Enterprise Sales: How to Close Deals in 9 Days

Summary

The SaaS Podcast: Build, Launch & Scale Your SaaS

Episode 465: Enterprise Sales Strategy – Closing Deals in 9 Days | Briq
Host: Omer Khan
Guest: Basim Hamdi, Co-Founder & CEO, Briq
Date: December 11, 2025

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Episode Overview

This episode dives deep into enterprise SaaS growth and sales with Basim Hamdi, co-founder and CEO of Briq. Briq is an AI orchestration platform serving "physical industries" like construction and manufacturing. Basim shares honest lessons from the company's rapid pivots, painful layoffs, and achieving eight-figure ARR, all while resisting common enterprise SaaS pitfalls. The conversation is a no BS look at how founders can close enterprise customers in days (not months), avoid Frankenstein products, and leverage small, high-performing teams. Practical, hard-won advice and vivid war stories make it a must-listen for SaaS founders eyeing enterprise growth.

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Key Discussion Points & Insights

1. Briq’s Product, Market, and Evolution

[05:42–10:46]

• What is Briq?: An AI orchestration platform focused on automating workflows in physical industries (construction, manufacturing, infrastructure).
• Ideal Customer: Mid-to-large businesses (≥$50M revenue or 100+ employees; often CEOs/CFOs as entry point).
• Core Use Case: “Really Brick is human replacement software. ... It can move data around, enter data and act like a human as if you have half dozen extra employees. Because it works 7, 24, 365.” – Basim ([06:53])
• Industry Focus: 80% in construction; expanding fast into custom manufacturing, particularly for complex, custom-fabrication workflows.
• Trajectory: Eight figures in ARR, 100-person team, 3-year goal to hit $100M ARR.

2. The Founding Story & Early Pivots

[10:46–13:13]

• Initial “Construction Data Cloud” Idea: Aggregating legacy project data via APIs—a non-starter due to lack of APIs in old construction tech.
• Key Pivot: Discovery of RPA (robotic process automation) enabled scraping/automation without APIs; digital worker product quickly found product-market fit.
• Quote: “All of a sudden the digital worker was born and that was a big step forward for us.” – Basim ([12:37])

3. Fundraising and the Dangerous Temptation of the Pivot

[13:17–20:36]

• Fast traction: $1.5M ARR by 2020, without user logins; demand was all for background automation.
• Investor Pressure: VCs disliked that there were no daily active users. Pushed Briq to spin up a forecasting tool, which failed to meet market needs.
• Lesson: “We had product market fit and then refounded the company without product market fit in a product segment that was more art than science.” ([18:27])
• Came back to core automation mission just as AI orchestration understanding was peaking in-market—right move at the right time.

4. Rapid Enterprise Deals: Land, Expand, and Monetize

[20:36–27:05]

• Contrary to Popular Belief: Large enterprise deals do not always take 6–12 months—Briq closed some in as little as 9 days.
• Strategy:
  • Land and expand by “giving them that little base of value with a check, never do anything for free.” ([21:14])
  • Even token payments ($1) create buy-in and momentum.
  • Avoid innovation departments who want freebies; go direct to financial buyers.
  • “Fire the bad clients is as important as closing the good ones.” ([21:55])
• Speed Tactics:
  • Present micro-skills—small, concrete pain points (like double-entry data tasks)—with easily quantifiable ROI as the entry offer.
  • Examples: Automating double data entry during data center projects.
  • Sales focus: “Focus on vision alignment and value alignment. ... If they have a vision match ... do you want to do that? Yes, check. Do you see value in doing this? Yes, check. Vision, value, then talk about the solution.” ([24:37])
  • “Your deal cycles could be 24 hours because if they have a vision match ... vision, value, then talk about the solution.” ([24:46])
  • Avoid lengthy demos—most customers won’t know what they’re looking at anyway.

5. Navigating Enterprise Sales to CFOs

[27:05–30:04]

• CFOs as Buyers: Risk-averse, love price certainty, and demand trust.
• Objections: Security and pricing models (e.g., tokenization vs. consumption vs. flat-rate).
• Building Trust: Found partner associations for social proof before having big logos; leverage deep domain knowledge.
• Account Based Marketing: “I wrote a Book called the Book on Account Based Marketing. ... Understand your ICP, not just buyers but blockers too.” ([29:01])

6. Pricing Experiments and Mistakes

[30:04–34:00]

• Early Pricing: “How big is your company? ... This is bigger than a bread box.” Experimented widely, little science.
• Initial Prices: Sometimes as low as $15,000 per project—“Awful ... too cheap ... didn’t scale.” ([32:07])
• Unlimited Use v. Consumption: Unlimited-per-department worked for sales but killed expansion; now moving toward token/usage models with hybrid in future.

7. Frankenstein Risk: Pitfalls of Custom Enterprise Builds

[34:00–36:24]

• Building for One Customer: “When you’re building for one enterprise, n needs to be higher than 1 to build a successful product.” ([35:17])
• Innovation Groups: Often no budget or real power to scale; risk creating hard-to-sell Frankenstein products.
• Prefer Upper Mid-market: More engaged, collective steering committees, better for scalable SaaS.

8. Product Management: Saying No & Staying Aligned

[36:24–41:03]

• Only act on feature requests that align directly with core vision (“autonomous workforce for physical industries”).
• “When a feature request comes in ... and they’re not vision aligned with you ... that feature request gotta be turfed. ... When you have your vision internally, it's very easy to figure out which feature requests to do or not to do.” ([38:54])
• Listen to sales calls for true market signals, but be wary of “XY problems”—customers misdiagnosing their own pain.

