As interactions between businesses and customers increasingly take place online rather than in-person, there has been a growing need for technology to extend the capabilities of the best-in-class sales and customer service agents.

Seeing the limitations of AI that simply automated the routine aspects of work performed by many, Cresta developed a platform that effectively scales the skills of the top few employees, whose job functions require heavier cognitive lifting and expertise. The company, which emerged from stealth in February with a Series A led by Greylock, developed an AI platform that analyzes conversations and provides contextual, experiential learning-based prompts that allow any employee to deliver expert-level service at every customer touchpoint. Cresta now works with customer service divisions at companies such as Intuit, Dropbox, and Porsche, and recently raised a $50 million Series B led by Sequoia with participation from Greylock, Andresseen Horowitz, and others.

“We believe that technology should be a building block to unlock human potential – not replace it,” says Cresta CEO and co-founder Zayd Enam, who formed the company in 2017 with fellow Stanford AI researchers Tim Shi and Sebastian Thrun. “Three-quarters of the office-working world is doing non-cognitive, routine work, and it’s the kind of work that’s really dying for artificial intelligence to help amplify the operation, amplify the experience, and amplify the expertise of the best people on a team.”

Enam recently sat down with Greylock partner and Cresta board member Saam Motamedi on the Greymatter podcast to discuss the company’s progress, their plans for expansion, and how AI is helping – not replacing – customer service reps. You can listen to the conversation here.


Episode Transcript

Saam Motamedi: Zayd, I’ve really been looking forward to having you on. You and I have been friends I think since 2015, and I remember the first time we met. It was just extremely evident to me that you’re one of the few people I wanted to spend a long time working with, and it’s been a privilege to be partners with you and Cresta since 2019.

I think there’s a range of interesting things for us to talk about today. It’s an exciting week with Cresta, with the company announcing their series B fundraise. I’d love to let our audience learn a little bit about the company and what you’ve done to date and your plans for ahead.

The second piece I’d love to talk about is the future of customer experience and how that’s changed following the COVID-19 pandemic, and the role Cresta plays in helping companies enable omni-channel digital customer experience. And then I’d love to talk a little bit about how you think about company-building, but let’s just start with you and with Cresta, and maybe spend a few minutes introducing yourself and introducing the company.

Zayd Enam: Yeah, absolutely. So my name is Zayd and I’m from Pakistan actually. And I ended up in California with a very lucky set of coincidences. So I was working on a project (an open source project in Pakistan), and as part of a competition released it. And I got this offer for an internship at a startup down in Southern California. So I went – way back in I think 2006 or seven for an internship there, and I guess they liked my work enough that they gave me a year or two years [position]. Later, a few of the folks there spun out a company and they gave me a full-time offer to come back.

And so that’s how I ended up in California and I’ve been in California for about probably 10, 12 years now. I basically ended up taking classes in junior college in SoCal, went up to Berkeley and studied engineering, CS and neuroscience there and then got really fascinated by the brain.

And so I had this questions of, “Hhow does the brain work? Why does it work the way it does?” And that led me into this whole thing about machine learning and artificial intelligence as a way of understanding the brain, understanding how those things work. And so I ended up applying and enrolling at Stanford for the PhD where I met a troop of really just amazing, talented, crazy, unique idiosyncratic people. Just very talented people. And yeah, so then we dropped out about three years into the PhD and started Cresta and that’s been the journey so far in the United States.

SM: Yeah. Fantastic journey. Tell us a little bit about Cresta.

ZE: Yeah. So Cresta started with this idea. I was in the Stanford artificial intelligence lab working with my co-founders Tim [Shi] and Sebastian [Thrun], and Sebastian had come back from building the self-driving car unit at Google and starting Google X and Udacity. The whole view of the lens was that it seems like the whole world right now is focused on artificial intelligence as a form of automation. And so how does it do anything a human does, but how do we automate it? And there’s folks that have this heuristic (or principle) way of thinking of artificial intelligence and the impact it will have for your business as anything a human can do in less than one second.

And our view was like, that’s just such a narrow focus of artificial intelligence. Because if you look back at technology – and the impact technology has had historically – it has obviously been a building block to help us achieve bigger things.

[For example], the phone makes us superhuman; it helps us. We can pick up the phone and talk to someone in Australia. Take the computer: Steve Jobs famously said it is like the bicycle of the mind. These things have always been building blocks that have unlocked our capabilities and unlocked our full potential.

