that everybody's starting to adopt to now. I think that we need to be more diligent with how we're qualifying these deals and really getting to the business outcomes quicker and really helping the customer understand that much faster. So like, I'll put this into, I guess a little bit of Glean terms and how I'm selling today. So when I go to head head to head with somebody like a ChatGPT or a Claude, for example, I need to come in with a perspective on how I can help that company in the first meeting and really kind of open their eyes to different outcomes that they might not have been able to solve today. So Copilot's great in Microsoft. ChatGPT is great as like a general knowledge management. When you start to bring things into your internal company knowledge, it really starts to fail. So that's where when I'm selling I try to talk to like, say I'm calling on the CRO, like what are three to five use cases that you can implement today that would drive a very, very different outcome for your business. Like those are some of the things that I like to be hyper specific as it relates to like force management. That stuff doesn't change. Like we still got to know the decision process, we got to know the metrics that that impacts across all of the different business units. What does the buyer care about. If it's a CRO, they probably go up to like a coo. Most of the time it's reducing the amount of time it takes for them to sell or improving the amount of revenue that they could sell per deal conversion rate. So those are some of the different language and terminology that I'm using. But I have to change that depending on the person I'm talking to.

[John Kaplan]

I love that. I think that what I heard you say is multi threading. Like that's a non negotiable today. If you're going to be successful in sales and you're not, I don't care what you're selling, if you're not multi threading, you're going to be in, in jeopardy. So what I'm, what, what I kind of hear you saying is instead of thinking about what I've learned and how it's kind of like a check in the box, like I have a champion that ain't cutting it anymore. So if you tell me you have one champion selling glean, you ain't gonna make it right because of the, the good news is the massive opportunity and the problems that clean solves. So I would just encourage people and you know, to listen to this and what you said is like all those principles that you have, the better your solution, the more impactful your solution, the more diligent you're going to need to be with your communication, with your execution, with your qualification. And if you just learned how to do med pick a check in the box like I have a champion or I don't have a champion and you don't know how to get multiple champions at this stage of a career, you're

[Dan Simon]

in a lot of trouble.

[John Kaplan]

You're a lot of trouble. A lot of trouble. That's why I love your book Johnny. I think one of the. I told Johnny in the qualified sales leader, one of the favorite parts that I think John did, which was so unique is that he told the story like he took the principles of qualification and messaging and all the things that a rep has to do from an execution standpoint. It just kind of, it's almost like you took like a pre AI version of it and you got it into the workflow of what a CEO and a CRO and a sales VP and a seller actually go through. And I think you just did a great job of talking about like what's, what's real and not doing like med pick is this, you know, it's this check in the box. It's that you gave real life Examples with real life scenarios. And that's what selling is now. Real live examples, real life scenarios that are going to, that are going to question, you know, how you qualify, who you qualify with, what you say to them, not just the need to qualify.

[Dan Simon]

So sure, Johnny, I'd say I'm fortunate here at Glean too. Like we do have a lot of successful customers and part of the mantra is proof points. So if I can share a relevant proof point with somebody and actually talk about the outcome that somebody has had, it's only going to add more clout to my pitch. Right. I'm a salesperson. Like everybody has the seller deficit disorder. They don't understand I don't understand their business. And like their eyes are already glazing over a little bit by the time they're talking to a salesperson. But if I come in with a perspective, I'm hyper specific. I have a business outcome that I can affect with that person. It's really going to open their eyes. And I always, I think trust is a huge part of every single sales cycle. Right. We're going to have to build that trust fast. And the way that they trust you is you bring value to them very quickly and you become hyper researched. You're very specific to how you can help that person. One of my favorite books is called the Go Giver and the principle of it is how much can, how much value can you add to somebody at scale? And ultimately that's going to come back to you in return whether it's financial return, which is, I'm a coin operated guy as a salesperson, right. So I'm always trying to add value to people as fast as possible and at scale. So if I can add that to one person, well how can I add that to multiple people in the business? I love that. You know, we're going to help people grow their careers too. Like a lot of the people that I've sold to have gotten promoted. Like that's, that's something that I take a lot of pride in as well.

[John Kaplan]

I love that example. You know, for years we used to talk about how to add value to a customer even without a conversation. And you know, in the old days it was sending them points of view. Like now it's an expectation and, and I think we're, we're actually evaluated by our customers by what value. If I'm going to spend some time with somebody who's just not just going to give me information about their product, but who's actually going to tell me something or ask me A question that I haven't thought of and what I love about what you just said, Dan, is I encourage all sellers. Like every time you interact with a customer, it doesn't have to be zoom, doesn't have to be face to face. You send them something, it has value. You're not just filling up their inbox. It's almost as if you had a face to face conversation. So if you sent three or four things with a highly relevant point of view, that's highly relevant to their problems or challenges or what have you. And the way the human brain works, it's like they get to know you better every time. It's like three flights, you know, not taking away being in person. But I think people really underestimate that. They don't figure out how to sell in their absence. And I think it's a powerful thing you just said. So go givers a good, a good read for that.

[Dan Simon]

I agree. Yeah. I wouldn't even say it's sales specific, but it's a, it's a great breed about adding value to people.