9. Headcount and Culture: Productivity Over Vanity

[41:03–43:29]

• Briq scaled to 300 people, then pared back to 100, becoming healthier and more productive.
• “Throwing bodies at problems does not result in more code written ... or more sales. ... The flex should be revenue per employee.” ([42:19])
• Modern success = high ARR per employee; measure that instead of headcount vanity.

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Notable Quotes & Memorable Moments

• On Enterprise Free Pilots: "Never do anything for free. ... Even a dollar ... pot committed on payment ... fire the bad clients as important as closing the good ones." – Basim ([21:14])
• On Product Customization: "You're going to end up with a Frankenstein product ... you're solving for their problems, not solving for a holistic set of problems." ([35:13])
• On Speed of Closing Deals: "Focus on vision alignment and value alignment. ... Your deal cycles could be 24 hours because if they have a vision match..." ([24:37])
• On Handling Feature Requests: "If the feature request isn't aligned with your vision, then toss it." ([38:58])
• On Company Flex: "The flex should be revenue per employee ... that's my target." ([42:19])
• Favorite Inspirational Quote: “Go forth and crush.” – Basim’s Slack handle and motto ([05:06])

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Timestamps for Important Segments

• Briq product & ICP introduction: [05:42–08:10]
• Founding and pivoting for product-market fit: [10:46–13:13]
• Investor pressure, failed pivot, and return: [17:46–20:36]
• Closing 9-day enterprise deals (case study): [21:08–27:05]
• Trust and closing CFOs: [27:05–30:04]
• Pricing evolution and mistakes: [30:17–34:00]
• Custom builds and Frankenstein risk: [34:00–36:24]
• Saying no—vision-aligned product management: [36:24–41:03]
• Headcount, layoffs, and ARR per employee: [41:03–43:29]

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Lightning Round Highlights

• Best advice received: Sit at the engineer’s desk until your request is done—it’ll magically be done quickly! ([43:44])
• Book Recommendation: The Secret—manifest positivity daily. ([44:46])
• Key Founder Attributes: Hard work, natural curiosity, resilience. ([45:07])
• Favorite Productivity Tool: Plaud (clip-on recording and AI summary device). ([45:47])
• Dream Business Idea: Dog boarding (“boarding a dog right now is like going to a five-star resort.”) ([46:30])
• Fun Fact: Canadian who hates winter—loves California. ([46:56])
• Personal Passion: Family and dogs. ([47:18])

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Summary & Actionable Takeaways

1. Get Paid Early: Always charge (even small amounts) to accelerate enterprise buy-in and avoid wasted pilots.
2. Micro-Value Focus: Land enterprise deals fast by solving one acute, clearly quantifiable pain.
3. Fire Poor Fit Clients: Bad enterprise accounts are as dangerous as no accounts—know when to walk away.
4. Align Product with Vision: Ruthlessly filter feature requests by your company’s “north star” to avoid bloat and Frankenstein risk.
5. Leverage Domain Expertise & Social Proof: Win trust before you have logos; partner with industry orgs.
6. Optimize Lean Teams: Headcount≠success; track ARR per employee and strive for high productivity.
7. Iterate Pricing: Start simple, but keep evolving toward scalable, explainable models (e.g., usage-based).
8. Don’t Build for One: Mid-market clients and cross-company steering committees yield more scalable products than one-off enterprise builds.

For SaaS founders aiming for enterprise, Briq’s story offers a textbook case in tough pivots, fearless sales, and staying grounded in value—presented in Basim’s direct, pragmatic voice.

Final words: "Go forth and crush." – Basim Hamdi ([05:06])

Transcript

[A]

Foreign.

[B]

Welcome to another episode of the SaaS podcast. I'm your host Omar Khan and this is a show where I interview proven founders and industry experts who share their stories, strategies and insights to help you build, launch and grow your SaaS business.

In this episode, I talk to Basim Hamdi, the co founder and CEO of Brick, an AI automation platform for the construction and manufacturing industries. In 2018, after spending nearly two decades in construction tech, including a stint at Procore, where he helped scale the company from 10 million to 100 million in ARR, Basim set out to build what he called the Construction Data Cloud. The idea was to aggregate all project data through APIs. It seemed like the perfect fit, given his experience. There was just one problem. The software systems used in construction. With 30 to 40 years old, and none of them had APIs, his entire concept was technically impossible. Basim was ready to give up and go back to corporate life when a chance meeting with an engineer introduced him to Robotic Process automation, or rpa. These bots could log into legacy systems and and extract data without APIs. Suddenly, the business had new life. But customers wanted more than data extraction. They asked if the bots could also enter data. This pivot to digital workers found product market fit quickly, and by 2020, Brick had reached 1.5 million in ARR. Then came pressure from investors. VCs didn't like that no users logged into the product. They pushed Basim to build something with daily active usage.

[A]

So.