And so what we felt was there’s this really lazy view of artificial intelligence which is, “I’m going to go automate anything the human does existingly,” and we want it to go approach with a creative view of artificial intelligence. And we thought it was our responsibility and ultimately that led to our developing and to building out our artificial intelligence [tools] where that can happen.

So we looked at a lot of different places of work and where artificial intelligence could help people be better. And there’s actually a lot of applications for it and huge amounts of applications. But one of the things I remember from looking at one of the data sets, is that you look at the number of people doing types of work in office – knowledge work, which is cognitive, non-routine work – and cognitive routine work, and it’s basically you have three quarters of the world in this type of work. And it’s the kind of work that’s really dying for artificial intelligence to help amplify the operation, amplify the experience, and amplify the expertise of the best people on a team. That’s what we really look for.

We originally started with education. So obviously being PhDs and a professor, we were like, “Okay, where can we have this biggest impact?” Well, we hate grading papers. So we started working on using artificial intelligence to help people – we can do it for ourselves and help grade papers better.

And so we started with a computer science class where we trained an AI that would basically learn from the graders and the TAs in the class, and then it would identify the mistakes that students are making. And the mistakes are common year over year; the same mistakes happen to the class. So it turns out in our experiments that we were able to double the speed of a grader and also improve the overall quality of feedback that the students gave back to the TA.

And that was like, okay, clearly there’s something here. There’s a technology that you can leverage that can make people better. And it was basically giving responses like: here’s the feedback given to the student, here’s how to grade the assignment, here’s what the mistake is, here’s the best way to coach the student on this solution.

So we looked at it and we examined it and said, okay, this is a neat piece of technology. But then when you try to see what was the market for this, it was clear that there’s not, unfortunately, a large market. That’s a topic that I guess is worth a deep dive by itself – the education market.

But we then looked, okay, there’s clearly something here that we can apply to something. And then we looked at email: we looked at how people communicate. And we actually built a little Chrome extension that sits in your email and responds to your emails, to give responses, gesture responses based on learning from your pattern of emails. And that was something that we actually got a bunch of people in the computer science building teams to use. And I remember the day Google launched Smart Compose I got 20 articles from people telling me, “Hey, did you see this launch?” I was like, “Yes, I did see this launch.” But it was interesting. It was interesting to get that piece, because it was pretty clear Google has just a 1,000X data advantage there. So while it was a useful piece of tool, it wasn’t clear that we would have the advantage in terms of being able to build something that’s really useful for people. And then secondly, just the realization was that email has so many external things where there’s your calendar and your family situation, all these things that are not in the email. And so generating responses with your circle email is actually really hard, because it’s an open domain problem.

But then that’s when you’ve gone into the enterprise of the business. And so we really looked at these teams and started partnering with corporate teams in the Bay Area and started providing artificial intelligence for support teams. I would go to these companies and just shadow people – like, what does an HR person do on a day-to-day basis? What does a finance person do on a day-to-day basis? What does a salesperson do? What does a support person do? And that was fun because for me I just love learning about jobs and learning what people do and what their work is, and what makes someone good, and what makes them not good. So I just really enjoyed that; just studying people and understanding what their work is.

Basically then, that phase was just building tools and seeing what can artificial intelligence do? What software tools can we build to streamline workflows, make people better, make people more effective? And then I remember at some point we were working with a sales team for a particular business. I built a tool for them to help guide them on conversations and we were able to prove that we were driving $100,000 of incremental revenue per month. [And we were doing that] as a grad student and a small team. And so it was a million dollars per year.

Then I remember going back to the lab and presenting, “Here’s the results I had.” And it was clear like, “Okay, this is a business. There’s this thing and there’s something here.” If a single grad student can have that kind of impact on a business, and have that kind of effectiveness on the business then there’s something there.

And then I remember that’s where Sebastian saw the results and then specifically asked me, “Okay. So do you want to publish papers or do you want to start a company?” And then I went on this soul search of what I wanted to do with that technology. And that’s what ultimately led to Cresta.

SM: What an incredible story. And I think your customers and your team are probably excited you decided to go down the company route.

Zayd, one thing that’s interesting is that Cresta today is focused on contact centers, but from day one, as you’ve described, the mission to me and everyone around the company is making every office worker 100X as effective. It’s an incredibly horizontal and expansive vision. And contact centers are interesting, because on the one hand they’re massive – almost every enterprise has a contact center. It’s an important surface area of customer interactions, and on the other hand, most of us who have interacted with contact centers have had very negative experiences, right? These are very manual, low NPS areas of customer experience. And so maybe talk to us about why it’s so important and why Cresta decided to just start focused on the contact center.