[John McMahon]

Love it just for the audience because we mentioned Glean a number of times and most of the audience might know what they do, but at a high level just explain to the audience what Glean does do.

[Dan Simon]

Yeah. So we were founded as an enterprise search company. So when I started that's actually what we were selling it as. Is you can search for anything across your company and find it really fast. And now what we're seeing is the lines are starting to blur across that as somebody like ChatGPT, like Claude can, can plug into your company data. So what we're seeing as the real pivot of how we're selling the value of Glean right now is our context engine. So what context mean is how you work as an individual in the organization. There's a lot of different application hops that you have. So I'm a fisherman, so I'll kind of do an analogy for you. So you could cast a net out, right? And maybe you're going tuna fishing, but you cast the net out on the back of your boat and you're just trying to catch everything. Like you might catch some other fish, you might be catch some trash floating through the ocean. What Glean does really well is think of us having a fish finder. We have a setup already with a lure that knows how to catch that tuna and we're going to go find that fish immediately for you. And the way that kind of translates to business value right now is we're seeing Massive token consumption across all of the main LLMs. And it's the way that they're calling out to the different applications is very inefficient. It leads to poor accuracy, more tokens being used, and ultimately you're trying to get your users to use this. So if they're not having accurate answers and they're spending a lot of money for that, they're not going to ultimately see the value. So we're selling our context engine as a service right now. And that's where I'm seeing a ton of traction. As people have said, like, hey, I'm trying to build an AI platform for my teams. Obviously I have ChatGPT, I have Copilot, but what we're lacking is like the accuracy, the security and government governance layer and the context, which nobody is talking about.

[John Kaplan]

Johnny, when we, when we have people on, we're always kind of, oh, by the way, what are the concerns about security and, and permissions and that kind of stuff. Can I add to your analogy a little bit? Because, like, I, I came and spoke at your. The day before you guys probably got there. I was with all of your sales leaders and was with Brad and his team. And you know, my stomach was hurting a little bit for you guys, like when I was. Because I've been following you guys. I really, really think you guys got something great going on. And I'm, I'm looking at where all the other companies are going. And when I started to think about like this analogy, you just said you're a fisherman. Well, I think one of the unique advantages that you guys have right now, at least, and that's just saying AI right now. Right? But like, I can get the context as a fisherman. I can get the context as the boat captain. I can get the context as I, I want to get the context of I want to go and I want to rent that boat and I want to be the person that's fishing on that boat. So you have the ability to build that context in which is role specific and permission specific. And when I first read it, I was like, yeah, of course. Like. And then when I kind of really looked at the industry, I'm like, no, that's a big deal. Am I right or wrong? Is that a big deal?

[Dan Simon]

It is, it's a huge deal. And I think that's like. But I was feeling in South Florida, it's a great territory, of course, but I'd say a laggard compared to some of the folks like Silicon Valley, like Boston, like New York, there are Some more tech forward companies out there. Areas out there where I'm starting to see the main traction is you come back to somebody like, like I said before, no pain, no deal. There wasn't a lot of pain because they're like, oh, our AI initiative is Copilot. And they're like, well, Copilot only works really well in Microsoft. So let's like buy ChatGPT. ChatGPT says they plug in more into that. And now we're seeing a big pivot to Claude. So now all of a sudden these companies have three different licenses and maybe they've got some point products for like call center, like legal, but they don't have a platform. So that's really what I'm seeing as going to be a big shift in the industry over the next, I don't know, a year or two. But even Gartner's writing around it about it now is the context is really king. Like you really need to have the context to have your AI be effective in the enterprise. Otherwise you're going to have a bunch of different AI products that don't talk to each other.

[John Kaplan]

Well, think about the slop that we get. You know, I think you guys call it the slop problem or the AI slop. And like Johnny does, like I do, like every other consumer out there is trying to figure out. We all have licenses of the same stuff. Yep. I have three main licenses, at least three main licenses. And what I've noticed is, okay, if I have my personal situation and I have a Gmail account and I have, you know, like that workspace environment, that could be interesting if I have, you know, if I want inference, if I want speed, that's, that's one that could be very interesting if I want, you know, so they're, they're starting to kind of morph out a little bit. And at the end of the day I see that people still lean for one reason or another to a specific technology because they've come to the realization that that's what helps me do my job better. So I think that the AI winners are the ones that get close to the work of the individuals and they make that individual massively more productive. I think that's the only thing it's going to win.

[John McMahon]

Yeah. And that will happen over time where there'll be different specialties for each domain. But right now that's exactly. And I think what Dan is talking about and what I've seen is if I'm very familiar with the domain, it doesn't give me the Right answer. Right. When I'm not familiar with the domain all of a sudden I think well that sounds right and I'm really familiar with the domain and I ask it a question, you know, that it, it's hallucinating and it's given me an answer and I look at it and go that's not right. Because it doesn't have the deep domain knowledge that, that it requires.

[Dan Simon]

Yes.

[John McMahon]

I think that's what Dan's talking about when you're talking about accuracy with glean. Right?