[B]

So Brick pivoted again, this time to a forecasting tool. But it was a disaster. Customers loved the idea of automated forecasting, but the product couldn't deliver on that promise. And less than two years later, they killed it and returned to their automation roots. As if that weren't enough, Brick had ballooned to 300 employees during the growth phase, and the large team created more problems than it solved. And Basim says they lost the plot. Painful layoffs followed in 2023 and 2024, eventually reducing the team to about 100 people. Today, Brick generates eight figures in ARR and is targeting to hit 100 million within three years. Basim is determined to replicate his Pro Core success, but this time as CEO. In this episode, you'll learn why Basim insists you should never do anything for free and how getting even a dollar from enterprise customers accelerates deal cycles. How Brick closed enterprise deals in as little as nine days, using a land and expand strategy focused on micro value. What happened when investor pressure led the founders away from proven product market fit and how they recovered? We talk about why building custom solutions for a single enterprise client creates Frankenstein products that can't scale. And how Basim now measures success by revenue per employee rather than headcount. And why smaller teams can be more productive. So I hope you enjoy it. If you're building an AI agent, a SaaS product, or stuck trying to scale, check out Gearhart. They can act as your fractional CTO and technical team, bringing AI expertise from projects for Meta and Google plus, strong Silicon Valley connections with founders and VCs. And since they're a Ukrainian born company, you get senior engineers with an offshore pricing model with offices in San Francisco and London, and a distributed team of 40 experts. They've helped build over 70 successful products. Right now, they're offering our listeners the first 20 hours of development for free. Just book a call at Gearhart IO. That's Gearheart IO. Most SaaS companies react to security breaches after they happen. Nordsteller gives you real time visibility into what attackers see. Leaked credentials, exposed assets, session cookies from malware, brand impersonation attempts built by the team behind NordVPN with access to one of the largest dark web data pools in the industry. Stop reacting to breaches only after the damage is done. Be prepared with Nord. Stellar. Visit Sasclub IO Nord to book a demo and mention code BLACKFRIDAY20 for 20% off. That's Sasclub IO Nord. You've built the product, you've got a few customers, but 10k in MRR still feels miles away and you're not sure what to do next. That's the hardest part of the early stage, not building, figuring out what actually moves the needle. SaaS club launch gives you a clear plan, weekly coaching and direct access to me. So you're not guessing anymore. Apply@SASClubIO launch. That's SASClub IO launch.

Basim, welcome to the show.

[A]

Thank you. Omer, how are you?

[B]

I'm great. How are you doing?

[A]

Very good, very good.

[B]

Do you have a favorite quote? Something that inspires or motivates you that you can share with us?

[A]

That's a great question. So when we closed our Series B, you know you get a lot of no's, and actually one of the big VC no's, the partner was so convinced of Brick's ascension that he said, I'm going to put in my own money check, which he did. And he wrote me a note that said, go forth and crush. And that's actually my slack handle. So it's go forth and crush.

[B]

Love it, love it. That's going to Be the most unique quote I've heard for a while. So tell us about Brick. What does the product do, who's it for, and what's the main problem you're helping to solve?

[A]

So Brick is an AI orchestration platform. We really focus on robotic, which is deterministic and problemistic AI solutions to solve major work streams in what we call the physical industries. So a physical industry just to start off is anybody that takes raw material and turns it into a product, takes a thing and makes stuff. You know, that stuff could be a product that's manufactured, usually custom manufactured or fabricated. It could be a bridge, a road, a data center. It could be a school, a hospital. It's anything in your physical environment. We don't sell to software companies. That's kind of the one clear path. But we'll sell to folks that, you know, do the hard, dirty and dangerous work. You know, it sometimes sounds inhumane to say this, but really Brick is human replacement software. But generally our clients are growing. So if a client is scaling in an industry that's a little less sexy and, and you know, B2B people on this call.

Take this to heart. Unsexy industries are sexy from a go to market perspective.

They can't get enough white collar workers in accounting, in business development, in operations. It's just there's not enough people joining these industries and they use this AI technology to log into their archaic solutions, create Excel spreadsheets, you know, go through and generate data, access data using this AI orchestration layer so it can move data around, enter data and act like a human as if you have half dozen extra employees. Because it works 7, 24, 365. So that's really what we focus on. From a ideal customer profile, it's really anybody doing over about 50 million in revenue and or somewhere around 100 plus employees, we usually see fit there. And then obviously it scales up to billions of doll in revenue. We have some very large Fortune 1, hundreds on brick and then we usually come in through the office of the cfo. But that has been changing as AI has been talked about. And basically our machine used model, it's different than say anthropic, but now people know what a machine use model is or a computer use model is. So we're seeing operations and business development as also our gateway in. So we have, you know, CEO or CFO is really the, the core entrance.

[B]

Okay, great. And what are the top two or three verticals for you today with your business?

[A]

We're still highly construction oriented. We started in construction I would say that's about 80% of our client base. I think it gets hard to describe to people that don't live and breathe construction what that means. I think a lot of people think of construction and they think of commercial construction. Whereas, yes, that is a portion of our business. But the vast majority of our business are doing bridges and roads, infrastructure, data centers, power generation, solar.

All the way to mechanical and plumbing contractors that do major work. So when we use the term construction, it means a lot of different things, not just the big buildings you see in New York. Yeah.

[B]

And then beyond construction, what are your favorite verticals that you're targeting?

[A]

Right now the fastest growing one is custom manufacturing. So you're seeing a lot of synergies with companies that are fabricating things. One of the largest steel fabricators, for instance, runs brick to automate their drawing management tools. So essentially they get a lot of custom orders and they need these specs and drawings to be generated and viewed and analyzed for manufacturability. And so they use our tools to do that. So it's like an expert drawing manager, if you will. So we're seeing a lot of success in that fabrication, custom manufacturing area.

[B]

So give us a sense of the size of the business where you in terms of revenue, number of customers, size of team.

[A]

Yeah, so core product or AI orchestration product is eight figures. So we have kind of crossed that, that bridge from zero to one to one and up. Now we're focused on a three year plan to get to 100 million. That is the big audacious goal. And I think my history people, it might sound silly to say this, like 100 million seems unattainable, but when I joined Procore, which is a cloud based project management solution, as head of go to market, as I was EVP of marketing and strategy, we did that. We went from 10 to 100 and that's kind of that, you know, I want to break through and do that again, not as go to market, but as CEO. So I'd love to be at the helm to do that. And so that's where we're trying to get to.

