In short
OpenAI’s pivot away from in-chat shopping/checkout; chip-industry bets on SRAM-based inference to address the memory crunch; how stock-based compensation costs are affecting tech company finances; Anduril’s Ohio factory as it scales defense manufacturing; Synthesia’s enterprise AI video platform and ROI.
Guests and backgrounds
Anne Guillen (The Information e-commerce reporter). David Levy (general partner at Porch Capital; former AWS business development executive; wrote on Groq/AWS Cerebras and memory). Jackson Ader (Managing Director, KeyBank Capital Markets; authored a multi-part series on stock-based compensation). Corey Weinberg (The Information Deputy Bureau Chief of Finance; profiled Anduril’s Ohio factory). Peter and Carly (Synthesia CTO and SVP Customer Success; enterprise AI video executives).
Key claims + notable examples
OpenAI’s checkout pullback shifts commerce partners’ integration plans; PayPal (24,000+ employees, enterprise subscriptions) must renegotiate; Disney’s Sora licensing/investment ($1B) could complicate partner expectations. Groq and AWS Cerebras use SRAM (on-chip) instead of HBM to mitigate HBM supply constraints; “bottleneck whack-a-mole” may move to CPU/networking; Fastly is cited for AI-driven demand without hosted inference. Stock-based comp: Russell 1000 software median expense 13.8% (2024) vs 1.1% other companies; trend starting to decline (median <12% in 2025) amid layoffs. Anduril: Ohio factory (~20 miles south of Columbus) for Fury autonomous unmanned fighter finalist and Barracuda cruise missile; manufacturing leadership includes ex-Tesla Keith Flynn; approach emphasizes assembly-line scaling with commercial components. Synthesia: enterprise differentiation via long-form, multi-scene consistency, brand kits, and model orchestration (Vio/Sora); ROI via faster localized onboarding/compliance updates; “AI slop” is deprioritized in favor of reliability/control/security.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Chapters
Tap a time to open that second in VOOpenAI's Shift Away from E-Commerce
1:20 to 4:24
A discussion on OpenAI's pivot from shopping integrations and its impact on partners.
“has had ripple effects for the different e-commerce and payments companies that were working with OpenAI on shopping integrations.”
The Future of PayPal and OpenAI
4:24 to 5:50
Exploring the implications of OpenAI's changes for PayPal's partnership.
“So basically the headline here is that OpenAI has promised the world to its customers saying we're going to do everything.”
Etsy and Stripe's Relations with OpenAI
5:50 to 8:34
Insights into how Etsy and Stripe are adjusting to OpenAI's new focus.
“And just to be clear, on the PayPal side, do we know that PayPal was, you know, that they had committed to buying a block of enterprise subscriptions in return?”
E-Commerce Data Control and Checkout Experiences
8:34 to 11:08
Discussion on e-commerce companies gaining control over checkout processes.
“rules that governs how to make purchases through AI apps like ChatGPT.”
Understanding DRAM and HPM in AI Systems
14:00 to 21:16
Learn about the role of DRAM and high bandwidth memory in inference systems.
“And last question for you, then we'll get into the thrust of the column.”
The Impact of Custom ASICs on AI Hardware
21:16 to 21:30
Explore how custom ASICs are changing the landscape of AI hardware.
“So I guess that's the sector that we should be watching, these custom ASICs.”
Trends in Stock-Based Compensation Among Tech Companies
22:20 to 28:00
Discuss the historical trends and implications of stock-based compensation in tech.
“Well, I guess first, let's set a little bit of background and context.”
Understanding Employee Stock Compensation
28:00 to 29:50
Explore why employees seek high stock-based compensation despite market downturns.
“they prefer something closer to 35 percent of their total compensation so it's so funny that employees demand it.”
The Impact of Stock-Based Compensation on Company Finances
29:50 to 33:00
Learn how stock-based compensation affects company cash flow and investor perceptions.
“On the flip side, companies are constantly repurchasing shares to sort of keep the share count in check.”
Trends in Stock-Based Compensation
33:00 to 35:00
Discuss the current trends and projections for stock-based compensation in the tech sector.
“So now let's bring it back to where we started the segment.”
Show all 18 chapters
Inside Anduril's New Factory in Ohio
35:30 to 40:00
Discover the details and strategic reasons behind Anduril's new production facility.
“about not just what he saw, but what it tells us about Anduril's place in the defense tech race.”
Innovation Strategies at Anduril
40:00 to 42:01
Unpack Anduril's approach to innovation and competition in the defense industry.
“It's banking on this sort of shift within the U.S.”
Anduril's Manufacturing Innovations
42:01 to 47:50
Explore how Anduril is revolutionizing defense manufacturing with new approaches.
“You know, they want to take stuff that it's been tested commercially, or we know that works.”
AI Video Generation with Synthesia
48:09 to 56:00
Discover how Synthesia is using AI to transform video production for enterprises.
“I spoke with Synthesia's Chief Technology Officer at SVP of Customer Success.”
Specializing in Enterprise Video Solutions
56:00 to 56:29
Learn how Synthesia focuses on its core competency in enterprise video.
“For us, though, we are going to absolutely specialize in the things we do best and that's providing enterprise video.”
The Impact of Chip Technology on Application Layer Companies
56:30 to 57:09
Explore the considerations of chip technology for application layer companies.
“That is what we do best, of course, with many things.”
Leveraging NVIDIA Infrastructure for Performance
57:10 to 57:41
Discover how Synthesia uses NVIDIA infrastructure to enhance their services.
“We're an application layer company, so we're only one separate move from the hardware.”
Thanking the Guests and Show Closure
57:42 to 58:09
Hear the hosts express gratitude to the guests and summarize the episode.
“better work on the video and the voice models and computer vision.”