[Dan Simon]

Yeah. And you don't what's good about us. You don't have to do a lot of pre prompting so you can probably get a good outcome with a Claude with ChatGPT. But there's a lot of upfront work that you would have to do with GLMR inheriting. How we position ourselves right is it merges together content activity and people data so we know who you are in the organization, we know how you're working and then we look at all the content so it understands how you work and builds an enterprise graph. But then it also knows how Dan Simon works and that I'm going into Salesforce every day, that I use Google, that I go into Slack, that I have calls, recordings and gong and how often I'm using those. So when I ask a natural language question it just pops up. It just makes it so much easier with I'm decently technical but I'm not an engineer. I can't create a hyper custom workflow. I just want to use the AI assistant or maybe use natural language to build an agent and it just works. A lot of these tools you try to do that and it hallucinates like

[John Kaplan]

John was saying, you just hit it. For me, I think it's the context of the user and those that have the ability to figure that out the quickest. It's the permissions and the security of a company and what somebody's going to be allowed to do. It's the proficiency of the, I don't call it code code or no code or low code or whatever but that you know, creating agents and, and people's appetite to do that. That's where it's kind of leveling out for me that that's exactly going through that thought process of saying how I wound up with, with the, with the tools that I have. Tell me a little bit about the one that's a sneaky one for me is like Slack kind of is a, a sneaky one. Like everybody's, you know, so many people are using Slack, they're. I hated it. And matter of fact, it's not that I hate it. A lot of other people I want to be careful. I don't, you know, but you know, my company uses it and everybody says, well it's it. I sent you a message in Slack or whatever. So I'm one of those dudes that's like, okay, well tune Slack to. When something gets sent to me, it gets sent to my email because that's my normal workflow however, that he's aging himself now.

[John McMahon]

But go ahead, you're doing good job.

[John Kaplan]

Well, I, hey, I still do it. I get it. You know, I'm not in Slack every day but I don't miss anything because they wrote it so I could get an email. However, for me, like, like Slack AI, just talk to me a little bit. Like I can imagine you guys are out there every day and they're like, you know, it's, it's these companies, these big companies that are adding AI tools specific for that application that, that are probably not interesting but you guys have your eye on. So talk to me a little bit about that. Why would I just, you know, just you. We're all using Slack. Why wouldn't we just use their Slack AI? I know you're going to have a great answer for this, but give us some context.

[Dan Simon]

So Slack AI is going to be great in Slack, just like Microsoft Copilot is great in Microsoft. But when you start to go out of their ecosystem like Salesforce and Slack don't want to build a context aware connection for all of the different applications out there. So you could ask a natural language question in Slack and be like, where are my most recent Slack conversations? But I'm like, hey, where are we at on the deal with Company X? Like I have had communications in Slack as part of that, but I also have gong recordings. I also have emails through Gmail that have went out out and I just need it to pull in all of those different sources and give me a, like we call it an Account360 agent that we built. I just need to type in a natural language question. It needs to pull all of the most relevant information for me. SOC doesn't do that or at least it doesn't do it well, they might claim that they do, but it's not, it's not doing it well. That's why Glean's frankly been getting a ton of traction and like the enterprise wide casting a much wider net but pulling back the most accurate answer for you.

[John Kaplan]

You said something at the Beginning of this that I, I just want to highlight. You know, you said there's a difference between being and Johnny said, like a domain expertise in an application versus the ability to connect hundreds of applications and get that 360 view. And that is, I think that's extremely interesting for customers right now.

[Dan Simon]

I do for sure. Where have we sold deals like this before?

[Podcast Narrator]

Right?

[Dan Simon]

Like, what are some roadblocks that I could face? Like maybe that's not in Slack and there's even like you're pulling stuff from the public domain too. Like, hey, help me do some research on this company. What are the different business units that I'm going to sell to? What are the different outcomes that these individual Personas would then focus on and I can craft my very tailored messaging to each of those people. That's not just going to live in Slack. So you really do need something that's much broader. And of course there are great, like there's legal tools out there, there's call center tools out there and they're going to do things that Glean cannot do. But you're always like the first thing that everybody does in a company. And I'm sure we've all had an experience with like Google Drive or SharePoint, like their search quality is terrible and what a lot of the MCP is the connectors that a lot of our competitors use and MCP is inheriting that terrible search quality. So if you don't rebuild the context engine, you're going to have a really tough time finding the most accurate answer

[John Kaplan]

which again is going to go to how the user uses, you know, at the executive level. So talk to me a little bit about like I think selling in your environment is not just selling at the executive level. It's like if I was selling your product, I would be selling to Dan almost as much as I would be selling to the CEO or CFO of a company. Because at the end of the day, how they are going to look at a success of any AI strategy is if I turn it off, will Dan screen. Will Dan have a problem? That's my right now. That's my ultimate, my ultimate measure right now. If you take away any of these tools, will the rep. Will the, will the user. Will the end user screen?

