'Sweetgreen is Not a Tech Company': The Company's CEO on How He's Adapting to the Pandemic

Ben Bergman

Ben Bergman is the newsroom's senior finance reporter. Previously he was a senior business reporter and host at KPCC, a senior producer at Gimlet Media, a producer at NPR's Morning Edition, and produced two investigative documentaries for KCET. He has been a frequent on-air contributor to business coverage on NPR and Marketplace and has written for The New York Times and Columbia Journalism Review. Ben was a 2017-2018 Knight-Bagehot Fellow in Economic and Business Journalism at Columbia Business School. In his free time, he enjoys skiing, playing poker, and cheering on The Seattle Seahawks.

'Sweetgreen is Not a Tech Company': The Company's CEO on How He's Adapting to the Pandemic

Jonathan Neman, the 35-year-old co-founder and CEO of Sweetgreen, wants to make one thing clear.

"Sweetgreen is not a tech company," he says. "If you want to make that the headline, you can."

With a lofty $1.6 billion valuation, a sleek headquarters in Culver City down the street from Apple and Amazon, and talk with Kara Swisher about becoming a "food platform," one could be forgiven for thinking Neman has aspirations that go way beyond serving salads, bowls and now plates in 108 stores. These days everyone wants to be a tech company, even if they are just renting office space or selling stationary bikes. Neman certainly has lofty goals – wanting to expand to what he says is "well over" 1,000 locations. But he says he is trying to grow Sweetgreen in the mold of Starbucks, not Snapchat.

"We see ourselves as building the Starbucks of real food," Neman said. "We're actually not even valued like a tech company. If you look at the valuation it's much more like a high-growth food company. We leverage technology to build a better experience and make smarter decisions. And I think it is an accelerant to how we can grow and scale and build our model. However, at the core of what we do, we are a consumer brand."

Sweetgreen's origin story is decidedly techie. Neman hatched the concept with classmates Nicholas Jammet and Nathaniel Ru in a dorm room during their senior year at Georgetown University. Three months after graduation, they opened their first location in Washington D.C. in 2007. In 2016, they relocated to Los Angeles after opening their 39th location.

Last year, Sweetgreen reported $300 million in revenue and $3 million per store, well above Chipotle or Starbucks, which generated $2.2 and $945,270 per location, respectively.

The company would not disclose its numbers for this year but in an April blog post Neman and his co-founders described revenue being "dramatically affected" by the coronavirus. That month, Sweetgreen laid off about 10% of workers at its headquarters and furloughed nearly 2,000 store employees after deciding to return a $10 million PPP loan.

"As soon as we found out that they had run out of money, we decided to give it back, which we think was the right thing to do," Neman said.

Now 75% of the furloughed workers have been brought back and Sweetgreen has reopened all but 11 of locations. All dining rooms in California remain closed though some locations with outdoor seating can accommodate diners. Headquarters is officially open, though it is mostly empty as the company is not requiring anyone to come in for the foreseeable future. Despite some permitting delays because of COVID, Sweetgreen is planning to open 20 new locations this year and considerably more next year. And in late April, it introduced its first new major menu category since adding bowls four years ago – nine different plates, ranging from Hot Honey Chicken to Shroomy Asada, designed to increase dinnertime sales. On Wednesday, Sweetgreen will hold its first-ever $5 Greens Day where it will offer select bowls and salads for well under half the normal price.

Sweetgreen introduced its first new major menu category since adding bowls four years ago – nine different plates, ranging from Hot Honey Chicken to Shroomy Asada.

dot.LA spoke to Neman about how the company is adapting to the COVID era, why he ended an exclusive partnership with UberEats, and when Sweetgreen might IPO.

A lot of your business has been centered around offices. How are you adjusting since people aren't coming into offices?

To your point, we have a very high penetration in some urban areas and those are the ones that have been more severely impacted. Our restaurants that are more suburban-based are actually doing really well. Many of them have fully recovered to pre-COVID levels through just delivery and pickup. So really the impacts we're seeing are primarily only from the true demographic shifts rather than from changing consumer behaviors.