Transcript
Automatic transcript. May contain errors.0:13Welcome, everyone, to The Information's TITV. My name is Akash Pasricha. It is Monday, March 23rd. We are kicking off the week with some exclusive reporting the information published about OpenAI's sudden shopping pullback, a strategic shift that sent shockwaves through its partner network. Then we're turning our attention to the latest physical hurdle in the AI race, memory. I'll be joined by David Levy from Porch Capital, who published a blog post about the memory crunch. We're also looking at corporate finance, specifically how the rising cost of stock-based compensation is impacting tech companies.
0:49Plus, the Informations Deputy Bureau Chief of Finance, Corey Weinberg joins us after a rare look inside an Anduril factory to discuss his in-depth profile on the defense tech giant's manufacturing blitz. And we'll wrap the show with a segment supported by Google Gemini, where we evaluate how the AI buildout is moving past the hype to reshape specific industries, including the world of video creation. It's going to be a fun show, so let's get right on into it. OpenAI's recent prioritization away from shopping and e-commerce has had ripple effects for the different e-commerce and payments companies that were working with OpenAI on shopping integrations.
1:31Our e-commerce reporter Anne Guillen wrote a deep dive on how that drama could have broader repercussions for OpenAI's business, and I want to bring her on to talk all about it. Anne, welcome back to the show. It's great to have you here. Hey, Akash. So you reported a few weeks ago that OpenAI has pivoted away from putting checkout inside its platform. Now it's going to be living somewhere in these apps that it's going to co-develop with partners. And it's sort of the latest data point in the broader step away from focusing on e-commerce and shopping, which is not what the case was six months ago.
2:08And so the question I have for you and the question that you started to look at in your story was, how does this broader shift away from shopping? How is that sitting with all of the partners and the tech companies that OpenAI was working with? Yeah, I mean, I think it's not even just a question of what's happening with the commerce partners. I think, you know, the commerce partnerships are maybe just kind of the most concrete example we have so far of kind of the effects that this push that OpenAI is undertaking right now to cut down on some of their side quests and side projects and really refocus on the core chat GPT app and experience.
2:51and also focus on selling more of its tech to big businesses, big companies. I think we're seeing on the commerce front, you know, kind of the most immediate, you know, tension that is resulting from that shift. And so, I mean, I think, you know, with commerce, but also with some of these other side projects, OpenAI had committed to partnerships or deals with outside companies to help them, you know, construct these features, get them off the ground. And in several cases, these companies also committed to being big spenders on OpenAI's tech for their employees. So one example that's not related to commerce, but I think is pretty instructive here is Sora.
3:39You know, we've reported that OpenAI is planning to fold Sora into the main chat GPT app more, and it's unclear what will happen to Sora over the long term. But a key partner that OpenAI has tapped on the Sora front is Disney. In December, Disney announced an agreement with OpenAI to license its characters to appear in Sora videos, and Disney also said that it would invest a billion dollars in OpenAI. And so now with Sora's future a little bit more unclear, uncertain, you have to wonder if there's an impact on that relationship with Disney. And so we see that playing out with some of the commerce partners as well, which is what I cover in my story from today.
4:24So basically the headline here is that OpenAI has promised the world to its customers saying we're going to do everything. And to do that, we're going to partner with all these other companies, whether they're shopping companies or content companies like Disney, for example. And these companies were super excited about it because they get to attach themselves to OpenAI. They see their stock jump a bit. And now as OpenAI focuses, I guess based on your story, what you're saying is that this could actually complicate then the enterprise sales that OpenAI wants to make to those very companies who could be their biggest customers.
5:01Right, exactly. And I mean, we spelled this out clearly in the story. According to my reporting, those relationships are not in danger yet. They're not changing. But I mean, I think you look at PayPal. You know, PayPal's original announcement of its partnership with OpenAI was that it was going to add its wallet as a payment option for shoppers in ChatGPT checkouts later on this year. PayPal is going to start handling some of the payments behind the scenes for some of these in-chat checkouts. So that's a big business opportunity for PayPal to start, you know, handling more payments volume and also, you know, kind of get its users using ChatGPT and paying with PayPal on ChatGPT.
5:47But there's no more checkout. So, you know, given that OpenAI has kind of moved away from checkout and now, you know, the shopping efforts that are continuing are more focused on search and discovery, you know, how does a payments company like PayPal fit in? So, you know, I've reported in my story today that PayPal and OpenAI right now are currently discussing kind of what the next best step for their relationship is and, you know, kind of how to readjust the partnership so that, you know, there's some value for both companies. And just to be clear, on the PayPal side, do we know that PayPal was, you know, that they had committed to buying a block of enterprise subscriptions in return?
6:36Was that the idea? So at the same time that PayPal announced they would be putting their checkout technology into ChatGPT, PayPal also said it would increase its spending on OpenAI's APIs. They would provide enterprise ChatGPT subscriptions to their more than 24 ,000 employees. So, you know, that part of the agreement isn't changing. PayPal is going to remain a customer of OpenAI's from what I understand. But you do have to recognize, like, the relationship now looks a little bit lopsided that PayPal is, you know, giving OpenAI all the spending and, you know, checkout isn't really in there. Right.
7:19And conceivably, nobody would be using the PayPal checkout as much now because it's not as prominent in the chat GPT interface. The two other companies that you talked about that intrigued me were Etsy and Stripe. Very quickly, what's the story with both of those companies? Sure. So Etsy is a little bit more in the middle. Their original announcement to partner with OpenAI on some of the original checkout features, that's separate from any spending agreements that they might have with OpenAI. But now a lot of the development of those commerce features and the app, you know, that falls on Etsy versus, you know, a partnership with OpenAI where they would work more closely.
8:06And Stripe is probably more insulated. Their relationship with OpenAI kind of predates some of these shopping and commerce efforts. Stripe handles the billing for OpenAI's consumer subscriptions business. So that gives them another kind of line of work with OpenAI that's pretty separate from OpenAI's commerce efforts. And there's still, you know, those Stripe and OpenAI are still committed to working on the agentic commerce protocol together, I've reported, which is kind of the set of rules that governs how to make purchases through AI apps like ChatGPT. But it's unclear how much of a priority that work will be for OpenAI going forward.