[Dan Simon]

For sure. I think that goes back to multi threading is I want multiple people to scream when that turns off. So I'll talk about a recent deal I sold at a really large e commerce company. So the way I landed at the cto, he then passed me down to a couple of different Personas. There's somebody who leads the AI program for the organization. She has a plugin to the product managers, the engineers, the finance team. And then also legal was another domain. We build a use case for all of them. There is something that we can solve for each of those Personas. So I like to sit down with each of them. One of the biggest differentiators that I learned early at EMC too, with a very crowded competitive space, is get in person. In person is going to differentiate you very quickly. And with all the noise out there in AI, I think there's also something to be said of like, go build a real relationship. You're going to get a lot of outreach. That looks very similar. Go build a relationship. You do that better in person. So my engineer and I flew up to this customer and we met with each of these people for about an hour, identified what their current state is. What are some of the different metrics that we had on some of these use cases? So maybe it's like I'm drafting a PRD product review documentation, an HR use case around onboarding new employees, like drafting OpenRex, for example. There was like a variance analysis agent that we had to build for the finance team. We quantify each of those use cases. How long would it take you to do that today? In some cases it took took maybe 10 hours, 14 hours. And part of that would be like, oh, well, now I have to go wait on an update from this person that sits over in emea.

[John Kaplan]

Right?

[Dan Simon]

We're on a different time zone. So I'm waiting and waiting, like, that's stalling business, it's stalling revenue. So we have all of these little quotes as well embedded into this with the metrics, which I think really amplified the business case. When we went back up to the CTO who had already brought in ChatGPT, mind you, so we showed him a business case of like, yeah, you have ChatGPT, but you're spending 10 hours on this task, seven hours on this task. This is how many different people that this is affecting the business. It was like a seven to $10 million loss for them to not buy gleam. We were a fraction of that, of course, but our ROI was something ridiculous, like 50 100x. Right? Because we've been able to multi thread. If I only landed with like a single team, I wouldn't have had as compelling of a story.

[John McMahon]

Now, do you think if they hadn't taken in ChatGPT and you showed up, that you could have gotten the deal because they might have said, well, let's use Chat GPT first, because we hear that that could do it. So is it almost better that for salespeople that are selling a real good AI tool, that they've already used one of the large LLM models to try to achieve what they their business outcome and you come in afterwards because they're more educated.

[Dan Simon]

I mean, I'm confident in my abilities that we could have got a deal done there. But I think you're right.

[John McMahon]

I love that there's no pain, there's no deal.

[Dan Simon]

Like, there probably wasn't a lot of pain yet. And that's what I've heard in my first year of selling is like, oh, Copilot's our strategy. Oh, ChatGPT is our strategy. Like, I'm kind of feeling today like it was back at my EMC days. Like, nobody gets fired for buying Cisco, buying emc. Like, people are like, oh, we're not going to get fired for buying Copilot or chatgpt. Like, everybody knows about it. They're the biggest company out there right now. And I'm starting to feel that a little bit with Anthropic too. But they all have the same challenges is token consumption accuracy. Like, they're just not there. And now that they have the pain, my message has become much more compelling. And it's also helped to sell into a lot of Fortune 500 accounts now who have tried to build this themselves. They have two or three different products that are still not working, and it makes our story that much more compelling.

[John McMahon]

They're not worried about security. That doesn't come up where you're taking all your internal data and it's getting consumed by these models and even customer data, personal data. They're not concerned that much about security and compliance.

[Dan Simon]

I mean, I'm sure they've got some good sales reps telling the story. And then on the other side, like, they're six to 12 months into that implementation, like, hey, this isn't really what we were expecting it. So, yeah, I think what's cool about Glean, too, is we actually do have a security product embedded into our platform. It's called Glean Protect. So it actually will scan for sensitive content. So say you have credit card information or any type of PII that you don't want in there. There's a bunch of rules embedded into that. Or you can create your own rules to remove that from your index. So it also, like, some of my strongest champions have become CISOs. Like, I was looking at some data, data security protection tools and like I'm a little scared of chatgpt them making sure that they get this right. And you're telling me Glean not only could help me alleviate the need to buy a separate. Separate product, but they feel much more comfortable rolling out Glean with the way it's not. It is permissions as part of that. We obviously inherit the permissions of that source application. But also making sure that their users can't search for something that's overexposed in SharePoint. Like there was an instance in a pilot that we were running, which frankly helped us sell the deal. They had the salary information of all the executives and it was publicly accessible. So somebody like me, a seller, I could, if I knew where to look for that in SharePoint and it was probably hidden in a bunch of folders. But if you're in a chatbot, in a co pilot, like I'm not so sure that they would have been able to catch that. And that's something that Glean can find.

[John McMahon]

And who have you found in these deals? Where's the power base does I mean, you have the technical buyers like the CIOs. You talked about a CTO. You get the chief digital officers.

[John Kaplan]

Yep.

[John McMahon]

And you have the business buyers. You got sales, you got ops, you got cs. Where do you like to go first, second, and why

[Dan Simon]

first? I'm always calling in the tech organization because I do believe that they are the ones that are going to roll this out. And a lot of them have tried to build their own platforms. There's also a lot of opportunities I've had around the data teams. So people that are working with some of the warehouses out there, like a databricks, like a snowflake, they tell a very compelling message too. They actually both use our product for their own internal use because what they do really well for structured data, Glean does really well for the unstructured data. So they're a customer and a partner of ours. We can integrate with their platforms to tell a much better, better together story. But instead of having data, scientists have to kind of create their own Glean. We can actually automate a lot of that for them. So I'd say tech organization is a great fit for us. Like engineering data teams and then go to market is also a great one if we can drive revenue faster, help with better conversion rates, help win rates against your competitors. What I'm, I mean, it's QBR season right now, so I'm actually using Glean to build my QBR deck and they're urging us to do that. And it's not even a deck anymore. We actually have interactive HTML pages where I can say, hey, what's my forecast? What are the white spaces in my accounts? And it's like a presentation, but in a website format. I can just type that all out into Glean and it'll create an HTML website for me, which is really awesome.

