Meta’s 8,000 Job Cuts, SpaceX’s IPO by the Numbers, Google's Universal Shopping Cart

20 May 2026 · 53 min · 27 chapters

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In short

Tech and finance roundup focused on Google I/O AI features, SpaceX’s upcoming IPO, enterprise software contract changes due to AI, Meta’s 8,000 layoffs, and Parker fintech’s bankruptcy.

Guests and backgrounds

  • Erin Wu, Google reporter at The Information, attended Google I/O.
  • Corey Weinberg, Deputy Bureau Chief of Finance at The Information, analyzed SpaceX IPO charts.
  • Laura Bratton, author of The Information’s Applied AI newsletter, reported on enterprise software contract shifts.
  • Lloyd Walmsley, Internet Equity Research Analyst at Mizuho, assessed Meta layoffs and AI spending.
  • Anne Guillen, e-commerce reporter at The Information, covered Parker’s bankruptcy.

Key claims and notable examples

  • Google Search agents can scan the web for tasks like apartment listings and sneaker drops; “Universal cart” aggregates products across retailers; Gemini app adds personal assistant features; coding demos included Antigravity and Gemini 3.5 Flash.
  • SpaceX: adjusted EBITDA vs net income gap is unusually wide; Starlink-linked launches are ~3/4 of launches; Space launch grows ~7–8% YoY; XAI growth lags OpenAI/Anthropic; deals include compute rental to Anthropic and planned Cursor integration.
  • Enterprise software buyers seek shorter contracts and opt-out clauses; net retention down ~15 points (EY Parthenon example); ERP flagged as potentially pressured.
  • Meta: 8,000 layoffs (~1/10 headcount) partly AI-enabled efficiency and partly cost discipline; estimated savings high single-digit to low double-digit billions annuallyized; Muse Spark model built in ~9 months.
  • Parker: raised ~$200M; corporate credit cards for e-commerce; Meta ad payment policy shift (credit cards restricted; bank/debit required) reduced transaction volume, worsening cash-flow pressures; competitors like Flex, Brex, Ramp, and Shopify are positioning to gain customers.

Written by AI. May contain mistakes. Listen to the episode to check what was said.

Chapters

Tap a time to open that second in VO

Overview of Today's Topics

0:45 to 1:37

Discussion of the key topics covered in today's episode, including Google I/O and SpaceX IPO.

“First up on the show today, Google is hosting its annual IO Developer Conference.”

Google I/O Developer Conference Highlights

1:37 to 3:41

Erin Wu discusses the key announcements from Google I/O, focusing on AI features.

“event this week, debuting a long list of new features and tools leveraging AI.”

Reactions to Google's New Features

3:41 to 5:29

Erin shares reactions from attendees regarding Google's new AI-driven features and their relevance.

“We're seeing more agentic features in search and the ability to do much more complex answers.”

Coding Announcements and Market Context

5:29 to 6:40

Discussion about Google's coding announcements and market context in AI development.

“They have this mythos model that has been like teased and very much hyped, like not quite released, but like Anthropic is really dominating on coding.”

Impact of AI on Costs and Revenue

6:40 to 10:56

Discussion on how AI integration affects Google's costs and revenue generation.

“And I do think that Anti-Gravity, their big flagship coding release is kind of getting mixed reviews on X immediately.”

Transition to SpaceX IPO Analysis

10:56 to 11:11

Introduction to the SpaceX IPO segment, bringing in Corey Weinberg for insights.

“And so this is increasing Google's costs on the one hand, but it's also increasing the amount of revenue they are able to make.”

Understanding SpaceX's Financial Metrics

11:11 to 13:20

Corey discusses SpaceX's EBITDA figures and their implications for the company's financial outlook.

“As we look ahead to the SpaceX IPO, my colleagues Corey Weinberg and Valida Pau have a story out this week with five charts that should help you make sense of this historic IPO.”

Starlink Launch Data Analysis

13:20 to 14:00

Exploration of SpaceX's Starlink launch data and its significance for the company.

“You can make whatever adjustments you want.”

SpaceX's Launch Strategy and Market Position

14:00 to 18:11

Explore how SpaceX leverages its rocket launch capabilities for its own business segments.

“And, you know, what's the actual timeline for Starship to get up and away?”

XAI Segment Growth and Future Prospects

18:11 to 21:10

Discuss the challenges and future prospects of SpaceX's AI segment and its implications.