ZE: Yeah. And so when we got those initial results and looked at the space, it was like, okay, how many people have this problem and how big of a problem is this? Because the whole point is, if you have a big picture or a big vision, that’s a really difficult place to start because it’s so big that how do you even get adoption for it? How do you get things started? You always have to narrow things down. If you narrow it down, narrow it down, narrow it down, then at the end of the day, it doesn’t matter what you think. It matters what the value your customer is getting from you. And then you get the luxury and privilege to then execute on a vision if you start with delivering the value to your customers.

And so the reason that we started there is because it’s an area with lots of pain and lots of opportunity where we could have immediate impact. It was taking me just two or three weeks to be able to just drive dramatic impact for these teams. And it’s like, okay, clearly there’s something here where we can start and build something that gives us the luxury and privilege to be able to execute on a longer-term vision.

Every company I was just looking at – every single company in the world – has a contact center, because every company has conversations with their customers. I remember reading about Patrick and John and Stripe in the early days where it felt a little bit like people avoided the payments problem. And it felt to me like nobody I knew that was smart wanted to go work in the contact center, because it seemed like a super unsexy place to go work. But it was like, wow, every company in the world has this problem. No one says that they do a great job at it and we could have a product or something that can deliver value quickly and immediately. This seems like a big opportunity to be able to go execute on something big. And so that was the thinking I had.

SM: One of the interesting things I think is quite remarkable about Cresta is, from day one you focused on working with the very largest enterprises in the world. And as you said, every enterprise has a contact center, but the scale of contact centers that Cresta’s working with is very, very large. And the company launched out of stealth in early 2020. Since then you’ve begun working with many customers across verticals that are operating these very large contact centers.

I have two questions related to that. The first is, how did you get your first customer? You rolled out of the Stanford AI lab, you have proven these amazing results and you, Tim and Sebastian started Cresta. How’d you convince these large enterprises to partner with you on such an integral part of their business?

ZE: Yeah. It’s a funny story. So, it was clear that the biggest market by far was in the enterprise, because the enterprise had the largest customer-facing context and operations and it was the biggest place where you can just have a huge impact and huge value. And because I’m all about data – in terms of conversations where artificial intelligence would have just the biggest impact. So enterprise is clearly a place that if we start there, we’re going to have the best product, the best customers, and ultimately, the largest market that we can start with. So that was tricky.

I actually remember at the time looking at all these things and thinking, “What is the advice that Y Combinator has?” Y Combinator at the time had a blog post about, “Don’t go for enterprise. Don’t start with enterprise because it’s a fool’s errand.”

But I knew that was a market that we needed to go into, and so that’s the market where we need to start, because that’s where our product would have the most value. So I actually did a bunch of cold emails prospecting. I ended up sending a cold email to Scott Cook who was a founder of a company called Intuit – massive products like TurboTax and all the other products that they make – after he gave a lecture. And I just mentioned some of the PhD work I’d been doing and some of the results I had. And I asked him if he had some time, 30 minutes or so just talk it through and give me some advice on some things. And he was super busy and he said, “Look, I’m super busy. I can’t do this but here’s 30 minutes with my CIO’s. Go meet him and he can help.”

And so I got a 30 minute meeting with the CIO of Intuit and so I showed up and said I was an enrolled PhD student at Stanford ,and I’m going through all my PhD work, my results, the way you present, you know. It’s funny, but that’s the stuff in my head. So I went down, walked him through some results. What I’ve been doing, the value, the impact and he said, “This is great. This is excellent. We’re becoming an AI company. This is a key part of our mission and how do we use artificial intelligence to help our employees better? All this is fantastic.”

And so I said, “Awesome. I’m right here. I want to work with you. You want to work with me.” I said, “Great. I want to start a company here so would you be willing to be a first customer, early adopter of the technology?” And he looked at me for a second and he just looked at me and he’s like, “Look, we’re a Fortune 500 company with a nation’s financial data and our systems. We can’t work with one-person companies. You can’t do that, but if you want to sign up as an intern, you’re welcome to sign up as an intern.” So he basically offered me an internship and I was like, “Huh. Okay.” So I took that and decided, okay, I’ll take him up on the offer.

So I signed up as an intern at Intuit, got access to their system, got access to their data, went in, built the initial systems and models and software, all these things, and deployed to this team out in Tempe, Arizona. And so I fly to Tempe, Arizona. That’s where the call centers were. Got the very first person using the product and then he loved the product so much, he got the other people at that team started using it. They adopted the product. And then when that team was seeing great results where their performance to quota went from 80% to quota to 160% to quota, they were like, “Okay, we need to expand this to another team.”