[John Kaplan]

You got to start somewhere and for you to be able to do something like you just said, these have to be like massive implementations. It's like the sucking in of content and like explain to us like how hard that is to implement.

[Dan Simon]

Glean. Yeah, I mean the connect.

[John Kaplan]

The good news is you can connect to, you know, 100 agents. The bad news is you got to connect to 100 agents.

[Dan Simon]

I think the connection is fairly simple. The part that takes longer is getting the people to actually want to build their own agents. Like Glean does have some agents out of the box, but until somebody understands the value that it can bring to them, like that's why it takes a lot of hand holding and there's a big movement around forward deploy to engineers to try and build these agents. For people to deploy Glean, it could take a week or two. We index, we understand like that's not the long part. The part that takes longer is talking to somebody in finance and identifying the use case that we can help them with and then working with them to build that agent. Most of the time to build that agent, it's like an hour or two. But you really got to help find a task that they're doing multiple times over and over again. Like that's where, like how, how often are you doing this task is kind of step one. Because if it's only you're doing this once a year, like it's not going to be that impactful. Like is there something you're doing every day or once a week? Walk us through that step by step process and that's where we'll, we have a team ourselves, an AI outcome manager that will help them actually build that agent out. But it takes some time. You got to sit down with each individual person. They're all doing different roles within the organization. That's what I mentioned at the beginning. You have to be hyper specific and really understand the person you're speaking to. What does their day in the life look like so I can prescribe them the right agent or the right outcome.

[John Kaplan]

I think that what you talked about on like business outcomes, why this is so critical today you could go in like these forward deployed engineers that's going to cost the company money whether they're going to pay for it or not. That's a whole nother conversation where they have resources to do it. What customer success looks like. The best advice I give to go to market teams today is find out the biggest business issue facing that customer and work backwards all the way down to the workflows at the critical exchanges of information. It's like what we used to whiteboard 20 years ago when we would say what are you trying to accomplish? Walk me through your process. Where are the biggest bottlenecks? And so it's like you can't sell this. You talked about multi threaded earlier. You have to sell this at all. You have to sell it at the executive, the business, the line of business level. You have to sell it at the technical level, you have to sell it at the user level. And you got to have your crap together. Like you can't be missing any of those. Like if I tried to sell glean at the CEO level of a company, CEO is going to say this is an unbelievable concept. I would, I couldn't imagine why my company wouldn't want to do this. But I'm certainly not going to tell them which AI strategy to go Now I'll ask them why the hell didn't you use glean? But, and that's, you know, you can't shortcut these things anymore. You have to multi thread.

[Dan Simon]

Absolutely.

[John Kaplan]

And start with the business issue. I think the advice I have, starting with the biggest business issue, work your way backwards. So you work your way backwards to the process flows, the, you know, the technologies, the, the, the, the user workflows and it's, I don't think it's that hard but you got to keep them connected. You can't do it for a thousand different ones. If you pick the biggest business issue and work your way backwards, you're going to hit a home run for sure.

[Dan Simon]

I mean I love starting high, right. A lot of the executives are getting like you've seen some of the reports around. Just mentioning AI just jacks up the stock price, right. So they're all getting a push to roll out AI. So if I can land high, have a nice message around, why Glean can be an enterprise wide solution. Get their buy in to actually send me to these different Personas. Like that's where I've seen my biggest deals happen versus if you are landing low, you might be able to solve one problem, but it might, it might be a little bit harder for you to go around the organization.

[John McMahon]

Right.

[Dan Simon]

If Somebody in engineering might not talk to somebody in HR that often. So I'm always trying to get as high as I can and then work down the chain. If I do land low, of course, ask your champion to introduce you to other people.

[John McMahon]

Right?

[Dan Simon]

That's going to benefit them. It's going to benefit the sales process. But the fastest ones that I've seen, especially recently at our company you're landing at sometimes it is the CEO in smaller accounts, but for strategic it's cio, CTO and even the cfo because they probably already spent on another LLM provider.

[John Kaplan]

Got all these tools.

[Dan Simon]

If there is a way for us to justify that. And Glean right now we're coming out with these really cool enhancements. We have a new LLM ourselves. It's called Waldo Waldo. If you use that as the pre processing engine, we can actually reduce the amount of token consumption by about 30%. So if I do a math problem and I've done this for a customer just today was like hey, if you roll this out to 20,000 of your employees that could be like a 6 or 7 million dollars cost savings just in the token consumption alone. That isn't even me quantifying the use cases or the outcomes for each of those business units. That's strictly in token consumption. And then that gets them like the CFO like holy crap. This can solve a really big problem for me. Now I will sponsor you to go to the different business units too. Identify where specifically you can help.

[John Kaplan]

Are you selling this seat wise or consumption?