“pretty extreme, you know, sort of business deals, spending$60 billion on Cursor, renting out a bunch of their compute to Anthropic.”
Show all 27 chapters

Enterprise Software Contracts in the Age of AI

21:10 to 24:48

Understand how companies are adjusting their enterprise software contracts due to AI pressures.

“Corey, I want to thank you for coming on.”

Net Retention and Software Vendor Dynamics

24:48 to 28:05

Examine the implications of changing net retention rates and customer power in software contracts.

“And are the software vendors giving them the shorter contracts that they want?”

AI Race and Vendor Negotiations

28:05 to 28:48

Explore how uncertainty in AI tools is reshaping software vendor contracts.

“And they don't know which software vendors are going to win this, you know, quote unquote, AI race and which AI tools are going to be better.”

Meta's Job Cuts Announcement

28:58 to 29:40

Discussion on Meta's announcement of 8,000 job cuts and restructuring plans.

“The company is set to cut 8 ,000 jobs today, which amounts to roughly one-tenth of the company's overall headcount.”

Layoffs: Efficiency vs Overhiring

29:40 to 30:58

Analyzing the reasons behind Meta's layoffs, including AI efficiencies.

“And so I think it's wise of him to try to be constantly tightening the belt, given how much they're investing in so many areas.”

Cost Savings Analysis from Layoffs

30:58 to 33:08

Understanding the financial implications of Meta's layoffs on operational costs.

“So I think they, more than a lot of companies we follow, they've been ahead of the pack in right sizing.”

Investment in AI and Model Development

33:08 to 34:13

Examining the effectiveness of Meta's AI investments and product developments.

“So all of this is in service of better AI, and yet it feels like we maybe haven't seen the better AI that everyone's hoping for.”

Meta's AI Challenges and Opportunities

34:13 to 35:42

A look at Meta's AI models and the challenges they face in implementation.

“of CapEx, I think were disturbed because we had so little visibility into whether or not they could build a good model, whether or not they could catch up to the frontier.”

Manis Acquisition and Regulatory Hurdles

35:42 to 36:55

Discussing the uncertain future of Meta's acquisition of Manis amid regulatory issues.

“You were impressed by the Spark model then.”

Meta as a Potential Cloud Provider?

36:55 to 39:56

Speculating on whether Meta could enter the cloud services market.

“Do you think it'll go through in the end?”

Google I.O. Highlights and Reactions

39:56 to 41:22

Reviewing key announcements from Google I.O. and their impact on competition.

“Before you go, you also cover Google, and we had Google I.O.”

Google's Competitive Edge in AI

41:22 to 42:00

How Google's AI advancements could threaten other companies in various markets.

“or yesterday, they announced that they were extending some of their agentic capabilities into lodging, which is more of a risk for companies like Booking Holdings and Expedia.”

Analyzing OpenAI and Google’s Competitive Strategies

42:00 to 42:30

Explore the contrasting approaches of OpenAI and Google in tackling industry challenges.

“But as you point out, I mean, while OpenAI is pursuing that approach of trying to work with these players, Google has an offering that is really targeted at eliminating all of it altogether.”

The Rise and Fall of Parker: A Fintech Story

42:46 to 44:42

Learn about Parker, a fintech startup focused on corporate credit cards for e-commerce businesses.

“Tell us, who was what was, rather, Parker, the fintech company?”

Challenges in the Fintech Lending Model

44:42 to 46:09

Understand the complexities of balancing equity and debt in venture-backed lending.

“And then some of it was debt financing that they used to then lend to their own customers.”

Impact of Meta’s Policy Changes on Parker

46:09 to 49:14

Discover how changes in Meta's advertising policies directly affected Parker’s business model.

“So, uh, they're, they do have to kind of pay a premium for access to this debt.”

Competition and Market Dynamics Post-Bankruptcy

49:14 to 50:59

Examine the competitive landscape following Parker's collapse and industry responses.

“And so the business, I think, you know, according to my reporting, was growing much slower than it had been in the past.”
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Transcript

Automatic transcript. May contain errors.

0:13Welcome everyone to the information's TITV. My name is Akash Pasricha. It is Wednesday, May 20th. Wall Street is looking out for NVIDIA results after the bell today. We're also tracking a critical week for SpaceX as it readies for its Blockbuster IPO. There's also some big media news out today. James Murdoch is buying New York Magazine and Vox Podcasts. The other half of what we know as Vox, which includes websites like The Verge and PopSugar, will become part of a new company run by Ryan Pauly, current president of Vox Media. First up on the show today, Google is hosting its annual IO Developer Conference.