[B]

You've had the taste of it once and you want more.

[A]

Not easy, but we'll get there.

[B]

I hope so. Let's talk about the idea. Where did the idea come from? What were you doing at the time? I think this was. You founded the business in around 2018?

[A]

Yeah, we're an older vintage, I would say, so, you know, 2018, I came up with this idea that I thought was fabulous. This is a great idea. It turned out not to be a good idea, by the way. So the idea was something called the construction data cloud. And we, I just, you know, I had just done a lot of API work at Procore. I just came off of going to markets with marketplaces and I'm like, APIs are everything we're going to be able to. And this was the theory be like the car facts of an asset, a physical asset. So everything that's ever happened, you know, the plumbing contractor, the electrical contractor, the GC material tickets, what was delivered, what was installed. And I thought, this is going to be great. So we actually started building something and we had this kind of ontology data model of asset to the components of that asset and then came filling in the data model, which is a problem because all the software in the industries we're serving are like 30, 40 years old. And, and there are no APIs. So I'm like, well, that was a quick business, I guess I'll go back to work. But I ran into an engineer and I was just like hunting and pecking and found this guy who's still with us, Ash Kapoor. And I said, hey, how can we access data without an API without trying to understand a database? And he, at the time, 2018, we called a robotic process automation. I didn't know much about it, but I knew about bots making, you know, harder to buy Taylor Swift tickets or whatever. And so he's like, let's try it. And eventually.

Today we've taken what we originally built in 2018 and created a computer use model that navigates. When we thought, okay, we are going to get this data, this is kind of the right turn we took. People were more interested, wow, you have something that can execute against 30 year old software. Does it enter data too? And we said, yeah, it does. So all of a sudden the digital worker was born and that was a big step forward for us. We found product market fit very early on, this concept of a digital worker in accounting initially and then operations. And so that was great. And I can tell you, I think we talked a little bit about this, the left turn we took after that, but that is where the idea was generated and that, that's the story of Brick today.

[B]

Did you know who your ICP was at the time? Like, how clear were you?

[A]

So that's a great question. So ultimately, you know, my history was always in this construction space, right? So my first 15 years with a construction ERP solution, the next three to four was with a project management solution. So I Kind of had it in the blood. So I said, I know my tam. I know my addressable market. I'm very familiar with it. I have connections in it. I'm not a young founder. So, you know, I had some history. And that's why we chose the industries we chose initially. It was easier to get broken in, right? So, you know, like, our first real robotic process automation was on, you know, a very large social media company and a very large general contractor that I happen to know installed our robots on a data center project. That was like the first thing that we really got off the ground. So I chose it or it chose me. I don't know one way or the other, but I chose to go through our icp. Now, I made mistakes on our ideal customer profile because of my experience bias. And I think that's one thing that if I could have done differently, my experience bias stated that I should go after general contractors. Basically, the big companies that run these projects. What I didn't realize is they don't really have a labor crunch as much as the specialty contractors that do the mechanical, the electrical, the plumbing, you know, the site work. That was a big surprise. So what we realized was, you know, know thyself. Our ICP shifted quite significantly from what I thought it should be to what reality was as we commercialized.

[B]

How many conversations did you have with potential customers when you were building that first version of the product? Because you have a lot of history, which can be, you know, they say it can be a curse, right? Because you know a lot already. But how much was it like, okay, I know the problem, I know the solution, let's build it versus let me go and talk to as many people as I can.

[A]

I'm a big advocate of building the plane in the air, and that could be crazy, but.

People always say, hey, we're agile, we love agile. And then they're like, when you talk to them, they're really waterful. And agile means giving this much that does this much, not giving this much that does nothing. And if you're like, hey, do you want to move one document type from A to B using a robot? Yeah. Okay, let's create that one little thing, that micro step that's meaningful but easy. And I think what we did was we tried a lot of different things. Oh, my God, did we try a lot of different things. I think what's different about scaling an AI company today versus a software company is we could try things.

Without a user interface very easily because.

We wanted to be autonomous. We didn't want users logging in. So that made our story a little easier. Now with things like replit and lovable, like if you're creating a true software company, not an AI company, you can create prototypes, functioning prototypes that store data, that have authentication, that look production ready and try things. And I think what we've lost in product management is that go fast and break things concept, which is we do a lot of interviews. We, you know, I think it was Marty Kagan or one of the product management schools. They're, you know, what problem are you solving? And then you talk to some of these younger project product managers and they're not, they're not doing anything, they're just writing notes and it's like, build something. And now that anybody can code build something and try it and show it and get them to use it and watch them use it. I think a lot of this product management generation today kind of annoy me because it's so theoretical. And you just want to be like, hey, SAS software is a full contact sport. If you're on the sidelines too long, you're out of the game. Get off the bench and get into the game. I would say so.

[B]

You sort of alluded to this about this left turn that you took, which I think was around 2020. How much traction had you gotten by that time? Or was it you were still trying to find traction and that's the reason you sort of took this left turn.

[A]

We got zero to one pretty quickly actually. We're probably one and one and a half in 2020.

[B]

1.5 million ARR in ARR.