[Dan Simon]

We had been selling seat and I actually think this is where I see a big movement to this whole model is consumption based moving forward is you're going to see I think a lot of the different AI providers charging for consumption. Glean now has a consumption model ourselves very recently. So I think it benefits both sides is they're going to be using our product more. The more value that they're getting, the more they're going to consume consume. And it's our job as sellers and post sale resources too to make that customer hyper successful.

[John Kaplan]

So we are tokens come back into play here in consumption.

[Dan Simon]

They do for sure. But that's also the the they're getting more. If they're using more tokens that means they're probably getting more value out of the tool.

[John Kaplan]

Love it.

[John McMahon]

Dan, when you go into these accounts, has anyone talked to you about like their worry about agent sprawl? Like every sales rep is building agents, Dale's is building agents, CS is building agents. They got agent, you know Initiatives up top, you know, with the chief digital officer, chief tech officer. Do they ever talk about, my gosh, it just seems like this agent sprawl and they're not worried about that.

[Dan Simon]

Yeah, I hear, I hear that a lot. I see it ourselves. Like Glenn, like people are building their own agents and there are some great ones out there that sometimes I don't even know exist. Like there is. I think there needs to be a management layer on top of all of those agents to better identify like what are the best agents to use. And we do kind of gamify this a little bit within the Glean platform. You can break it down by like sales agents. How often are these ones being used? For example, you can ask our assistant like is there an agent for call coaching or is there an agent for me to do account research? And Glean will actually pop that up. But I do think that's a big opportunity in the market right now to help with that problem for sure.

[John McMahon]

And when you're mapping an account, we talked about multi threading the account. When you're mapping an account, walk us through like your methodology or how you, how you frame that when you're walking through these stakeholders, these pains, these use cases, here's how I'm going to go after them. What's your methodology to do that?

[Dan Simon]

I lean on Glean very heavily for that. Now what it looked like in my past life is I, I mean I still go into LinkedIn, sales navigator. I'll create a map of all the different Personas. I'll look at their website and then I'll say hey, to Glean, I'll just ask, do research across their 10k financials. Find everything you possibly can across the Internet about this company. Then break out the different business units within this business, whether it's like supply chain, hr, legal, et cetera. Provide me a value statement across each of those and then provide me a proof point where I could position this to somebody. And then when I have that I'll have like a nice Excel spreadsheet where it's all organized. I can say cool. Now today's my day to go after hr. Give me maybe a five step sequence that I could send over the next couple of weeks to this Persona and provide a proof point there, use some actual metrics, a similar customer to them. So I am leveraging AI for a ton of that right now and it saves me a lot of time because getting hyper specific is what you need to do to break into these accounts and get cut through the noise. I think the Biggest challenge is a lot of these emails are going to sound the same because we all are using the same AI tools. The number one way to get meetings still to this day is cold call. For me, people are leveraging their AI tools and I think people are getting stuck of like, oh, I'm going to write the perfect email. I'm going to write the perfect LinkedIn message. Well, your competition's also doing that. But a lot of people are still lazy just to pick up the damn phone and make a cold call. And we've actually been able to get a lot of meetings that way. I think it's still just as valuable as it was when I started my career as a bdr.

[John McMahon]

And you got to believe that customers are starting to build or get, you know, some sort of spam type filters on the front of the front end of their emails where they just sorting through knowing that some of this stuff is just, they've seen it time and time again and they're just rejecting those. So those email getting through for sure.

[Dan Simon]

Is it really. It's harder on the phones too. There's call screeners all over the place. I got them on my own. So it's, it's definitely getting harder for us sellers out there for sure.

[John Kaplan]

Would you even say that the. Is it. I wouldn't even call it cold calling anymore. I mean, I know maybe we emotionally connect to that like the, the good old days. But like AI, there's no reason to cold call. You could make every single call that you. Like what you just described and you've seen this in your, in your, you're a young guy, you've seen this. Like if you had this back at the, when you started at emc, you say, okay, today I'm going after this sector, I'm going after these. Your productivity level and your effectiveness is, is just off the charts. And so anybody picking up the phone right now, that isn't. Or excuse me, that's listening to this and thinking about, you know, how do you build a really good solid prospecting day? Like PG days. Like there's still companies I talk to today, they're like, oh yeah, we don't do that anymore. And I'm like, what? Like I didn't say you do it the same way you did it 20 years ago. But like, I mean that's so exciting. I mean what have you seen? And just your ability to do. Walk me through like to do prospecting when you first started to do prospecting. Now just give us a high level overview of what that Looks like for

[Dan Simon]

you, I think the biggest time saver has been my research. And you're right, it's a warm call nowadays because I know exactly how I can help that person. I've got a proof point. I've used AI to find that it is much more tailored. It's not. Hey, I'm calling from emc. You know, I would love to talk more about your storage. It's like, hey, I know that you guys are building an AI platform. I read all about it on XYZ blog. Or I saw a YouTube video of you presenting and that's probably pulled from AI. Here's how glean can specifically help. And here's how we saved this customer millions of dollars and help them accelerate their AI initiatives by using Glean. Like, would love to just get a couple minutes of your time to share more earlier.

[John McMahon]

He's coming in with a point of view, a business outcome and points, and he's hyper specific about it. And that's what's differentiating Dan.