0:54Our Google reporter, Erin Wu, is at the event and joins us in just a second to tell us about what she is learning on the ground. We'll also dig into the SpaceX IPO with three charts that can help us make sense of the scale and story of this moment. The information also published exclusive reporting about how companies are adjusting software vendor contracts to make room for heavy spending in AI. We'll also talk about Meta's planned layoffs and we'll wrap the show with our weekly finance column and the inside story of the bankruptcy at Parker, a fintech company that's gotten a lot of attention recently.

1:32It's going to be a fun show, so let's get right on into it. Google has made a splash with its I.O. event this week, debuting a long list of new features and tools leveraging AI. Our Google reporter Erin Wu has been on the ground. I want to bring her on to talk to us about what she is hearing. Erin, welcome to the show. It's great to have you back. We had the keynote yesterday and a long list of new exciting announcements that Google announced. Walk us through the big ones and what you are paying attention to.

2:05Erin Woo:Yeah, so this is Google. So there's a million different announcements. Some major themes, obviously, agents were big. There's new agents coming in Search. This is really interesting. Search will be able to scan the web for information on things like apartment listings or like sneaker drops was the other example. Also, some personal assistant features coming to the Gemini app, Gemini Spark. And then there's some new shopping announcements as well, a universal cart that lets you take products from different retailers, like put them all in one place, and it'll do some research for you on the back end.

2:38Erin Woo:And then a new video model, which is interesting because Google is really leaning into this one kind of like nobody else is. So let's unpack each of these a little bit more. Video, I think people can kind of get their head around. They've been doing some great things in video and image creation from the start. Search has always been a big question. We've talked to you about it on the show. How are they going to handle Search, Gemini, the balance between the two? What was your reaction to, I mean, they're doing it. Search is now really Gemini, right? Yeah, I mean, I think the announcements yesterday really re-upped that question of like, what is the difference between Search and Gemini?

3:21Erin Woo:And like, why are there two different things? To be honest, like, I do not know. The answer that Google always gives is that, oh, like we're meeting like customers where we're at. I personally do not understand why there are two massive teams that are building two very similar products and then putting them in different places. But that maybe is why I do not run Google. But they are very much coming together. We're seeing more agentic features in search and the ability to do much more complex answers. They're expanding the search box for the first time in 25 years so that it's more multimedia and you can ask longer questions.

3:57Erin Woo:And so there's a lot of convergence between these two things. on the shopping piece what what's what was the uh well i mean let's go broadly what was the reaction on the ground to all of of these features from attendees i mean again there's a lot of different things we like haven't even talked about coding yet um i think there's a the people that i was talking to there's excitement about like the new search agents there is excitement around the universal cart remember like google has had a lot of success in shopping like i know like for me personally like Google Flights, like Google Hotels, like a lot of this comparison booking stuff that like can pull across the internet.

4:34Erin Woo:It's stuff that they're really strong on and like that really like becomes a part of people's lives. I think some of the agent stuff, it feels like this is still a little bit more complicated than anyone actually needs in their personal life. I was talking with someone there who was joking that like every Google exec, it seems like their life is like, and now I must look for events to do on the weekend and like what hikes I'm going to do and like the Italian food I'm going to eat for dinner, which like, great. That frankly seems like a great way to live. But also like a lot of these things, it doesn't necessarily seem like a normal person needs like an agent, like custom coding a schedule for their weekend.

5:11Erin Woo:Like, it seems like that's kind of something that, again, like you can just kind of do. Well, but I mean, look, you might not need it every weekend, but, you know, in the moment that you do, that's what it's there for, right? i'm willing to accept that maybe i am just 26 years old and my life is not that complicated but i did ask friends with kids and they were like no we don't feel like we need this either so okay okay fair um well so what about coding yes so i mean like for me this was one of the big like if you take it less from like a person who uses the internet perspective and more from a tech reporter perspective like this was really like the big question that i had coming in so like the AI framework right now, as we've talked about on the show a million times, is that like Anthropic is really good at coding.

5:58Erin Woo:They have this mythos model that has been like teased and very much hyped, like not quite released, but like Anthropic is really dominating on coding. And so like a big question was whether Google was going to come into this with some big splashy release like they catch up and they're going to blow everyone out of the water. And so they had some coding announcements. They had a demo of Antigravity, their coding agent platform, and they also had not a big new model, but a smaller model, Gemini 3.5 Flash, that they're hoping will be a faster, more workforce option for developers. So they had some coding announcements, but I don't think anything that feels like it's made a big splash thus far.