Jonathan Neman hatched the concept of with classmates Nicholas Jammet and Nathaniel Ru in a dorm room during their senior year at Georgetown University.

Does COVID change where you anticipate opening stores in the next few years?

Yeah, a little bit. We were already on a path of expanding beyond our current markets. This year, we have already opened in Denver and Miami and we're opening in Austin. And so we already penetrated a lot of the larger cities, and we're on our way to going into other markets that are more suburban. If you look at the makeup of the United States it's much more suburban than urban. So there was a lot more suburban growth coming, but I think this has accelerated a lot of that as our suburban model has done better. But we have not given up on the cities. We're going to continue to open in New York. We are very confident people will come back to work, although it may be different and we'll be well positioned for it.

Now that we're in a recession do you worry that people will see your menus and think of it as an indulgence to spend $14 on a salad?

Our prices are different by market. Definitely very top of mind for us is affordability. We like to balance all stakeholders when we think about price. So you have to think about how we pay our team members and our farmers.

This is why food is really complicated. I could charge less, and then pay my team members less and pay my farmers less and then I'd get heat for that as well. But having said that, I do think that Sweetgreen will do more over time to address different consumers and price sensitivity. Over time we will think about different menu items and formats and ways to make it more affordable. One way is when you think about our plates, $12 for lunch may be expensive but $12 for dinner is actually pretty affordable. Another way we do this is through things like Outpost [a central drop off shelf in buildings where Sweetgreen couriers drop off orders.] You're not paying the delivery service fee that you would for a lot of other places.

You had signed an exclusive deal with Uber Eats last year and then canceled it. What was the decision behind that?

We have a great relationship with Uber but I think we've realized over time that different consumers use different platforms and they're more incremental to each other than they are cannibalistic. Especially in a post-COVID world where delivery will be a bigger piece of the pie, we wanted to get in front of as many consumers as possible. We also are very focused on our native delivery which is which is by far our biggest delivery channel,

I'm curious how you think about delivery. Because for a lot of restaurants they're sacrificing huge margins...

Correct. Not only are they sacrificing huge margins, but they don't have a direct relationship with their consumers. We have a direct relationship where we can tell you when new menu items come out and we can personalize the experience to you.

So why not just have it all be native?

I think there's certain customers where the marketplace becomes a great place of discovery, it becomes, you know, almost like a customer acquisition marketing tool for us a way to amplify our message and reach more people.

Have you ever thought about doing brunch or breakfast?

We definitely have. Sweetgreen is an ethos, which is connecting people to real foods. Eventually we'd like to take that ethos and expand way beyond salad, bowls and plates, whether it be brunch or otherwise. The vision is to go much, much broader.

That's a perfect segue to my last question. What's your current thinking on a possible IPO?

There's no current thinking right now. We're just very focused on expanding the brand, delivering a great product to consumers and strengthening the business. Sure, one day, but not not anytime soon.


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Creandum’s Carl Fritjofsson on the Differences Between the Startup Ecosystem in Europe and the U.S.

Decerry Donato

Decerry Donato is a reporter at dot.LA. Prior to that, she was an editorial fellow at the company. Decerry received her bachelor's degree in literary journalism from the University of California, Irvine. She continues to write stories to inform the community about issues or events that take place in the L.A. area. On the weekends, she can be found hiking in the Angeles National forest or sifting through racks at your local thrift store.

Carl Fritjofsson
Carl Fritjofsson

On this episode of the LA Venture podcast, Creandum General Partner Carl Fritjofsson talks about his venture journey, why Generative-AI represents an opportunity to rethink products from the ground up, and why Q4 2023 and Q1 2024 could be "pretty bloody" for startups.

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AI Is Rapidly Advancing, but the Question Is, Can We Keep Up?