8:50So more of that work could fall to Stripe. It is kind of funny to me. There's no way of knowing, of course, what the net impact would be on each of these companies' bottom lines because we don't know the exact dollar figures here. But this is a little bit of like, let's get all of our products everywhere from both sides of the company. Because conceivably, you know, if Stripe or Etsy or PayPal is saying, we're going to spend all this money on you for your enterprise subscriptions. But you have just promised to spend the same amount of money or, you know, we have to get that money back basically in terms of increased traffic of our products.
9:29I mean, again, we have no idea what this would mean in terms of both companies' profitability, but, you know, there's a little bit of you scratch my back, I scratch yours. Exactly, yeah. We'll save the world together. Last question for you, Anne. Could this end up working better for the e-commerce companies at all in the sense that previously on the show you've talked a little bit about how depending on where the checkout is, there's a question around how much data the e-commerce company or the payments company gets. Was that ever at risk with the all-in-one platform, ChatGPT, or where does that stand?
10:07Yeah, I mean, OpenAI has said they got feedback from some of these early partners that they wanted, you know, the merchants and the marketplaces wanted more control over the checkout experience. And so I think moving away from the in-chat buy button, that certainly does give the retailers and the marketplaces back a little bit more control. The payment company is a little bit less so because they're more behind the scenes anyways. So I think this is probably net positive for now for some of the merchants and the retailers because they will get a little bit more insight and control into the checkout process.
10:56But kind of the flip side of that is there is more work that kind of shifts to them versus OpenAI kind of building them this all-in-one experience. Great. Well, Anne, I want to thank you for coming on. That is Anne Guillen, our e-commerce reporter, here at The Information. NVIDIA's new Grok chip has been all of the excitement in the chip world. But David Levy, a general partner at Porch Capital and a former AWS business development executive, argued in a blog post that this chip, along with AWS's announcement that it will deploy Cerebrus's chips, are actually about the memory crunch that we are seeing play out.
11:35I want to bring on David to walk us through his thoughts. David, welcome back to the show. It's great to have you here. So, David, how are you thinking about the NVIDIA Grok chip and AWS's play with Cerebrus? Well, if you notice, the one thing that's consistent through both is that they're opting to use systems, the NVIDIA and AWS, they're opting to work with systems that are predicated on SRAM, not high bandwidth memory. And those are two different things that we've all had to learn in the last few months. Which are what? So walk us through the differences between SRAM and HBM. Okay, so high bandwidth memory, which is HBM, it's basically fast DRAM.
12:18Most AI systems have been built around that. Most GPUs have been built around that. And because of the explosion of inference, it's become supply constraint. When it also sits next to the chip. SRAM sits on chip. It's very, very fast. And so it's not subject to the supply constraints that HPM have right now. So the systems from Grok and the systems from Cerebris both use SRAM and are not reliant on HBM. And so my... So it's a little bit of chip 101 here so that I understand this. So basically the vectors upon which these things are different are, there's the consideration, is it living on the chip or does it live outside of the chip?
13:04It's how fast the memory is and then there's like how much memory can be stored on it. Are those the different vectors? And so HBM is very dense. and you can have lots and lots and lots of capacity when you have it. And it's faster than regular DRAM, but it's not as fast as SRAM. It's also relatively cheap compared to SRAM. The per gigabyte cost of HBM is an order of magnitude less than, I think it's an order of magnitude less than the per gigabyte cost of SRAM. SRAM, by contrast, sits on the chip. So it's the latency between the instructions from the chip into the memory is very, very, very low because of its, quote, location.
13:54It's also, it happens to be very fast. The problem is with SRAM is it can be expensive because, and it's limited in capacity by the size of the chip. Got it. And last question for you, then we'll get into the thrust of the column. You mentioned DRAM, and I know that's not as relevant to the column, but what is DRAM here? DRAM is your computer memory. And so HPM is a type of DRAM. It happens to be packed very tightly in a certain way that you can have super high capacity. And it also has, well, it's called high bandwidth memory for a reason. The throughput between the chip and HPM is very quick relative to if you were going to something like regular DRAM.
14:44Okay. So now that we have our definitions in place, now the thrust of your column is what? You've noticed these deals, and you're saying that the SRAM, it's on the chip. Just walk us through that now that we have the context. Yeah. So in short order, and by shorter, I mean in the last few months, you've had at least two, if not several, major transactions or partnerships. So number one, on Trista's eve, NVIDIA announces this$20 billion deal for Brock. It's not a total acquisition, it's this oddly structured asset thing. But the clear thing is that NVIDIA was concerned enough about their capability and scaling inference that they felt the need to spend$20 billion to do this deal.
15:35All right. AWS, AWS, I think it was last week, announced a partnership with Cerebris, where they're going to launch their inference service with Cerebris wafer-scale chips that have SRAM on them next to their own Tranium chips. So both of those companies, AWS and NVIDIA, have and had existing hardware in Silicon. But they both felt the need to either go out and do a partnership in AWS's case or spend tens of billions of dollars to get access to this IP from Grok. And again, you're saying basically so that they can get the memory on the chip, which is a key constraint. constraints yeah the you know the the the uh point of the column was that a lot of this the overarching theme is that inference is exploding and inference is a memory problem less so than a compute problem training is a compute problem uh inference is a memory problem because you're constantly moving things on and off memory uh and so you can do that to avoid the supply constraints and much, much more quickly by using SRAM.
16:48And so Cerebris and Garak have figured out a way to do inferencing without putting all of the stuff onto HBM and instead using SRAM. So for each company, it mitigates the requirement for HBM, which is a giant constraint. So my kind of like sort of tongue-in-cheek but honest thesis is that these types of systems, these types of inferencing systems are becoming more prevalent and more desired because they're not reliant upon what's the current bottleneck, which is high bandwidth memory. So let me ask you this then. So if inference, in your mind, what you're saying is, I mean, the inference, it's about the memory in many ways.