[A]

And we were like loving it. We never had anybody log in. We never wanted anybody to log in. There's all these robots working in the backgrounds that we started to commercialize and we fundraised and that story. And they're like, well, rpa, not that sexy. We're not that interested. You gotta find some part of the product that can have people log in. When we say no, we don't want daily active usage other than the robotic usage. People were like, you're crazy, you have to find a product. And we were lucky enough to be in that kind of roaring twenties moment where it was a little easier to fundraise. And so we, we said, okay, here's this robotic product, this automation product. But inside this automation product we started to see some traction around forecasting. And it was actually a pretty clear cut view that there was no competitors in that forecasting world. And we're like, okay, that's interesting. Great, let's go with that, so we built a forecasting tool that kind of looked and felt like Excel. And what we realized is we had product market fit and then refounded the company without product market fit in a product segment that was more art than science. And when we say art, it's like you're forecasting, you know, what's the forecast? It's an Excel tool with very little ability to automate. And so what we ended up doing less than 24 months later is discontinuing that product. The interesting part of that is we fundraised on it, yes, but we also sold a lot of it. People want, wanted the promise of automated forecasting, but when they saw the sacrifices you need to make in automated forecasting, which is, it turns out forecasting is just guessing, from what I could tell.

They wouldn't want it. So we had this product market fit. Then we took a left turn and created this new product mainly by the pressures of the investment market, not the market itself. People love the automation platform. And so we returned to our roots and lucky, you know, good to be lucky, Lucky to be good. It was right at the intersection of people understanding what AI orchestration is. And so that's when we doubled down, built our, we call it a large action model which we call auto that, that learns, that speaks, that talks to the, the industry and has computer use for these archaic client server type solutions that nobody else has. And so we have that competitive moat and that's where we came back to our roots.

[B]

Now many founders who start to get into the enterprise space from day one, the biggest fear is, you know, it's going to take me 6 to 12 months to close a deal. I have 0arr, I don't have any logos, how the heck am I going to close a deal? And you, you were able to close some deals in as quickly as nine days with enterprise customers. So tell me, tell me about that. Like how were you able to do that? What was the pitch and why do you think you were able to be successful with that?

[A]

I think, you know, from a go to market it's all about land and expand. If you can give them that little base of value with a check, never do anything for free. I think that's one thing that, you know, founders learn very quickly is that, you know, I see this a lot actually. So we do some mentoring with like younger entrepreneurs and you see them going in and saying, hey, I have this huge company, they don't want to pay us. I'm talking to the VP of innovation and they want to try stuff and you're like, you run out of the room screaming because you're a, you're not talking to a financial buyer. They're going to drag you in dark alleys a lot of times because they have all these like shiny objects they want you to fix and at the end of the day they're not paying or paying enough for your time. So I see these people go out and say, yeah, I closed Bechtel or I closed, but you didn't close them. You're just talking to an innovation guy that's wasting your time. So I think never do anything for free. Give them a little bit of value that they're willing to pay for even a dollar because as soon as they're pot committed on payment, they're going to really try to use what you have. And then finally, like with Enterprise specifically, fire the bad clients is as important as closing the good ones. Because like I said, a big company is as likely to put you out of business as well as put you on the map. So from my perspective, I'd say think all about land and expand. Sell to the user or the group that sees an ROI in your solution, especially in the B2B space and then ultimately go into.

Analyzing that client very quickly to make sure that they are really an icp. I think one of the challenges people have on closing big deals is can I get this solution in that does XYZ for a million bucks. And I think you gotta work your way up there. I mean like we just started probably last year, just started metricing deals of over 100,000 per year as like one of our core metrics. So it's a, it's a, it's a, it's a journey. So don't expect that big enterprise client to just pay you a million bucks day one.

[B]

So give me an example of a deal that you closed in in nine days. What, what like how did it start from day one and how did you keep things moving and getting to close so quickly?

[A]

Yeah, so we, we have a pretty standard deal demand gen to BDR to AE model. And you know when we say start small, we have AI that allows people to coordinate with third party systems owned by somebody else. So just imagine you're being asked to build a data center and as that part of that data center project requirement, you're being told you need to log in to this other person's system and add data to that system so they can have a data store of all the things that are happening. So for us it was very easy to Come in and say, hey, do you like doing that? And the answer is no. So it's like, okay, let's get through that. So when the demand gen starts.

We talk about this micro skill, I call it this small thing that we can offer them and we can say, hey, in exchange for this thing, do you want this? And the answer is yes. It was invariably yes, if you like. I think the problem with, you know, certain products is you can't define the roi. And so for us the ROI was they were going to hire a person to do the double date entry. That was really easy. Yes, that is a simple ROI or ROI has gotten more complex now. But if you can't say this is what you're saving concisely, if you're focused on demoing a product or explaining the product or if you're in love with your own tech, which you know, a lot of people end up being in love with the tech, not the money, you're going to have a problem closing any deal. So what I say is focus on vision alignment and value alignment. And your deal cycles could be 24 hours because if they have a vision match, what is your vision? If our vision is to automate physical industries where there isn't enough white collar workers, do you want to do that? Yes, UK check. Do you see value in doing this? Yes, check vision value, then talk about the solution. I think too many people in enterprise or even in mid market try to focus on the software. I could demo a blank screen. Like it doesn't matter what's on the screen, they don't know what you're demoing anyway. Like they've never seen your product before. They was like squinting, they're looking at a zoom. Focus on vision and value and you can close very, very quickly.

[B]

So it sounds like with these guys, instead of going in with some big product vision and telling them you can do these 25 things, you just focus on that one pain which was do you like updating this data on a regular basis? Yeah. And the value was okay, we'll give you that piece and start, help you start updating. And once they get a taste of.