[John Kaplan]

I love it. You know what I hate right now? I'm getting so many reach outs from these. From these people. It's like they're taking a half swing. You know, Johnny, sometimes when you tell me, like, I just kind of. I didn't, I didn't follow through on the swing and they'll say, hey, I listened to your Revenue builders podcast with Dr. Gervais and I'm like, okay, I lean in and then that's it. I have this tool that allow you to do, what the hell? There's no connection between. You listen to a podcast that Johnny and I did, and I leaned in a little bit and then you freaking did a half swing. Like, it's almost insulting.

[Dan Simon]

But they still went through the plate and struck out.

[John Kaplan]

So clearly went through the plate to the plate every now and then if I have a little time, I mean, I'm not. I'm not a bad guy. But every now and then I'll just say, like, really? You listen to a podcast and then sent me a spreadsheet of you know what? It's just like, there's no. There's no even connection.

[John McMahon]

I still get offers for sales rep jobs.

[Dan Simon]

Oh, I know, I know.

[John Kaplan]

Me too. Me too.

[John McMahon]

I'm like, really? You did your homework?

[John Kaplan]

Yeah.

[John McMahon]

Hey, Dan, talk a little bit about the tech stack that you're using right now. What do you said gong? You're probably using Zoom. What else do you have in that tech stack over there? You have salesforce.com.

[Dan Simon]

that's right. So by far My favorite tool, of course, it's literally my favorite product I've ever used. Glean is by like, I use it probably 15 or 20 times a day. So we have that plugged in at least for me. We have a bunch of other applications, but I'll talk about us as a seller. So gong for call recordings, we have Zoom and actually Google Meet. Our founders are from Google, so we've got a relationship actually with both. We use G Drive, Gmail, Slack for messaging. And I think there's a content management system that I actually never go into because I have Glean, just suck the content out for me with the question. So we use all of those. But like, that's why I use Glean so many times a day is I'm. That's my entry point. And I'm asking a natural language question and I'm like, I need to compete with Copilot on one of my calls and how do I position them? Like that might suck it out of the content management that we have for our sales team, but I'm rarely going actually in there. And then it will pull some of the like, call transcripts from other calls with other reps that we may have talked to about a very similar competitive situation. But I don't really need to go into that source app anymore. It's just pulling that out for me now.

[John Kaplan]

Does it learn, Danny, if I go in, I say, give me this because I'll go into Copilot, I'll say, give me this and it won't give me the right thing. And I'll refine the search. And I'm hoping that it learns from my first question to my third question to my third prompt and then obviously, well, by learn from how I'm prompting. But will Glean learn? When you asked, like maybe a too generic of a. Of. Of a prompt for Glean and it gave you back something that was not exactly what you needed. And then you. And then you ask it again. Does it learn from that?

[Dan Simon]

It does. That's part of our memory layer within Glean so it understands how you like to interact with the solution over time. There's also a new feature that a lot of the LLMs are coming out with, and Glean has it as well. Skills. So when I like, it's a skill for outreach. Like, what is the way that I like to do outreach? What is the way that I like to prep for a call? You can create a skill for that. So every single time it knows that Dan Simon would like to get this. Maybe it's a bullet point format or executive summary of the company. What are three to five questions that I can ask this customer on a call? What's a proof point? Give me a targeted next step. Like that's a skill that you can pre frame within glean. So it absolutely does learn over time. So you don't have to do as much prompting.

[John McMahon]

Zach Dan, when you guys are forecasting or you have to update the systems. How often do you have to update these tools to feed with your forecasts?

[Dan Simon]

So once a week, every Thursday they expect our forecast to be updated before our call on Friday. We have agents of course within Glean that I could say auto update this for me so it'll push our latest update. Maybe I had a call with my customer the day before or that day. It'll understand that it'll see the emails that went out and then I can say hey, what was the next step that we had talked about with Company X? Push that into Salesforce or you could actually take the call recording upload it to our Salesforce update agent that we have. It'll understand everything on the call and then you can just click a button and it'll push it out to Salesforce for us.

[John McMahon]

Your manager's still asking you for updates like verbal updates on where the deals are throughout the week.

[Dan Simon]

Thank God. It's like a blessing that we don't have to do that even. I know I talked a little bit about call coaching like there used to be, you know, big deal review calls with your managers. Right. Like that's something that I can self service as a rep now. And that's why I said like the qualified sales leader agent like just help me understand where I'm at in the deal. Like if I need help, sure I can go to a leader to get a different perspective but I think that it just helps expose my gaps, gives me some actions that I can take today. Like a lot of this is now able to be self serviced as a

[John McMahon]

rep agents could they could hallucinate because you could say here's the three reasons I think John Kaplan is my champion. And the thing will come back and say yeah, John Kaplan's your champion. And then you could say well you know John Kaplan did this and then it could come back and say yeah, John Kaplan is definitely not your champion.

[Dan Simon]

Yeah, I think that relies you have to go back into the agent And I think ChatGPT for example. Agree. I think everybody says like agrees with everything that you right

[John Kaplan]

the way in

[John McMahon]

which you asked it. Right.

[John Kaplan]

That's right.

[John McMahon]

You Say Kaplan is my champion. It answers that. Yes. And you say, kaplan's not my champion. It answers Kaplan.

[John Kaplan]

It's a pleaser. It's an AI pleaser.