Lon Harris
Lon Harris is a contributor to dot.LA. His work has also appeared on ScreenJunkies, RottenTomatoes and Inside Streaming.
AI Is Rapidly Advancing, but the Question Is, Can We Keep Up?
Evan Xie

One way to measure just how white-hot AI development has become: the world is running out of the advanced graphics chips necessary to power AI programs. While Intel central processing units were once the most sought-after industry leaders, advanced graphics chips like Nvidia’s are designed to run multiple computations simultaneously, a baseline necessity for many AI models.

An early version of ChatGPT required around 10,000 graphics chips to run. By some estimates, newer updates require 3-5 times that amount of processing power. As a result of this skyrocketing demand, shares of Nvidia have jumped 165% so far this year.

Building on this momentum, this week, Nvidia revealed a line-up of new AI-related projects including an Israeli supercomputer project and a platform utilizing AI to help video game developers. For smaller companies and startups, however, getting access to the vital underlying technology that powers AI development is already becoming less about meritocracy and more about “who you know.” According to the Wall Street Journal, Elon Musk scooped up a valuable share of server space from Oracle this year before anyone else got a crack at it for his new OpenAI rival, X.AI.

The massive demand for Nvidia-style chips has also created a lucrative secondary market, where smaller companies and startups are often outbid by larger and more established rivals. One startup founder compares the fevered crush of the current chip marketplace to toilet paper in the early days of the pandemic. For those companies that don’t get access to the most powerful chips or enough server space in the cloud, often the only remaining option is to simplify their AI models, so they can run more efficiently.

Beyond just the design of new AI products, we’re also at a key moment for users and consumers, who are still figuring out what sorts of applications are ideal for AI and which ones are less effective, or potentially even unethical or dangerous. There’s now mounting evidence that the hype around some of these AI tools is reaching a lot further than the warnings about its drawbacks.

JP Morgan Chase is training a new AI chatbot to help customers choose financial securities and stocks, known as IndexGPT. For now, they insist that it’s purely supplemental, designed to advise and not replace money managers, but it may just be a matter of time before job losses begin to hit financial planners along with everyone else.

A lawyer in New York just this week was busted by a judge for using ChatGPT as part of his background research. When questioned by the judge, lawyer Peter LoDuco revealed that he’d farmed out some research to a colleague, Steven A. Schwartz, who had consulted with ChatGPT on the case. Schwartz was apparently unaware that the AI chatbot was able to lie – transcripts even show him questioning ChatGPT’s responses and the bot assuring him that these were, in fact, real cases and citations.

New research by Marucie Jakesch, a doctoral student from Cornell University, suggests that even users who are more aware than Schwartz about how AI works and its limitations may still be impacted in subtle and subconscious ways by its output.

Not to mention, according to data from Intelligent.com, high school and college students already – on the whole – prefer utilizing ChatGPT for help with schoolwork over a human tutor. The survey also notes that advanced students tend to report getting more out of using ChatGPT-type programs than beginners, likely because they have more baseline knowledge and can construct better and more informative prompts.

But therein lies the big drawback to using ChatGPT and other AI tools for education. At least so far, they’re reliant on the end user writing good prompts and having some sense about how to organize a lesson plan for themselves. Human tutors, on the other hand, have a lot of personal experience in these kinds of areas. Someone who instructs others in foreign languages professionally probably has a good inherent sense of when you need to focus on expanding your vocabulary vs. drilling certain kinds of verb and tense conjugations. They’ve helped many other students prepare for tests, quizzes, and real-world challenges, while computer software can only guess at what kinds of scenarios its proteges will face.

A recent Forbes editorial by academic Thomas Davenport suggests that, while AI is getting all the hype right now, other forms of computing or machine learning are still going to be more effective for a lot of basic tasks. From a marketing perspective in 2023, it’s helpful for a tech company to throw the “AI” brand around, but it’s not magically going to be the answer for every problem.

Davenport points to a similar (if smaller) whirlwind of excitement around IBM’s “Watson” in the early 2010s, when it was famously able to take out human “Jeopardy!’ champions. It turns out, Watson was a general knowledge engine, really best suited for jobs like playing “Jeopardy.” But after the software gained celebrity status, people tried to use it for all sorts of advanced applications, like designing cancer drugs or providing investment advice. Today, few people turn to Watson for these kinds of solutions. It’s just the wrong tool for the job. In that same way, Davenport suggests that generative AI is in danger of being misapplied.