And so then they expanded Cresta to a second much larger team. And so then that’s when I went back to Scott and the CIO and said, “Hey, thank you so much for the opportunity, but this is becoming a bigger thing and you don’t really want and intern supporting this project. And it makes sense, sign a saas contract with a business or a company.” And so basically we came to an agreement where we have a standard saas contract where the last clause of the contract is basically, this contract hereby terminates my internship at Intuit.” And so then I signed as CEO of Cresta and off as an intern of Intuit. And so it’s funny because every time we can do a renewal, I have to sign as both for our first customer, but it’s always a reminder of that experience.

SM: We’ve heard many stories around landing the first customer, especially in enterprise. I think going and signing up as an intern and then converting that into an enterprise deal is an incredible example of customer centricity. And I think the next time we have a new founder who’s scared of breaking into the enterprise that I will make sure to refer them to you so you can walk through how you did it.

ZE: Yeah.

SM: Amazing story. Okay. So going back, so Intuit, your first customer started with a meeting with the CIO. You showed him what you could do in the context of the same way you had shown with the lab results. Now fast forward several years, I think last week, Cresta had a very big product announcement coinciding with the big funding news. Maybe talk about where the product is today and what are customers buying? How are they deploying it and how are they driving value from it?

ZE: Yeah, absolutely. And I think that transition, or that journey, from that point to now is really the fundamental transition that you have as CEO, which is the switch from a founder to CEO. And the transition of how much of the business you are driving by hustle, and how much of the business rate is being driven by building a machine.

What I’m excited about now: we launched Cresta Voice. and every single customer has been asking us for this for a while. We have deployed to only sets of customers, and they’re just having tremendous amazing results. And it’s because at the end of the day, everyone recognizes that there’s an opportunity to be better in these conversations they have with their customers.

We started with digital and shop, and we started with these products and they were seeing the value immediately. It was really quick to get to value. They would see the value immediately and then renew and expand to other business units, other use cases. And the first question everyone was like, “Can you help me with voice? That’s my lion’s share of customer contacts.” And so we’ve been working hard at it.

It’s a much harder problem because you got to solve a lot of fundamental R&D problems in terms of latency, for speech and text, in terms of being able to provide behavioral prints and prompts in a way that’s consumable by the agent. But the team’s been working really, really hard and really solving these key design and AI and UX problems and we’ve gotten into it. I think we have an amazing product that was excited to launch yesterday on ready, singly, fantastic results with companies like EarthLink, who are seeing these things and it’s just the start where we’re headed as a business.

SM: One of the things I’m curious about is how you think about the engineering challenges here. You just mentioned some of them, particularly around voice – getting the prediction latency down so it feels real time and that’s one center.

I think the other piece that I’ve always found really interesting connects back to something you said earlier. And I think you said when you were starting Cresta back at the lab at Stanford, one hypothesis you and your co-founders had was the market’s view of the impact that AI could have was quite narrow and it was really focused on automation. So taking low hanging fruit use cases and automating them away.

And your hypothesis was actually that there’s a lot more to be gained by building AI systems that can work with humans and make humans more effective. Can you talk a little bit about that? It’s such a unique thing to see an AI company in the market building software that really augments and works alongside humans.

And then the thing I’m curious about from an engineering and product challenge perspective: how do you do that? How do you build a system that someone sitting at Intuit or sitting at EarthLink working at a contact center environment, wants to interact with and can effectively interact with?

ZE: Yeah, absolutely. So that strategy – that approach – came from a few different things: one is just the realization that the combination of humans and AI is ultimately going to result in something superior than the individual.

And the second thing is just that if you look at the state of conversational intelligence or conversational AI, we are not at the level where we understand the fundamentals of language enough to deliver human-level conversations. And so whenever folks tried with the approach of automation first, they just ended up with just poor experiences and frustrating experiences, to be honest. And so our approach was like, “Look: the best in any market, any opportunity, any technology, is not bringing things down to the lowest common denominator and trying to solve it for the lowest common denominator.”

But what is the best? Where can you take the technology, the product, and ultimately result in the best? In this case, what is the best conversation possible? How can we leverage what we have: The tools in front of us, which are amazing advances in artificial intelligence and NLP, and also just the amazing things that humans are amazing at? How do you get to a point where conversations are better, where companies have more empathetic, more effective, more efficient conversations with their customers? And so that was the approach that we took.