17:31How do you think then the memory chip supply chain crunch, I mean, if that hadn't played out the way that we have seen it. Are you saying that these deals wouldn't have transpired the way that they did, or...? I think they still probably would transpire. There's a more urgent need because of the constraint on high bandwidth memory supply. But the SRAM-based systems claim to have higher throughput and a better cost per token than these HBM-based systems. And again, these are systems. So keep in mind that when you're running an AI system, you're not just running a chip, you're not just using memory, you're not just using compute, you're not just using networking.
18:15It's all of these things combined that make up the price performance of the system. And so by working with Grok, I think that NVIDIA more or less mitigated the concern people had about them scaling inference. And I think AWS felt the need to work with Cerebris to do the same thing. Now, you also talk in your column about this idea of bottleneck whack-a-mole and the idea that today it's memory ships, tomorrow it could be something else. Where do you see the next bottleneck coming? Yeah, the whack-a-mole is that in 2020, like, GPUs were stuck on boats and recently and still power and energy supply constrained as well as memory now.
18:58If I had to guess where the next constraint would be, it would be in CPU and networking. And the reason is because as you go to this ejectic AI systems, the workloads become so complex, they require a lot more orchestration. You've already seen an example of this. There's a company called Fastly. It's an old content distribution network. They had two blowout quarters and the stock tripled. And the reason is that they've had AI tailwinds and they have no hosted inference. Keep that in mind, they have no hosted inference. They're seeing demand increase. Which means what? So they don't offer an inference service.
19:30They're seeing demand for their CPUs just to orchestrate agentic workloads on other people's inference. So even companies like that are seeing increases in demand in CPU compute to orchestrate these agentic workloads. So I think if there's going to be a next constraint, it's going to come up in compute CPUs and in networking, where you're having orchestration and then all the hardware talking to each other. Okay, and last question for you. I mean, we hear about the custom ASICs business. How does that relate to all of this? Well, I mean, the TPUs are custom ASICs. Grok can be considered custom ASICs.
20:12Custom ASICs are specially designed to handle very, very, very fast inference when they're built for inference. And so, you know, more and more, they're being designed to not rely on high-bandwidth memory. And so, yeah, I think we're seeing people think about how they build systems that are not reliant upon whatever the current bottleneck is, whether it's memory, power, etc. So the less reliance you have on places where there are bottlenecks, the less subject you are to not being able to produce and scale your business. So custom ASICs could actually be more of a solution to some of these bottlenecks that we're seeing.
20:53Yeah, custom ASICs for sure. The custom ASICs use less silicon than a GPU does. They're specially designed. They're very, very fast. They're not all-purpose. They probably can't do these big, gigantic training modes. But if you can make a chip that is price performance better and also uses less energy, you're going to see a lot more of these custom ASICs and a lot more of these networks. Got it. So I guess that's the sector that we should be watching, these custom ASICs. Yeah, who thought we'd be looking back at memory pricing again, but here we are. There you go. It always comes back to that.
21:28Great. Well, David, I want to thank you for coming on. That is David Levy, a general partner at Porch Capital here on TITV. Stock-based compensation has been one of the most important tools for CFOs at big tech companies to leverage to grow their businesses and also to reward employees. Some people argue, however, that stock-based comp may have gotten slightly out of hand. I want to bring on Jackson Ader, Managing Director at KeyBank Capital Markets, who I know has thoughts on all of this. Jackson, welcome back to the show. It's great to have you here. Thank you, Akash. Yeah, it's good to be back.
22:03So you wrote this four-part series on stock-based comp, which I guess that's what we're doing now. So it really was a fascinating read. What was the main message you were trying to get through to the community with these four reports you put out there?
22:27Jackson Ader:Well, I guess first, let's set a little bit of background and context. It's for thus far, right? I don't want to promise any future research, but I think we've got probably at least another one coming in the future. we'd like to do some work on whether stock-based comp actually matters for returns, right, and correlate to multiples. But for thus far, what we wanted to get out of this was really just reflect the conversations that we've been having with investors over the last kind of six to nine months and package it in a way where we can all agree, what exactly are we talking about? what should matter, what does matter to investors, how should we treat stock-based comp, and then certainly laying the groundwork for what are the trends.
23:19Jackson Ader:Because there's been actually a, I would say, a five-year trend or so, or a five-year line that you can draw from the 2020 and 2021 timeframe through to today. And so just framing that historical context was also important to us and so what what is the trend where did it end up walk us through some of the big numbers i mean i i i've got a few listed down here but i'll i'll let you sort of share what you thought the biggest findings were so in the what what i would call you know the late 20 teens or so um stock-based compensation as a percentage of revenue not just overall for the sector but even for the large established incumbent companies and software, stock-based compensation as a part of revenue or as a part of the total expenses for these companies started to move higher.
24:14Jackson Ader:And then you had a wave of fresh IPOs, of fast-growing software companies that also would have been issuing a lot of stock to their employees because it's a source of funding. And so the general trend was up, up, up, and even outpacing the sector's revenue growth. So giving employees more shares than even, or I guess, hiring and giving employees more shares than even their overall expense growth and overall revenue growth. And what was interesting is that in the 2022-2023 timeline, after software multiples, I mean, I don't think it's too dramatic to say multiples collapsed from the highs in 2021 to kind of the nadirs in 22 and 23.