6:40Erin Woo:And I do think that Anti-Gravity, their big flagship coding release is kind of getting mixed reviews on X immediately. Well, you know, I just want to go back to sort of, I'm thinking about Mark Zuckerberg's goal to prioritize personal superintelligence. And I'm thinking about the consumer-centric products that Google unveiled here. And, you know, there is a question about when meta will get, you know, truly close to that mission of personal superintelligence. I almost feel like yesterday's keynote was like the closest that we've sort of got, putting wearables aside for them. I mean, you know, I get that the wearables is supposed to be the true north of personal superintelligence.

7:27But, you know, insofar as consumer products, I, you know, Google really seems to be far and away ahead of the pack in terms of people who are actually using search. you know they are they they've they've got YouTube and video I mean does it really matter that they don't have coding I guess is my question to you yeah and so I think I like I think that is a very

7:49Erin Woo:fair point um I think that like again the big advantage Google has is that Google is everywhere um illegal monopoly antitrust etc but like Google is like all of these products are you must be a Google reporter. Wow, it's what it says in the current. All of these products are things that people use every day. And so it's like AI in Google Docs, like the document builder you're already using, like AI in Gmail, like AI in search. And so Google has this huge distribution surface. What I would say about coding is one... So there's one side of this, which is that coding makes a lot of money. Anthropic is the fastest growing revenue business in history, and that's because all of these enterprises are willing to pay a lot for AI that can code because software engineers are very expensive.

8:40Erin Woo:The other side of this is around the idea of AGI and AGI takeoff and artificial general intelligence. And so there's a mode of thought, which is that the way to get to superintelligence, not like personal superintelligence, but like the real singularity superintelligence is by building AI that can improve itself. And so Anthropic very firmly believes that the way to get that is via coding. And there's some of that at Google as well. I mean, like Sergey Brin has really focused on this coding push and part of that is trying to get to HCI. Google does take a little bit different approach to this where a lot of it's also around like trying to create a world model and this is where someone like the video multimodal stuff comes in but i mean like that i think is the bigger picture of coding like it's about money and it's also about agi now one thought that i had yesterday that i wondered if you talked about with folks on the ground is the risk to google's margins at all as it as it embeds ai into literally everything we know that the cost of of implementing all this is not negligible Any discussion on the ground or any concern from folks that, and we should say that, look, Google is, you know, it is one of the biggest tech companies that can afford a lot of this, right?

10:03It has tons of free cash flow to go around. But did that come up?

10:08Erin Woo:I don't think, I mean, that's not something that developers think about. Like, that's not something that, like, attendees of the conference, they're like, oh, great, like, now there's all this new AI that I can use. I mean, this is something that's come up, obviously, on earnings calls. It's a big question for the company. And what Google has been saying, and I think thus far this seems to be bearing out, is A, that they're really working to reduce the cost of serving all of this. So Google has operated infrastructure at scale for a really long time. And so they're working very hard to make this stuff cheaper to serve.

10:38Erin Woo:And the other side of it, so the other thing going on today is Google Marketing Live, which is their advertising conference. But what we're seeing is that they're also able to make a lot more money, in part because of AI. where they're able to remember ads and people are searching more. And so I think like, and there's also like the growing Google Cloud business. And so this is increasing Google's costs on the one hand, but it's also increasing the amount of revenue they are able to make. Great. Well, Aaron, I want to thank you for coming on. That is Aaron Wu, our Google reporter, here at The Information.

11:11As we look ahead to the SpaceX IPO, my colleagues Corey Weinberg and Valida Pau have a story out this week with five charts that should help you make sense of this historic IPO. I want to bring on Corey to help us unpack some of the data that he pulled together. Corey, welcome back to the show. Viewers will be pretty familiar with your commentary and your analysis on SpaceX, also your original reporting, but I want to go through these charts that you put together. And there's five of them, but really three, I think, tell the story exceptionally well. And I want to start with this first chart here.

11:46you looked at basically the EBITDA figures for SpaceX compared to other companies. Tell us, what should we be paying attention to here on this chart? Yeah, what I found very striking was the very wide gap between how SpaceX will be describing its profit on an adjusted EBITDA basis versus how it's more traditional accounting profit or loss in net income. So as I think a lot of viewers will know, it's quite common for companies to sort of present adjusted profit metrics to investors. Nothing weird about it. but they aren't usually this different than the actual profit and that's what's stuck out to me the chart just shows like even in other capital intensive businesses where you would take out a key expense and depreciation um spacex's gap is much much wider so a couple questions you know i I know that adjusted EBITDA is often a much nicer figure than net income, as the chart shows here.