[A]

That, the key is I think in a lot of when you're short staffed, I think a lot of those early, you know, baby steps may have partially been squandered because we didn't have people, enough people on the account management side to come in and start expanding them. And so I think don't, just don't forget the expand and land and expand. That's I think one of the lessons. But land and expand is, from my perspective, if your product lends itself to land and expand, that's got to be the gtm because that gives you the ability to go in and get paid, get that dollar. I cannot stress enough, a POC with an enterprise client is a waste of your time unless there's a dollar or some amount attached to it.

[B]

So you decided to focus your ICP as CFOs in these companies.

Traditionally those guys tend to be pretty risk averse. So going in with a new product.

What kind of objections did you face and how did you get over that first one?

[A]

Always security. Security, security. That was the, you know, CFOs in our industries generally run it as well. So there's that real question of like, how secure is this? The other thing is they're not just risk averse, they are.

Spend averse. I'll put it that way. They love certainty. So, you know, we, you know, we have a tokenization model and accountants, we've just recently gone to consumption and the accountants, you could see it on their face, they hate any. But how many tokens is that going to be? How many? Like I don't. And we're like, well it'll be approximately this and it'll be this much per month. And they're like, I can't. So you know, I think they love price certainty. But the nice thing about going after the cfo, they also write the check. So they are the economic buyer generally. So that is kind of the gateway in. But there are so many things that you have to do in order to earn. You know, we talk about vision, value and then solution. There's a kind of a middle layer that a lot of people, you know, feel uncomfortable talking about, which is trust verification.

You might not have a lot of logos, so you have to earn the trust some other way. And either that's domain expertise or expertise on the type of business they are, or it's technical expertise giving them something they don't understand how to do themselves. That gives you that added trust. So yeah, it's vision and value, quick, close to deal once the solution is verified. But in between that is Trust. With CFOs, you're right, the trust metric has to be high. They have to trust and believe in you. And the way we did that was partnering with a lot of the financial associations in the industries we served because that provided that kind of social proof. Before we had a lot of logos. So that was really kind of core to our go to market. You know, I wrote a Book called the Book of the Book on Account Based Marketing. And it's just all about going in and talking about account based marketing, understanding your icp, understanding who your ideal customer profile is. Not just the people, people that come in and the Personas that are going to buy you, but also the ones that are going to be the blocker. And I think going through the exercise of saying what is my true ICP or target and it's going to move and shift over time and what Persona is going to hate me and what Persona is going to love me when I'm selling an account? So that's kind of the core of how we did it.

[B]

And you were selling a product. There was no precedent. It was basically like a new category for these companies. How did you figure out the pricing, what to charge?

[A]

We're still working on it.

Pricing is always kind of a moving experiment. I feel like more so with us recently. But you know, at first we would just say, how big is your company? I mean, this is not the most scientific way and said, you know, okay, this is bigger than a bread box. And we just tried a bunch of different things. If you look at our early paper, it's like all over the map, right? So there's so many different pricing models that we experimented with. Looking at Velocity, you know, how are they retaining, are they expanding? So, you know, it's just. I wish I had a better bulletproof answer for this, but pricing is just always a challenge in our technology world because first of all, in tech, gross margins are great. So you're not like building a widget and then shipping a widget and you can say, oh, I want to be 30%. Most tech companies are 80, 90% gross margins. So you're thinking, okay, I can charge anything I want. And that flexibility lends itself to a lot of experimentation. I think we finally nailed it. I think we did by more akin to how like a ChatGPT charges, which is token usage, or maybe how an AWS charges, which is about computer use or compute power used. So that has provided an easier way of explaining things. But I'll tell you, pricing modeling never stops. There's entire companies out there that do experimentation on pricing. But I wish I had a better answer to that question.

[B]

I'm curious.

What was your first price to a customer and how wrong did you get that?

[A]

Oh, it was awful. It was like $15,000 for a project or something. It was like some, just like it was too cheap. It didn't scale, didn't allow for expansion easily. And we just like, we need money. How much are you willing to pay? I really took to heart, give us whatever you got in your pocket and you can have this. So that's how it started. And then we started getting a little bit more scientific where we started to say, hey, let's base this on the size of the company and the amount that will be a doppelganger for the amount of volume we're going to see. That's really, you know, if you have 100 employees, we kind of know what your payrolls look like or what your AP looks like. So we're going to use that as the doppelganger. And then what we did, which was a very successful pricing model, but not a great expansion model, which was unlimited. Unlimited. Unlimited within a department or domain within that company. Now. Very easy to explain. Very easy for a salesperson to explain, hey, don't worry about it. You buy it for the AP department. That's what you're getting. It's 25,000, let's say, because you're 100 employees. Unlimited. Unlimited. Unlimited. The challenge there was when we went to expand, we couldn't go to, like, it was hard to go to the next department to resell them that solution. And they're like, it's not, you know, I don't know. You know, Chuck runs ar. That's not my area. So, you know, it's like a brand new sale all of a sudden versus now with tokenization and consumption modeling, there's no limit on what they can do. They just pay per minute, you know, and so we've gone both ways from unlimited to consumption. I think what will happen next year, I think you'll see some sort of hybrid of that. If you commit your use, you'll get near unlimited based on the domain. But yeah, we got wrong a lot.

[B]

When we were talking earlier, you were telling me about how often founders, one of the mistakes they make is going in and working with one customer and effectively building a custom solution for that customer. And it sounded like you in the early days ended up doing the same.

[A]

Thing a little bit. I think I learned my lesson quick.