25:05Jackson Ader:We did see a bit of a reset in terms of grants or stock-based compensation grant values. But then they quickly rebounded as the sector started hiring again and as employees started demanding, again, more restricted stock units instead of cash. Right. And I mean, some of the numbers that stood out to me from your report, I mean, you pointed out uh and this was a number that our co-executive editor martin pierce cited in his column last night actually i mean your report said that the median stock compensation expense for software companies in the russell 1000 was 13.8 percent in 2024 so that's software companies 13.8 percent but the median for the all the other companies in the index i believe that's what it was 1.1 percent so i mean this is a 12 point something percentage point delta uh i mean so walk me through so are you arguing basically that this needs to come down you know how are you thinking about it so um i guess first to be fair to software i don't want to be a total homer here but to be company's expense base is labor and ends up being what you pay to employees.
26:32Jackson Ader:So relative to maybe a manufacturer or a logistics company, other sectors of the economy, less of their expense base is going to be tied up in labor. So it's not exactly a perfectly fair fight. But still, 13 versus one, I don't think we can just hand wave that away. So what we are saying is, is we expect the trend over time for software companies certainly to, I think the phrase we've used before is age gracefully, right? And so I think that means - That's a nice way of putting it, Jackson. Yeah, and I think that means let's pay our employees a little bit more in cash, the mix of the overall compensation, more in cash versus stock.
27:24Jackson Ader:But what's interesting Akash is we also, as part of this series, ran a survey. So we asked 300 employees of publicly traded companies, 100 of which are employees just of software companies and 200 of which are outside the software sector. um the stockware employees certainly get paid when asked you know their mix of cash versus stock certainly get paid more than others in terms of their of their stock compensation but they also want more they get paid about 25 percent or so of their total compensation in stock and they prefer something closer to 35 percent of their total compensation so it's so funny that employees demand it.
28:12I'm just trying to understand. Did you talk to these people? Why, when in a climate where we are in a SaaSpocalypse, why would these employees want more stock-based comp?
28:27Jackson Ader:I don't have a good answer for you. I expected the numbers to be lower. I'll just say going into that survey, my hypothesis would have been that the numbers would have been lower. Certainly, you can look across the SaaS and the software landscape and say, you know, the stock used to be 100 and now it's 50. And so I would like some cash, please, in my compensation. You know, it gets into a little bit of psychology. At the same time, if you're working for a Salesforce or a ServiceNow, you might say to yourself, I don't know. I mean, is it all that crazy to think that we could be the next NVIDIA, right?
29:08Jackson Ader:If you would have asked NVIDIA employees five or six years ago where they expected the stock to be today, I'm not sure if anybody would have said where it is. There is still an aspect of if I get paid the chance for a life-changing amount of wealth, that is going to come from equity ownership. My argument is cash can also buy company shares. right um but yeah it kind of gets into the psychology it was just very surprising also to us that people that already get a bunch of of stock-based comp wanted even more right now i just want to make sure that that we hit home sort of why stock-based comp that is too high can adversely affect a company's financial profile i mean my understanding of this was that look, you have to issue shares in order to pay people with stock-based comp.
Read the full transcript
30:07On the flip side, companies are constantly repurchasing shares to sort of keep the share count in check. Is that your understanding of the way that this, in the end, will affect the company's cash flow profile? Because we all know that we look at the cash flow statement, stock-based comp, I mean, it's a non-cash item, but then I guess it's the repurchases where it comes back to bite you.
30:32Jackson Ader:Yeah, it's certainly the repurchases that come back to bite you, from a cash flow perspective. But it's kind of twofold. If you asked an employee, hey, how much money do you make? They would not say only the cash component of their salary. They would include both the cash and the RSUs that get granted to them. each and every year. And so on the one hand, you have investors that are, you know, potentially new investors to software, like a value investor, you know, or someone who's been taking a broader look at other sectors and saying, okay, how does software stack up relative to other sectors that I've covered in the past?
31:19Jackson Ader:And they say, I'm looking at the gap income statement. I'm looking at the quote unquote economic value of this company. And if there is a huge swath of the expenses that are just not being accounted for on the cash flow statement or on non-GAAP earnings, that investor is going to say, no, no, no, no. The total expenses here should also include this thing that employees say is important to them and that would certainly be demanded by those employees on an ongoing basis. Then you bring up a great point, which is, okay, well, you give shares. I mean, that is value. That's dilution. That means you have to issue shares in the future.
32:03Jackson Ader:And so that's why in our analysis, we choose to say, all right, we forecast a fully diluted share count and we forecast that fully diluted share count to grow over time, even into perpetuity as part of our discounted cash flow analysis. And so you can make an argument that maybe forecasting future dilution and also including the stock-based compensation in your economic expenses is kind of double burdening. I don't know. I hear good arguments on both sides. I think what is definitely clear is that software companies are saying with regularity, we are repurchasing shares to offset dilution. and in the metrics that we all use to value these companies like unlevered free cash flow or straight free cash flow or free cash flow to equity, those repurchases are just, they lie outside of those reported metrics.
33:01Jackson Ader:And so it ends up inflating the multiple at which these companies trade and you have to start doing some adjustments if you are going to be comparing software companies with their 13 % stock-based comp to other companies with their 1 % stock-based company. Right. So now let's bring it back to where we started the segment. Do you think that it's going to come down? Are we seeing evidence that it's starting to come down? I mean, we talked about the trend we've seen to date. Where is this going? We are. We are starting to see the trends come down. Again, you got to dig through the Ks, which have just been filed to get to the actual grant values.
33:45Jackson Ader:A lot of companies only disclose the restricted stock unit grant values in the Ks filing. But our friend Nate on our team actually just pulled some numbers here just a second ago, if I can double check them, that the median company as of 2025, stock-based compensation as a percent of revenue down to less than 12 % in 2025 versus 13 in 2024. before. And so we are starting to see it come down. We saw year to date in the first three quarters, the actual grant values come down as well on a year over year basis. Some of that is certainly manager preference, right? Doesn't sound like it's employee preference, but some of it is manager preference to shift more toward cash.