And so it’s a different approach, but ultimately what we think is that, once you get to that point, once you really make every single conversation excellent, then you have just all kinds of things you can do and all kinds of things that open up as opportunities, rather than starting with the lowest common denominator automation-type tasks.

SM: Great. I want to zoom up from Cresta 30,000 feet and just talk about what’s happening in the market.

Cresta today works with large enterprises across verticals. Saas companies like Intuit, financial services companies, retail companies, automotive companies. Zayd, I want you to rewind to March, 2020. You’re the CEO of Cresta. Cresta’s focused on serving these verticals. Contact centers are a core part of customer experience, but obviously the physical retail is as well. And physical is also a very big part of how your customers interact with their end customers. And March, 2020, the pandemic begins and all of that comes to a halt. What happened? How did customers who were so reliant on retail and physical channels adapt, and what do you think customer experience looks like looking forward – hopefully coming out of the pandemic this year – in the new normal?

ZE: Yeah. It’s interesting. I think one thing I think just to be proud about – or the American system should be proud about – is just the dynamism of the economy, where we just have whole functions, whole parts of the world just shut down but somehow we managed a way to keep going and keep doing business; bringing out a different way to interact, transact, to do things. That’s remarkable. I think few economic systems have that resiliency to be able to have major parts of the system cut off and be able to do that.

I think our partners were super, super innovative and intuitive about where the customers expected to meet them now. And there’s all kinds of places where the interaction shifted from purely retail, in-person interactions to entirely digital interactions over messaging or voice, and companies pivoted amazingly. Companies did that correctly – they succeeded tremendously and they did that in a really effective way.

I remember actually in the beginning of the pandemic when you forwarded me a note from one of our customers, Sleep Number. It was their earnings transcript. It’s interesting because Sleep Number had shifted from entirely retail-focused operation to an operation where they were selling and supporting all the mattresses and products over phone and digital. So they actually presented their Q1 earnings just at that time in March to Wall Street and they exceeded analyst expectations for what the revenue of the business would be, and they actually attributed that revenue expectations to phone and the digital overperformance in the point of digital channels.

At the same time, they had brought us in and we had shown a 24% increase in revenue per conversation for the digital channels and conversation. And so being able to drive and see, first of all, from our side where we can improve the impact of revenue and then see that impact ultimately in the stock price of the company, help show you, the CEO of Sleep Number, how you can help her beat her quarter and ultimately help her increase her stock price by 30% and ultimately increase the GDP of the United States. That was just so exciting. Just that moment when it’s the recognition that you built a technology that not only is making individual people productive but is actually fundamentally increasing the GDP of the country because you’re improving productivity of one of the core functions of a business. That was awesome. That was cool to see.

But we saw that play out across many different industries and many different customers who have become top level strategic priorities. Another one of our partners, Porsche ( which is this amazing partner), recognizes that all their storerooms are now just seeing 1/10th of the volume that they saw pre-pandemic. So they’re really investing at the CEO-level strategically. How do we get the best of digital experiences, and how do we convey the Porsche brand and the Porsche experience across not just our retail operations, but across our digital experiences with phone and digital and messaging and all these things? How can we leverage artificial intelligence to do that? Not just automate the basic things, but ultimately get to the Porsche experience. What is the best possible conversation to have there? And so that’s what we saw, and I think that’s just a testament to our economic system and a testament to the innovation and ingenuity of all our partners and customers. They were able to pivot like that and work in this brave new world.

SM: Yeah. Those are excellent anecdotes. And I think two things you alluded to really resonate with me. One is: I completely concur. It was amazing just to see the dynamism in our economy and in these companies specifically. And Sleep Number is just such an interesting one, because if you think about any company that relies on a physical retail presence for their business, it’s selling mattresses, where folks want to come in, they want to lie down, they want to try the mattress. That’s at the very core, and for that business to completely reinvent the way it maintains relationships with its customers in such short order is incredible. We’ve seen that happen across verticals.

The second piece which ties into that is just the opportunity companies like Cresta have to help drive that transformation. And it’s really unique. Both of those pieces you need forward-thinking organizations that recognize that they can use innovation to adapt to new worlds, and then you need companies like Cresta that can bring the expertise on the solution side to partner and get them there. So those are really interesting and powerful anecdotes.

I want to spend the last few minutes of our conversations, Zayd talking about how you’re building Cresta as a company, because I think there’s several things you do that as I’ve observed you, I’ve learned a lot from and I think are very distinctive.

I want to start with building an AI-native company. You often talk about how Cresta, from day one, has been building AI products and has architected the company in a way to deliver AI products that improve over time. Talk to our audience about what that means, and what it really means to build an AI-native company.