Because they weren't paying right. There was no real money associated with it, or the money looked more like services than they did a recurring revenue number. Actually, in some of those cases, we should have booked them as services. We thought they were buying our product, but they're like, yeah, we like your idea, but we wanted to do all these different things that it didn't do yet. And in some cases, those partnerships can be great. And in some cases they were very good. They gave us access to domain expertise and use cases that we hadn't thought of, which is fantastic. But in some of those cases, when you're not talking to the business users.

Whether it's IT or innovation or the experimentation department.

They don't have as much skin in the game, in the business as you think. And so getting in and going into the front door of an innovation group and saying, hey, this is the kernel of our product now help us build out the rest of it, you're going to end up with a Frankenstein product that is probably very hard to sell to the next client because you're solving for their problems, not solving for a holistic set of problems. And I think that's what ends up being, you know, I, I always say n equals 1. When you're building for one enterprise, n needs to be higher than 1 to build a successful product. So if n equals 1, you got a problem. And, and I think we learned that and what we were able to pull out of that quick. I love mid market, like we call it the fat middle, like upper mid market, like you love those hardworking companies, they're the ones that will join multiple clients on a steering committee to give you great advice. So just always be wary. I see some of these startups that have just gotten funded in the AI space announcing, oh, some agreement with a massive company and I look at it and I go, maybe a good idea, but odds are it won't work out.

[B]

So it sounds like you learned your lesson pretty quickly. And when it comes to finding product market fit, I came across a quote from you, I think, where you said if you try to do everything, you end up doing nothing. And so I'm curious, like, how did you figure out what feature requests from customers to say no to? And even better, is there an example of a feature request that on the face of it seemed to make a lot of sense, but you're really glad you didn't end up building it.

[A]

Sure. I think you know, the, the answer to product management is like, what problem are you solving? Right? And I think clients, people that are in it every day, have real issues.

Defining their problems. I call them X, Y problems. You know, they're asking for if you, if you Google Search or ChatGPT, what is an XY problem? It's the idea that, you know, they're defining the problem set in the terms of their own mind. And you're, and you're trying to solve a problem that is the wrong problem to solve essentially. And so you, when you interview a client, you know, what are your problems? You know, where are your issues? Where do you see that bottleneck? Never take their solution. You have to define their solution. So feature requests from a client.

Require real serious digging. Like, real serious digging, because they're going to define something myopically, like touching the elephant. They're only going to understand the tail. Let's say you got to define the whole elephant. And, you know, I was lucky enough to run product very early in my career at my first company that I worked for. And so I got to learn that very much, you know, again, the hard way, and see that, you know, we are. We're solving for a problem that the client thinks they have. They get that solution. They're like, this isn't my problem. So, you know, I call it like bandages on bullet holes. It's like, you're solving the right. You solved the wrong problem. So I don't take feature requests at face value. You look at the feature, why are they asking for it? Is the first thing I would say. Why are you asking for this? And one of the things that I think I learned not to say no to is I have this idea of the autonomous workforce for these physical industries. I want to be the Roomba of the. I want to be the Waymo of the Roomba, not the vacuum cleaner or the Ford. I want the thing to run by itself in the background. That's been my vision from day one. Took a left turn as we talked about. But when you have your vision internally, it's very easy to figure out which feature requests to do or not to do. And when a feature request comes in, like, I want to be able to stop the AI autonomous workforce to check in on them every once in a while, you know, they're not vision aligned with you. And that feature request gotta be turfed. So I think everything needs to be in the light of what is the shining light. What is the big audacious goal of your company? Mine is to have, you know, millions of autonomous workers running these companies. If the feature request isn't aligned with your vision, then toss it. Not to make it sound easy or callous, but I think it is easy when you say this vision, this request don't match. And I think that's how. That's how we do it. Now.

[B]

Did you ever lose any deals because you didn't have a feature a customer or a potential customer wanted?

[A]

Always. I mean, like, yeah, it happens daily.

They also might say, hey, this is a great new feature, and that's where a lot of good ideas come from. Because if you know, I can't stress enough like I was lucky enough to be like a go to market CEO, product sales, marketing. I'm non engineer so I get on a lot of sales calls. I think the sales calls are great to hear what the. It's one very, very important input of what the market is saying right now. It's like find out what the prospect is asking for and again be careful in X, Y and non visual line feature requests. But if you lose a deal a couple of times, that's when you know you should build that feature. So yes, it happens all the time, but it's a learning lesson. It's actually a great thing because you didn't have that feature. Maybe you needed it or maybe you didn't so you'd have to make that decision. But yes, all the time.

[B]

You and I were talking earlier about like, you know, the number of employees used to be the thing to flex about and it isn't so much today. And it reminded me of conversation I had with Adam Robinson who runs retention.com and he was at some, some party and there was some like startup folks there and a woman asked him what he did and then I think the story was basically like how many employees you have. And you know, he has a very healthy, you know, multiple seven figure business at a time. But he said like you know, 15 people or 20 people. And he said I'm not interested in talking to you. She's walked off kind of thing. So it was like you got to be. Yeah, I got to have like thousands of people. So it sounds like you went through a similar thing in terms of. Just tell me about what your experience has been like.

[A]

I mean we ballooned to 300 employees and what that did was just breed more and more problems. We're down to 100 now and went through the typical RIF process in 23, 24 just like everybody else did to get to very, very cash efficient which is a requirement to fundraise now. And.