34:35Jackson Ader:And we've heard some companies be explicit about that. And then the sadder portion of that really is that layoffs, have started and might be continuing. And so it's not just stock-based compensation that's coming down. It's all types of compensation that are coming down as a percent of revenue as margins float higher. Great. Well, Jackson, when you write part five, come back on the show and tell us more about what you found. I want to thank you for coming on. That is Jackson Ader from KeyBank capital markets here on TITV. Anduril has bold ambitions for its work in the defense sector, and at the center of attaining and fulfilling the big government contracts it is aiming for, the company is building out a giant factory in Ohio.
35:23The Information's Deputy Bureau Chief of Finance Corey Weinberg visited the factory recently and published an in-depth profile about not just what he saw, but what it tells us about Anduril's place in the defense tech race. I want to bring on Corey to share more about what he learned. Corey, welcome back to the show. It's great to have you here. Hey, Akash. So where is this factory that you visited? Well, I journeyed to the great state of Ohio. The factory is about 20 miles south of the city of Columbus in Pickaway County, Ohio, surrounded by soybean fields, cornfields, quite a rural area just near Columbus.
36:05a lot of industrial warehouses and a lot of data centers, as you might expect. Why did Anduril pick that state of all states to build their new factory? Yeah, no, good question. I mean, it's there are a multitude of reasons. One, you know, they got, you know, nice, a nice tax incentive package. That's always, that's always nice um but it's also got an air force base there has an air field there and they're going to be building fighter jets uh as one of the the kind of weapons or vehicles that they're building in the factory so that's useful for for testing and things like that okay so you get to the factory and walk us through the the big questions that you were trying to get answered as you were going into this visit to the factory uh well it was my first defense factory that i had been to so uh what what do these things look like uh was one question on my mind and uh yeah i was there with andrel executives and so what is their messaging and framing going to be about what they're trying to do because i think just taking a step back here akash like this is a huge pivot moment for andrel It is a turning point.
37:24They are going from a company that has not been producing at scale. They have been producing in a few factories around the world, in part that they had purchased. They have an R &D production center in Southern California where they're based. This is their first attempt to really produce and manufacture at scale and actually try to, you know, sort of fulfill large contracts that they would be winning from the U.S. military. So, you know, I was kind of curious about all the, you know, sort of details around how do they actually do that? Like, how do they how do they sort of make that a big jump into the big leagues?
38:08And remind us, what is it that they're intending to make at this factory? yep so a few things first off that they that they flagged um uh probably the most high profile project that they'll be working on there is what they've called the fury fighter jet this is an autonomous unmanned aircraft that they are a finalist for in this competition from the u.s air force to create a collaborative uh combat aircraft it's supposed to be a plane that flies with the manned fighter jets in battle. And this one would be smaller, cheaper, autonomous. And Anduril is a finalist alongside another defense company called General Atomics to actually produce and build that aircraft.
38:57And the Air Force should decide within months who is actually going to win that contract or how they're going to divvy it up. Anduril will also be building, they say, their Barracuda cruise missile in the factory. And intriguingly, as is often the case with sort of defense companies, there is a classified confidential project that they say will be in the factory. So, you know, I want to go back to what you were talking about with the scale that they have to achieve with this factory. I mean, as they compete with these bigger companies that have been around so much longer, I mean, you mentioned General Atomics for this one contract.
39:40You also mentioned in your story Lockheed Martin, Raytheon, these companies that have been around for decades, they have their existing facilities. Did you get a picture into what the actual innovation is that Andrel is banking on that will help it win these contracts and ultimately actually make it a significant player in this game? It's banking on this sort of shift within the U.S. military and militaries around the world. to go from sort of what's termed large, expensive, exquisite systems for war. These would be the Tomahawk missiles. These would be the F-35 fighter jets. These huge, expensive systems that we buy, that the U.S.
40:34government buys for war. and real is saying we're not really trying to build those we're maybe trying to like we're definitely trying to build more expensive things than we were before we're building an unmanned fighter jet for instance but they're saying we can do it more cheaply um uh we can do it uh faster uh and so and with sort of commercial parts that was kind of a big part of the message that i got from andreal executives at the factory is, you know, they are trying to reduce supply chain risk and the risk that some component manufacturer goes out of business or has cost overruns by sourcing a lot of their material from sort of commercial providers of jets or boats or what have you.
41:25So is it fair to say that it's a little bit less product innovation that's more like supply chain innovation or yeah i think it's more i would say it's business model innovation it's taking and that's i think a good way to you're getting at the right question about andrel because i think it's one thing that i've been trying to like get my head wrapped around as well is this company and a fair number of like defense tech companies as well they're trying to not take tech risk um you know they're trying not to say like hey we have this like totally untested technology that we want to sell it to the government.
42:02You know, they want to take stuff that it's been tested commercially, or we know that works. You know, they don't want to necessarily push the boundary too much on how do you actually manufacture them. This factory is very simple. It's essentially an assembly line. And, you know, try to ensure that that's not what's holding them back is the tech. Right. Now, you spoke with some of the executives on the ground there. One of the people that you mentioned the story you spoke with one of the leaders for the manufacturing operations. Keith Flynn was his name. I wonder what you gleaned from the conversations with him.
42:39You know, what's his own background? You know, how is he approaching this innovation in manufacturing that you talk about? Yeah, so they had a couple ex-Tesla guys, for instance, including Mr. Flynn, who are manning that Anderle factory or the company's manufacturing efforts more broadly. I mean, look, I think they're confident. They're saying, you know, and they've been through these weeks of production hell on, you know, sort of the Tesla Model S vehicle and things like that. You know, they say, look, there has been this wave of new manufacturing innovations that we've seen at a Tesla or SpaceX or wherever, you know, where you can really use software to simulate and sort of figure out beforehand how you're actually going to make this thing.
43:31You know, sort of how are you going to actually attach the wings to the body of the airplane? You know, sort of all these things that you can do to kind of really dumb down the actual assembly process and ensure that you have a low error rate in your factory. And he's saying that essentially, you know, they're right at the beginning of that process where they're going to, you know, start actually building and assembling a large number of missiles and aircraft and things of that nature. And so there's sort of this mixture of humility and sort of boastfulness or confidence, I would say, on behalf of Andrell.