ZE: Yeah, absolutely. I think the whole industry for artificial intelligence is already providing impact, but it’s still so nascent. What we’ve done is barely scratch the surface of what’s possible with artificial intelligence.

And so what we’re doing is focusing on artificial intelligence, and then building basically what is a core value the company delivers, and focusing on what is that core value and how does artificial intelligence deliver that value? Then, building all the necessary pieces of software and enterprise software around it to be useful and consumable by the customer. That’s a very different company than a company that tries to build software and then tries to bolt on AI features into that software, because it’s just a different mindset and different approach to how you push your problem. Because at the core of it, an AI company’s lifeblood includes the data – the way you provide and deploy these models and provide value to customers.And it has to start at that. Data is a product; a product is data. And if you do that right, then you’ve got folks that are focused on delivering value to customers. It’s a little bit of a different mindset than a standard, where I would say a software company that tries to build an AI feature. So that becomes a key piece of the company.

And I think that the second thing is that, at the end of the day, the unique thing the AI company has is that there’s rarely been a case where you have a software company that is so directly tied to business outcomes, that the customer is looking at you to achieve it. With artificial intelligence [tools], the business outcome is literally you telling me what you want to do. Do you want to increase sales? Do you want to reduce call handle time? Do you want to reduce churn?

Then, we can tune and train our models to drive for that business outcome and deliver that business outcome. And so the unique thing is that the whole company can be aligned to deliver on the business outcome to the customer, and you can do that in a highly repeatable, productized way.

That becomes a unique opportunity where it’s no longer this thing that you see in enterprise software companies, where engineering’s off in this world building a product that they throw over the wall and then tell sales to go sell, and sales is going to try to figure out, “Ok, how do we make this product work and deliver business outcomes? How do we map customer pain to these things?” It’s like, no, the whole company is aligned using everything from the technology to the product, to the marketing, to sales, to delivering for business outcomes for the customer. And that is a unique opportunity to build a company that’s aligned that way. And I think that’s one of the things that makes a lot of the things that we do possible at Cresta.

SM: I want to double click on that alignment. Zayd, you often refer to two engines (or core centers) in the company. One is the engineering and product engine, and the other is sales and go-to-market. I want to talk about both of those.

Let’s start with engineering. I think one of the things that is distinct about Cresta, even from when the company was early and had in the tens of employees, was you had a large number of engineers on the team who were former founders and who were very entrepreneurial. And then the team has always worked in a hyper customer-centric way. Talk about how you build that center and how you build that culture.

ZE: Yeah. We think of the company and the engineering team as a lot of that team is entrepreneurial engineers. The way that Tim, and myself, and all of the early team view ourselves is that, “Yes, we’re technical people, we build software, we did a PhD, we built the initial product, we built all these things. But not only did we build the technology and the product, we also figured out how to go sell it. We sold the first set of customers and we were in front of customers that made sure that they got it. We made sure they got the value of these things. And I think being able to approach each function and each piece of that journey with respect and curiosity is key.

So if you recognize that none of those things is more important than the other – and you’ve built a culture on the fact that, look, we’re going to try to become the very best at every single piece of this customer journey, everything from building the technology of the product – I think that’s key.

For example, the first time (literally the first week) that Tim and I met, we had dinner. We decided to work together the next morning. We’ve been working together since then. The first week we said, “Hey, we should really go to the call center. We should try to understand everything that’s happening.” So we flew out an extra few days after we met (in terms of working together), we flew out to Las Vegas and just went and shadowed for a couple of days all kinds of calls and ratings and understanding what was happening in their operations.

Before the pandemic, we made it a part of the company tradition where we would literally fly out half the engineering team, three-quarters of the engineering team, and we’d get an Airbnb next to a big call center site where our customers were and we just go there for a week. Then we just basically talk to your users in the morning, ship the product at night, and have a bunch of fun as well. But it was such a key part of understanding who is our customer, and what do they want? It’s also super motivating, because you understand your user in a way that’s real. They’re a person, they have a story, and they have a life, and their kids, and a family and all these things. You understand what your product is doing for them.

That’s actually a big gap that I think is often in engineering teams where people – actually Karl Marx said this – “If you don’t know what you’re doing (who is the person you’re solving or delivering value to in the world), your work feels meaningless.” And so being able to actually meet the person and interact with them and talk to them, and have them tell you how excited and how the speech tool is literally reducing the stress of their day-to-day and making them happier as a person and helping them beat their quota – that’s so meaningful for someone who’s building a product. And I think that’s such a key part of what our culture is. And I’m really excited to get back to that once folks are vaccinated. I’m excited to be able to visit them regularly in the context of their sites.