What you see is extremely healthy. A much healthier company throwing bodies at problems does not result in more code written or in some cases more sales. I gotta give it that. But, but you're not going to get a lot more productivity out of people. And actually the more hands in the pot we found that we lost the plot and you get further away from the problems and further away from the solutions when you have so many bodies in between you and the problems and solutions. So I do think it's, you know, the flex should be revenue per employee. Like if you can say ARR. Per employee, that's the Flex. 100 grand, that's. That's my target. A hundred grand. Whatever the market say, states, that's really the flex. But I do agree with you. At coffee or at parties or, you know, they're like, oh, how big is your company? Is part of the discussion. And people don't like talking about money, so they use people as a doppelganger to that. But the reality is being a great, efficient company, eating your own dog food on AI, making sure that you're writing code, using AI, or doing everything you can to be more efficient, that's the flex today.

[B]

Yeah, totally agree. Okay, let's wrap up. Get onto the lightning round. So I've got seven quick fire questions for you. What's one of the best pieces of business advice you've received?

[A]

So in my, my first job running product, you know, I was in there and I said to this engineer, I need this little feature. I thought it was like, wrote it up really nicely. They said, that's going to take two weeks. It's going to take a sprint. And it was like adding a field or a dropdown. So my boss at the time goes, move your chair next to the engineer and tell them that you're going to sit at his same desk every day until it's done. And it was done within an hour.

That was the car.

[B]

There's a great ad I saw with. I think it was for. Was it for upwork or. I can't remember. I'm going to get creative and somebody's asking for a feature and the, the guy saying, yeah, maybe we'll get to that in Q5. I was like, hilarious.

What book would you recommend to our audience and why?

[A]

I stopped reading business books to a large extent, I have to be honest, a lot of them have just kind of got bogged down and in all this, you know.

Super business speak. But, you know, I do subscribe to manifestation. I love the Secret. I really do think that it's like being spiritual is part of, like having this job. You gotta, you gotta manifest positivity almost every day. So I, I'll throw in the secret.

[B]

Love it. What's one attribute or characteristic in your mind of a successful founder?

[A]

Oh, I, I think there's a few. Hard work, natural curiosity.

You know, I think hard work is probably the biggest statement. But natural curiosity, a desire to learn all the time, because you are learning. And, you know, I call it the scars on the back to show like you're going to get the crap eaten out of you in a lot of cases. And so having that natural curiosity, that optimism, that idea that you are going to get yourself back up and that hard work is, it is hard work. Those are the attributes I think make a great founder.

[B]

What's your favorite personal productivity tool or habit?

[A]

I found that recording myself rather than taking notes has worked. So I use something called Plod, which is like a little clip on mic that you can talk to yourself and it'll transcribe. Uses some AI, the basic AI. I find that better than taking voice notes because it does a little bit more analysis and like you're more in the moment. You could just like pop it on and then freestyle. So I've been using that a little bit.

[B]

So Claude liked the anthropic.

[A]

Claude. No Plaud P, L, A, U, D. It's like a, it's a tool that you just kind of have a microphone with it and you talk to the microphone or you can clip it on like this little thing and you can just start talking.

[B]

Pretty cool. What's a new or crazy business idea you'd love to pursue if you had the time?

[A]

Dog boarding. Because I just got a large dog and I never realized we always had small dogs which are like cats. Like you don't have to worry about boarding. Somebody's going to take them. Large dog nobody wants to take and then you have to board them. And like boarding a dog right now is like going to a five star resort. I don't know what's going on with this pricing but yes, let's do that. We should go into business together and dock board.

[B]

What's an interesting or fun fact about you that people don't, most people don't know?

[A]

Fun fact? I. I'm very open book. So like if you read anything by me or you see these interviews, I'm all always very, very open. I think a fun fact is I'm Canadian but hate winter. So I don't know if that's a fun fact, but I love California. I hate winter.

[B]

And finally, what's one of your most important passions outside of your work?

[A]

Family. I have a 12 year old, my wife and I, three dogs now, three crazy family and my child. That's the passion.

[B]

Awesome. Well, thank you so much for joining me, Basim. It's been a pleasure. If folks want to check out Brick, they can go to Brick. That's b r I q.com or AI. And if folks want to get in touch with you, what's the best way for them to do that.

[A]

Brick.com. it's easy. The letter brick.comv R I Q.com.

[B]

Well, thank you so much. Congratulations on everything you've achieved so far. And I wish you and the team the best of success as you work towards that 100 million ARR goal.

[A]

Go for it. Yeah.

[B]

Awesome. Take care. Cheers. You're putting in the hours, but your SaaS isn't growing. It's not your product, it's not your pricing. It's the way you're wired as a founder. And once you see it, everything changes. Every founder has a blind spot. The builder ships great code but forgets to sell. The visionary chases big ideas but can't execute. The optimizer tweaks endlessly instead of finding customers. Which one are you? I created a free quiz that identifies your founder archetype and gives you a specific playbook to fix what's holding you back. Take the quiz at sasclub IO Quiz. That's sasclub IO Quiz. The playbook that got you to six figures in ARR won't get you to seven figures. And at this stage, you don't need another course. You don't need more content. You need clarity and you need people who get it. Because right now you're probably second guessing every decision, wondering if you're focused on the wrong things. Working harder but watching revenue flatline. SaaS club mastermind is how you get there. A small group of founders all scaling to seven figures with Mastermind calls and direct access to me. Think of it as your board of directors without the drama. Apply at SasClub IO mastermind. That's SasClub IO mastermind. I've interviewed over 450 B2B SaaS founders on this podcast. Success leaves clues and I've been taking notes. Every week. I send out the shortcuts, the blind spots and the tactics that actually work so you don't have to learn everything the hard way. Over 5,000 founders read it. You probably should too. Sign up free at SasClub IE newsletter. That's SasClub IO newsletter.