44:12It's a bit of like, hey, we've kind of been there before with, you know, car companies or airplane companies or whatever. And we're just going to apply that to defense. You know, we'll see. It hasn't really been done before. But what do industry experts, I mean, people who maybe are people who are not at Anduril or any of the other companies, I mean, what do they tell you about this manufacturing innovation that Anduril is pitching? I imagine that Lockheed and Raytheon and General Atomics, I mean, I imagine everyone's kind of doing this, right? Yeah, definitely to a degree. I mean, like the difference here with Andrel, they're using a, you know, a ton of venture capital that they have raised to essentially build out in front and take a bet that, you know, they're going to win these contracts and that this factory is going to be humming.
45:06That's like a key thing is they have this, you know, risk capital that's willing to, you know, sort of take a bet on the fact that Andrel is going to win these contracts and they're going to keep these assembly lines humming. um a lot of kind of traditional larger prime contractors um they're not building a ton of new factories or and if they are they're tied to a very specific contract that they've won um so it's just a little bit of a different way of doing things and it's you know the difference is the fact that you know andreel sort of they don't have public shareholders that they're trying to uh satisfy they have uh injuries and horowitz and founders fund who's telling them you know go big swing for the fences but i i guess the question i i was hoping to get at was the the industry experts that you spoke to people who have been in this industry for a long time who have seen many companies come and go do do they feel like this approach that anduril's taking with vc money with these newer factories i mean are they confident in anduril's prospects here or do they sort of have the viewpoint that you know what it's harder than you think let's see you know No, it's a good question to get at.
46:20I do think people think it's hard. I think Andreal sits in this position more broadly in the industry where they have achieved the status where people are kind of still this mixture of skepticism and also giving them somewhat of the benefit of the doubt. They kind of sit in this middle ground. And that's why this sort of production kind of push for the company is such a big deal. This is like a bit of you got to prove it and show it to me that you can actually win big contracts and deliver significant, you know, sort of stockpiles of weapons or aircraft to the government because they haven't really done it yet.
47:05And so they haven't also had like huge missteps either, I think. I think they have become a big name in the defense industry, despite being a lot smaller than their competitors. And I think everyone sort of thinks like, hey, these ideas that they have around kind of cheaper, more mass manufactured sort of products for the Pentagon is one that people generally—it isn't that hotly contested necessarily. It's just, can you deliver on it? Right. Great. Well, Corey, it sounds like an exciting trip, and I imagine that there will be more trips like these to come as the company grows. Thank you for coming on.
47:50That is Corey Weinberg, our Deputy Bureau Chief of Finance, here at The Information. Our next segment is supported by Google Gemini. AI video generation is one of the most exciting applications of the technology. And to talk about it, I sat down with executives at Synthesia, a popular company in that category. I spoke with Synthesia's Chief Technology Officer at SVP of Customer Success. Here is that conversation. Peter and Carly, welcome to the show. It's great to have you both here.
48:24Jackson Ader:Thanks for having us. Okay, so Peter, I want to start with you. Remind us, I mean, in the AI video landscape, there's a lot of players out there. What is Synthesia's product? How do you differentiate yourself in the market? What are you guys really good at? I appreciate the question. We are the world's leading AI video platform for business. Right now, there's roughly 65 ,000 companies, including more than 90 % of the Fortune 100. And basically, they're there to turn ideas into professional video without cameras or studios. Yeah. Yes. And Carly, the way I understand it is your product is actually a little more focused on enterprises.
49:02You're not so much going for, you know, if I want to make a video on the weekend myself, it's more for what? For companies that want to create like training videos for their employees? Yeah, exactly. Okay. So Peter, tell me a little bit about the advances in AI video models then that have really made a difference for you. I mean, they've come a long way. At the same time, I figure there's probably technology that you guys want more advances in to help you get to even the next level. Yeah, the models have changed really quickly. It feels like every few weeks, you have a new best-of-breed model.
49:38And for us, we use every one of the best models we can find. We're trying to look for contextual content for the most part, and we think about that as B-roll. Today, we use Vio, Sora, and any other model that's highly effective there for us. It allows the creator to be able to use more creative motions. As we think about the technology on the back end, we use LiveKit in our new skills component. And so that allows for deep interaction with the avatars rather than just having a static video. So for us, it's all over the map, and we can dive into really any part of that because each one of those is super interesting.
50:21And do you guys make your own models? as well? We do. We have our own models. And so for us, we have our own video models for static video. We have our own voice models. We have our own soon upcoming real-time avatar. Right. So I've always wondered this. I mean, when you have an enterprise customer and, you know, I imagine these are like video series that they're putting together, how do you decide then, you know, which model is better for what types of videos? Is one better at creating cartoon-looking graphics versus real-life graphics? Or how does it all work? No, that's a really good question.
51:00So for us, why we have our own models, like the other Frontier models provide some fantastic videos. That said, when you look at why our customers will choose our models for most of the cases, what they really want to see is long-form content. Most of the other Frontiers are really gauged around user use cases. And the other thing is that they're going to have multiple scenes. And so it's the length of time. It's longer than 8, 12 seconds. Some of our content's in minutes, and that's just not possible with any other library. The other thing is between scenes, they want consistency. They want to make sure that their avatar, their voice sounds consistent between those frames.
51:35The other thing is that they want to be able to apply things like a brand kit. They want a logo on a shirt. They want it to be able to be in a setting that makes most sense to them. So if it's a jeweler, they want it in their jeweler, not a generic one. So there's a lot of specifics that cause us to build our own models. That said, when we think about, you know, putting that avatar or some of that detail into context, we want to see that person in motion. And that's where the frontier models are just absolutely spectacular. So for us, it's kind of combining the best of breed in both these spaces to get the best outcome for our customers.