SM: Yeah. It’s such a powerful practice and it connects to something you talk about often, which is you want consumer-grade product and engineering in the enterprise. I think it’s easier for folks who are building consumer products, because they’re end-users themselves. They can talk to their friends who are also users. But by flying your team out to the customer site, you replicate the same tightness of a feedback loop before an enterprise product. It’s super unique.

How about on the go-to-market and sales side? How are you building that part of the company and what are some things that differentiate the sales and go-to-market culture at Cresta?

ZE: Yeah, that’s interesting. I think, again, it all starts with curiosity and respecting every single function within the company and every single job that someone shows up at Cresta to do. Everyone is showing up to do a job and everyone’s looking to be amazing at what they do. It has to start with the stop. So it has to start with you selling yourself. If you sell yourself, you gain some empathy for what the sales process is and how important it is.

Our first customer was a cold email. So it was pipeline generation. And I think pipeline generation and prospecting is a fundamental part of sales. People call it the calisthenics of sales, where if you’re good at prospecting into customers, it’s the fundamentals of staying tip top as an athlete.

I think that’s a fundamental piece. If you have this engineering culture that’s built around the customer and built around the outcomes of the customer seeing that – with super talented, amazing engineers who understand the customer, and have empathy with the customer,you build a sales team around people that aren’t just laid back but are prospecting actively. They are pipeline-generating into accounts, hunting for these customers.

Those are the two engines of the business. It’s almost where, if you get those two things right, you can get a lot of other things wrong and still build an amazing business and things can layer on top of that. It’s where you can layer marketing and product and all these pieces on top of those two engines. But if you get that leaned-in, forward-thinking, prospect and pipeline generation for sales in a very customer-centric approach to engineering, it’s this beautiful machine that starts turning.

I think unfortunately a lot of people view sales or go-to-market or technical CEOs, and they don’t have the respect for go-to-market that they should. And I think that’s a disservice. I think [it’s important to] really understand the craft and the art and the science of sales and marketing and what makes someone really good.

One of the funniest things, I think, for the CEO job is just understanding these things and understanding what makes someone truly excellent, and how you do this in the very best way possible. I think that’s one authentic thing, when you’re leading people and it’s something that motivates and is inspiring. And so I think that sort of thing ties and helps create a team that’s just always approaching you to say, “How do we get better? How do we become the best across the company?”

SM: Absolutely. And as you think about continuing to grow and scale this machine, as you’ve said, one topic on a lot of founders minds and startup employee minds is how work is going to look, coming out of Covid, and coming out of the pandemic (hopefully) over the coming months.

How are you thinking about Cresta and building Cresta in this new normal as we exit Covid and enter the next chapter?

ZE: Yeah, it’s funny. I think about this obviously a lot in all these pieces and on these things. And for me personally, for example: I spent a lot of time with my parents in Pakistan for most of my life. So if I think of a home, I have a sense of a physical sense of belonging when someone says, “Hey, go home.” I have a physical sense of my parents, my bedroom, all these things. And I think that such a key part of a bond and this connection that you have with people is that sense of physical location. And so I do think a hybrid work approach is the right way in the future, but I do think a physical location is just so ingrained to us in our psychology and our brains.

People have done these studies with rats where you put them in these mazes and they have these place cells, and you can put treats and all these things all over the place, but they’ll still always have a few set of neurons that are dedicated to what was the home position and what was that position is, and they will know how to navigate back to that one position from wherever you modify that. So there’s something fundamental about knowing a physical location, being able to be tied to it, and it being the heart and soul of the place.

For us, we’re going to put down roots with a three or five-year office space lease, in terms of scope, because it’s such a key part of what I think becomes a part of the company experience. We’ll be a hybrid company as an approach, but it’s going to be a place where it has to be beautiful. It has to be a place that people enjoy coming to and people see it as a score – just an amazing place.

And I’m not going to say where it is because we have to still sign the lease before anyone else competes with us to get the lease.
But it’s such a key part; it’s such an iconic part of what I think what’s going to make Cresta special. So that’s one of the things we’re doing. We’re going to continue investing in that as part of the company.

SM: I’m excited to see the new office. The Cresta offices that I’ve been to, both your most recent one in San Francisco and the one before that in Palo Alto, have always had a very unique, as you said, soul and energy to them. I’m excited to see that back up and running, hopefully this summer.