[Dan Simon]

There's ways to tune that within Glean. So you can say, be hypercritical of my deal, right? Like, expose the gaps. Don't be in agreement with everything I say. Like the way that you prompt it and ask it to respond, it will follow that instruction. So the qualified sales leader agent is actually very critical of your deals. It's not going to make you feel good, but it's going to tell you where all of the gaps are in your deal. And it'll actually give you a color. It'll give you a red, yellow, or green where you're at in that opportunity. So I think the way that you prompt it is going to be very important because if you just go to the LLM, you're right. It's going to say everything's great and fine, but you really have to refine that in the agent. You can do that?

[John McMahon]

Sure. Can I get a royalty on that one? And you got the McMahon agent, the QSL agent. Wow. All right.

[John Kaplan]

Yeah.

[Dan Simon]

It's publicly accessible knowledge, I guess. You know, you got to buy the book and then you got access to it. So.

[John McMahon]

Yeah, yeah, I've heard it many times where people have copied a lot of that stuff and actually tried to put it into LLMs and put it into their own system that they're building.

[John Kaplan]

Oh, that's a problem for you, John?

[John McMahon]

Yeah, I probably shouldn't have wrote the book.

[John Kaplan]

Yeah. Try being forced management.

[Dan Simon]

That was you giving, right? The go giver. You're giving, you're giving back.

[John McMahon]

That was the whole intent. I mean, you don't really make any money on a book.

[Dan Simon]

That's right. That's why you're interviewing me on the podcast. And I'm not interviewing you now. You know all the value that you

[John Kaplan]

brought, so she's such a giver.

[Dan Simon]

We appreciate it.

[John Kaplan]

Unless you're playing golf with them, forget it. Forget it. Hey, one last point I'd like to make and get your guys comment on all this AI that we're talking about. It gets me fired up because I think it's going to make the lazy sellers worse and the great sellers better. And we just kind of alluded to it. Put my John McMahon agent, you know, activating that. It's going to tell me why John McMahon would tell me that I don't have a champion. But knowing how to get a champion and knowing how to. You Got to keep these skills sharp, you know, telling you you need to be multi threaded versus multi threading. You need that human factor. And as much as you learn about productivity and learning these AI agents or what have you, do not stop learning about the human behavior of sales. Because you know the, I don't know what the software company was but the last week or two weeks ago that, that were AI. I don't know if it was Claude. I think it might have been where it deleted the, the, the source code. It's like deleted the product of the company. And what I first thing I thought about was the human factor up. You and I before we push that delete button, our finger would be shaking a little bit and they couldn't teach it to AI. The AI just said doesn't have this, we don't need it and deleted the whole freaking program. I can't. It was in the Wall Street Journal. I can't remember what it was. But that finger shaking, that bubble in your stomach that, you know, use these tools to take your skills to the next level. Don't be lazy. You know, what's my opening pitch that I should use for this customer? You know, practice it, try it on. Just don't be lazy and just, you know, first of all, like you guys have talked about, you could be getting some slop or some hallucination, but at the end of the day you're responsible for what comes out of your mouth or you know, what gets sent.

[John McMahon]

But I love what Dan's doing. He's separating himself by being hyper vigilant on what he talks about and more importantly, he's showing up face to face at the account.

[John Kaplan]

Love that.

[John McMahon]

I think a lot of these AI tools, people are hiding behind the AI tools. They're not going face to face with the customers and they're not sensitive, hyper vigilant about what they're talking about. So you can really separate, you can use these tools to caps point to make yourself a whole lot better and really separate yourself. Or you could just be lazy and use the tools and you're never really going to gain any new skills or anything. Showing up in person though, I've always felt like that was like a real strength because I. You can read the room, you can feel, you can use your intuition and when you just over email or over the phone or even over, you know, video, it's really difficult when there's other people in the room to, to have that type of sensitivity to your intuition for sure.

[Dan Simon]

Can't read body language over the phone.

[John McMahon]

Right.

[Dan Simon]

I think, like, you can understand very quickly if you got a real deal or not just by looking at the way that the person reacts. You can ask them more direct questions. By being in person, they're going to trust you more. They're going to appreciate that you flew out to their HQ to meet with people for a couple of hours. Like, that absolutely differentiates you.

[John Kaplan]

Yeah. So Johnny Glean's going to be on one hand. They're going to be. They should pay us some royalties, bro. They're going to be really happy at how Dan represented the opportunity, you know, the company, the. And they're going to be a little nervous on Dan represented himself because I can't imagine your phone's not going to ring off the hook, dude, for the skill sets that you displayed today. Well done.

[John McMahon]

Well done. Great job, Simon.

[Dan Simon]

Thank you. I'm grateful that I got the chance to speak with you guys. Thanks for having me on.

[John Kaplan]

Yeah. Thanks for coming.

[John McMahon]

Thank you, Dan, Simon. Thank you, John Kaplan. Thanks to everyone for listening to another episode of the Revenue Builders podcast.

[Podcast Narrator]

Thanks for listening to today's episode. If you enjoy the content, please subscribe, rate and review the show to help us reach more people. This show is brought to you by Force Management, where we help companies improve sales performance, executing the growth strategy strategy at the point of sale. Check out forcemanagement.com for more information.