52:11Carly, how do you then reconcile all of this video creation with this fear of AI slop, which is very much the topic of conversation these days? I mean, video, gosh, I don't even know sometimes. I'm on my feed, what's real and what's not. How do you guys approach that? Yeah, of course. So I think generally we're less focused on content, which shows up in consumer feeds. And I think that's what you're referring to is a lot of the slop that's out there. In the enterprise, obviously, the bar is different. So what really matters is reliability, control, security, whether or not our solutions save time or ultimately improve outcomes.
52:47So what we really focus on is helping our customers generate high-quality video that's easy to create, easy to update, and really grounded in what the business actually needs to communicate and teach. And what does ROI look like for your enterprise clients? Is this literally just that, hey, I didn't have to hire the five-person production team to produce that video series, and hence those are the cost savings? Or, you know, can you reach more? I imagine if it's enterprise, I mean, this is really a cost center for them, right? Yeah, I mean, sometimes. If we take the example of global onboarding, so a lot of our customers, you know, will partner with learning and development or HR teams.
53:26And what they're really focused on is potentially creating onboarding materials, management training, compliance-related training. And the content there needs to be frequent, it needs to be clear, and it needs to be localized. So taking that global onboarding example, a team might upload an onboarding deck or a handbook and then turn it into a series of short videos, leveraging an AI presenter, and then ultimately ship that to every new hire. And then when policies change, systems change, maybe there are updates needed to be made to product details. It's just as simple as updating a sentence or two in the script and then regenerating the video.
54:00So as you mentioned, no need for sort of reshooting or leveraging external agencies to manage that entire process. And then obviously there's efficiency through the one-click ability to translate into a multitude of different languages. So a number of our customers benefit from just the shift in what they were previously doing manually that now can be done dramatically faster. Peter, have you guys created your own training videos, your own employee engagement content with your own product? We do. Yeah, one of our core onboarding components is to actually have our tools introduce you to the company.
54:38In my particular department, it's introducing you to the development tools. it's walking you through a day in the life, it's walking you through how to do your basic day-to-day life. So absolutely. And we find it far more effective. So for us, our employees are just overloaded with information. The world's changing faster than you can ever imagine it. So for us, it'd be hypocritical for not to take advantage of the fact that video is one of the best ways to communicate, train, share knowledge, and do the basic training. So of course, our focus is to make it super simple and reuse it. And, you know, this is one of those times, you know, drink our own champagne, eat our own dog food.
55:15Well, and the reason I ask the question is because you're selling to enterprise software companies and we have this debate ongoing in the market right now. To what extent will people just build their own tools with AI? To what extent will they use enterprise software? These are the clients that you're serving to. I mean, as you are thinking about building your own tech stack at Synthesia, are you using only AI to build your own CRM or your own enterprise software functions? Or are you still relying on many of the companies that people are kind of scared might go away? No, definitely. I'd say a really good question.
55:52So for us, the way I think about it, in a Biverse build, we are good at certain things. I came from an Amazon environment as a prior employer and build was often the answer for different reasons. For us, though, we are going to absolutely specialize in the things we do best and that's providing enterprise video. In the case where we need a HRIS system, billing systems, we definitely are using best of breed third-party systems for that and we're building where it makes sense. For us, we are just like any other enterprise vendor. We do one thing, we do it well, and we want others who specialize in their area to be able to do their thing.
56:28We focus on human training. That is what we do best, of course, with many things. And it would be silly for us to enter into all these other spaces so it would distract us from our cooperation. Last question for you, Peter. Chips have been in the news this week with all the latest developments and newer chips that are coming out. Do you think at all in your role about, hey, we should be trying to run our workloads on this specific chip because of its capabilities? I just wonder how you think about that as an application layer company, because there's a lot of companies in the middle where you're working with cloud providers or inference providers, for example, that they probably handle the chips.
57:08But it matters to you, right? Oh, it absolutely matters. We're an application layer company, so we're only one separate move from the hardware. We have to think a lot about that. That said, we do an enormous amount of cutting-edge R &D and voice and video spaces, and that's critically important to our business. But we're going to rely on the best-in-class infrastructure to build, train, and optimize them. That is fundamental to our space. We use NVIDIA infrastructure on public cloud to optimize their performance. We also have strategic partnership, research relationship with NVIDIA, so that certainly makes it easy.
57:41And of course, they're an investor in Synthecia, and so for us, that makes it much easier for us. better work on the video and the voice models and computer vision. It really aligns closely with theirs. And so that allows us to have a collaboration on the software development as well. Great. Well, Peter and Carly, I want to thank you for coming on. That is Peter, the CTO at Synthesia, and Carly, the VP of Customer Success at Synthesia. Thank you both for coming on the show. Thank you. Thank you. That does it for today's show. A reminder, we are on this stream Monday through Friday at 10 a.m. Pacific, 1 p.m.
58:17Eastern. I want to thank you all for tuning in. We really do appreciate your viewership. Make sure to subscribe to the information on YouTube and follow us on X, Instagram, TikTok, and check us out wherever you get your podcasts. I'm already excited for our next show tomorrow. Have a great rest of your Monday. Bye-bye for now.
From the publisher
E-commerce Reporter Ann Gehan talks with TITV Host Akash Pasricha about OpenAI's sudden retreat from e-commerce integrations to focus on its core product. We also talk with Porch Capital’s David Levy about why Nvidia and AWS are pivoting to SRAM to solve the AI memory crunch and KeyBanc Capital Markets’ Jackson Ader about why software employees are demanding more stock-based compensation despite market volatility. Finally, we get into Anduril’s massive new manufacturing blitz in Ohio with Deputy Bureau Chief of Finance Cory Weinberg.
Articles discussed on this episode:
https://www.theinformation.com/articles/openais-shopping-u-turn-complicate-enterprise-playbook
https://www.theinformation.com/articles/inside-andurils-big-gamble-ohio-weapons-factory
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