This has been an awesome conversation. I actually want to end with one last question related to this: I remember in the fall of 2019 when we were spending time together in your office discussing partnering on your Series A. In addition to the soul and energy and excitement that was at the office, there was a painting from Diego Rivera that you had in the office. That painting is important to you and I think it’s important to Cresta. I’d love for you to share with our listeners what that painting is and what it means to you and the company.

ZE: Yeah, absolutely. I remember that fondly. We’d spend hours talking about the future of Cresta and all these things; it was awesome.

That painting is of Diego Rivera’s mural that he was commissioned to paint by the Ford Motor Company in the early 1900s, first half of the 1900s. He was commissioned to paint what a Ford Motor Company looks like inside. So it’s this beautiful, massive mural that’s in Detroit. As you can see, he painted this place, and he did this where he would paint people at work. So he did all kinds of a series of places that people at work. Diego Rivera’s a communist by the way; he was a communist by political ideology. And so he had this idea of “What do people experience at work, and what have they experienced?” in this set of paintings. He actually has a few in San Francisco as well at the Coit Tower that are absolutely gorgeous.

But the thing that always stuck out to me – and I’ve taken that painting everywhere, I got it originally while I was doing the PhD at Stanford and it was probably the only piece of art I had at my graduate dorm. But then I kept it, with a plane ticket for every place I’ve gone for the last five or so years.

Basically, Ford built the motor company to be like innovation factory, where the whole thing was set up to be the set of experiments where people were empowered to say, “Hey if there’s a better way to build a car, we can try it and we can save time on it and we can do that more effectively. So then let’s go build that.”

The innovation for the assembly line came about because someone came up with the idea based on what they saw at a butcher shop. They saw a butcher moving meat and cattle through an assembly line. They said, “Hey, if we did that, it would save a bunch of time in terms of moving parts from one end to the other.” And so they innovated, they got that and they actually saved seven minutes of production time for every car. And then they figured out, “Hey, if we hang drills up by pulleys instead of having people bend over to pick them up from the ground and these areas, if we held them at their height, that saves four seconds off every bolt that’s screwed in. And that ends up being two minutes on the line.

And so you get these massive improvements by just running these experiments. And the whole thing became this massive thing about how you automatically enhance productivity of people building the car. And so within four years they were able to quadruple the activity and ultimately they were able to 100 X productivity when building a car. A car couldn’t be built efficiently before, but now it could be built in a way that was affordable and effective by the class.

That’s always been an inspiration to me. One, it’s an empowerment of ideas and the power that ideas can have, and that the core technology can have, in the way people work and how much more productive it can be.

And then the thing is the car was built from this assembly-line technology that made people more productive. But then that fundamental technology has skewed second-order impacts in society. [It took us to a place] where cars could be used to drive from point A to point B, where you can go to restaurants and visit friends, and roads are built and highways are built. And it all started with the fundamental piece of technology that dramatically enhanced the productivity of someone in the factory. And the way society functions was built from that same thing.

Personally, when I was dropping out, when I had to make the decision to drop out of Stanford to start Cresta, I had to make a phone call to my dad. That was the one phone call I was not looking forward to, because he’s a very intelligent, great, but conservative father, which is awesome as well in many ways. But I had to explain that I needed to gain conviction that, “Okay, I’m going to do this. I’m going to have this conversation.”

This was at the same time that I was reading Ford’s biography, and also the same time that I got this was this mural. It was giving me the conviction that, “Hey, if I believe fundamentally that artificial intelligence as a technology is going to dramatically improve the productivity of people at work, and it could be like the same thing that happened with the car (and actually happened 100 years before that with the crop reaper). It might happen here as well. It might feel like an AI technology to go work on call-center tech, and we’ll start there. But the second-order impacts and making people much more productive have just so much impact on society, and so much impact on how we live and work and play as humans.”

The conviction was clearly there that this is what I should go work on. For me, artificial intelligence is that assembly line for office work, where we’re making people 100 times as effective and 100 times as productive. And I’m really excited for what the world will look like when we can unlock that potential, where we’re not spending so much time on busy work.

SM: Yeah. What a great story that reinforces the mission and opportunity ahead for Cresta. And I hope your dad is listening to this and is happy that you made that phone call to him.

Zayd, this has been a fantastic conversation thanks for joining us and thanks everyone for tuning into this episode of Greymatter.

ZE: Thank you.


Saam Motamedi

Saam partners with enterprise software entrepreneurs at the seed and early stages who are focused on new opportunities in intelligent applications, cybersecurity, AI, and data infrastructure.

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