While the industry and end users both race to solve the AI puzzle in real time, governments are also feeling pressure to step in and potentially regulate the AI industry. This is much easier said than done, though, as politicians face the same kinds of questions and uncertainty as everyone else.

OpenAI CEO Sam Altman has been calling for governments to begin regulating AI, but just this week, he suggested that the company might pull out of the European Union entirely if the regulations were too onerous. Specifically, Altman worries that attempts to narrow what kinds of data can be used to train AI systems – specifically blocking copyrighted material – might well prove impossible. “If we can comply, we will, and if we can’t, we’ll cease operating,” Altman told Time. “We will try, but there are technical limits to what’s possible.” (Altman has already started walking this threat back, suggesting he has no immediate plans to exit the EU.)

In the US, The White House has been working on a “Blueprint for an AI Bill of Rights,” but it’s non-binding, just a collection of largely vague suggestions. It’s one thing to agree “consumers shouldn’t face discrimination from an algorithm” and “everyone should be protected from abusive data practices and have agency over how their data is used.” But enforcement is an entirely different animal. A lot of these issues already exist in tech, and are much larger than AI, and the US government already doesn’t do much about them.

Additionally, it’s possible AI regulations won’t work well at all if they aren’t global. Even if you set some policies and get an entire nation’s government to agree, how to set similar worldwide protocols? What if US and Europe agree but India doesn’t? Everyone around the world accesses roughly the same internet, so without any kind of international standard, it’s going to be much harder for individual nations to enforce specific rules. As with so many other AI developments, there’s inherent danger in patchwork regulations; it could allow some companies, or regions, or players to move forward while others are unfairly or ineffectively stymied or held back.

The same kinds of socio-economic concerns around AI that we have nationally – some sectors of the work force left behind, the wealthiest and most established players coming in to the new market with massive advantages, the rapid spread of misinformation – are all, in actuality, global concerns. Just as the hegemony of Microsoft and Google threaten the ability of new players to enter the AI space, the West’s early dominance of AI tech threatens to push out companies and innovations from emerging markets like Southeast Asia, Subsaharan Africa, and Central America. Left unfettered, AI could potentially deepen social, economic, and digital divisions both within and between all of these societies.

Undaunted, some governments aren’t waiting around for these tools to develop any further before they start attempting to regulate them. New York City has already set up some rules about how AI can be used during the hiring process while will take effect in July. The law requires any company using AI software in hiring to notify candidates that it’s being used, and to have independent auditors check the system annually for bias.

This sort of piecemeal figure-it-out-as-we-go approach is probably what’s going to be necessary, at least short-term, as AI development shows zero signs of slowing down or stopping any time soon. Though there’s some disagreement among experts, most analysts agree with Wharton professor and economist Jeremy Siegel, who told CNBC this week that AI is not yet a bubble. He pointed to the Nvidia earnings as a sign the market remains healthy and not overly frothy. So, at least for now, the feverish excitement around AI is not going to burst like a late ‘90s startup stock. The world needs to prepare as if this technology is going to be with us for a while.

What the Future of Rivian Looks Like According to CEO RJ Scaringe

David Shultz

David Shultz reports on clean technology and electric vehicles, among other industries, for dot.LA. His writing has appeared in The Atlantic, Outside, Nautilus and many other publications.

What the Future of Rivian Looks Like According to CEO RJ Scaringe

Rivian CEO RJ Scaringe took to Instagram last weekend to answer questions from the public about his company and its future. Topics covered included new colors, sustainability, production ramp, new products and features. Speaking of which, viewers also got a first look at the company’s much-anticipated R2 platform, albeit made of clay and covered by a sheet, but hey, that’s…something. If you don’t want to watch the whole 33 minute video, which is now also on Youtube, we’ve got the highlights for you.

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