13:08When investors look at a company like SpaceX, will they make their own adjustments? And ultimately, does that actually matter to the SpaceX story, given that everyone is sort of clear? This is an Elon Musk company. You can make whatever adjustments you want. It doesn't really take away from the core thesis. Well, what's the point of all this? Why am I even doing this, Akash? That's the right question to be asking. No, look, I didn't put this together with sort of the idea of like, this is going to be the smoking gun or this is going this is like the aha. Like it's not as profitable as it says.

13:44It's a way to visualize and understand like the actual business in contrast with other, you know, other types of businesses. And so, you know, investors are going to be trying to understand like the different levers of the business. Like what's the unit economics of Starlink? And, you know, what's the actual timeline for Starship to get up and away? But I still think like, you know, investors are going to have to like truly digest like the historical figures and understand, you know, sort of like what it can tell us about the future. Okay, so let's move on to a second chart here. Speaking of Starlink, so you collected some data on the number of launches at SpaceX that were affiliated with Starlink and then the non-Starlink launches.

14:35What stood out to you here about this data? What I think people don't appreciate broadly is the fact of how large and how much of a growing percentage it is for SpaceX to use its dominant position as a rocket launch provider for its own internet connectivity business. um uh i think you know it's broadly known spacex uses falcon 9 its its main rocket to bring its satellites into orbit um that sort of help power starlink but it makes up a a about three quarters of the total launches that spacex runs and because of that when you're going to look at spacex's three business segments when the s1 flips it's going to be connectivity which is starlink space which is the rocket launch business and ai which is xai and and twitter um and you'll see the space launch business growing single digits it's growing seven or eight percent uh year over year which you would think why why is that happening for SpaceX like it it dominates the market and it's because the actual the actual launch that's doing for outside customers is a very small percentage of the overall launches that it's doing right and so in other words if you look at that chart is your expectation that that the red bar here in the chart you know as a proportion of total launches, the red bar should remain a majority.

16:18And if, you know, it might actually increase proportionally going forward. Is that our expectation? Yeah, I mean, I think that's like a big hot topic in the space industry broadly, especially as SpaceX starts talking more about using its rockets and satellites to put compute into space, which is what is this kind of launch dominance going to mean for the rest of the industry? um will they have to wait in a long queue to be able to deliver their payloads and their satellites into space will any company will any other company that wants to uh put compute in space need to run through the the toll that is spacex or will spacex just be using its rockets to kind of own the entire stack and do it all themselves like there's gonna be we can't quite the story is not clear today.

17:12But I think in the years to come, there's going to be a huge conversation around SpaceX's market position and how it uses its own rocket launch capabilities for its own purposes versus third-party customers. Okay, so now you talked about the growth of all these segments. And so the third chart I want to bring up here looked at the growth of the XAI segment within in spacex otherwise i guess known as the spacex ai segment here but i mean the the revenue growth here is is pretty meager do we expect this to get better over time or what what are you hearing um well they just sold a bunch of their compute to anthropic and that'll probably be a nice little revenue jolt they bought you know they have agreed to buy cursor and you know we'll expect They'll fold that into the XAI business later this year.

18:08So that'll be a nice jolt. But I think this helps explain why they're sort of seemingly scrambling to make all these pretty extreme, you know, sort of business deals, spending$60 billion on Cursor, renting out a bunch of their compute to Anthropic. It's simply because their models and their kind of key AI division have been a pretty significant laggard compared to the bells of the industry, which are open AI and anthropic. And obviously, there's some caveats with this data. XAI obviously also incorporates Twitter, which has, you know, sort of an established revenue base, which can affect growth as well.

18:51But I think any way you slice it, you know, sort of it shows that last year, the AI business was not at all the kind of huge growth driver that we saw for Anthropic and OpenAI. Do people expect more deals like the Anthropic deal, renting out compute, you know, XAI getting into the NeoCloud business? Again, this is sort of a short-term jump in revenue that could help them make use of all the capacity that they have. Is there a discussion at all amongst folks in the SpaceX orbit that maybe XAI just becomes a NeoCloud company? I think buying cursor sort of makes that less likely. I think they are a real player in the kind of developer AI and broadly enterprise application world, which is a huge market that XAI is going to need to go after.

19:52And they need a ton of compute. So yeah, like is XAI just going to become a neocloud? Like, no, it won't help their valuation. Those businesses are usually valued on the lower multiple. And so, yeah, I think if this cursor deal gets done, you're going to not see a ton of that. Let me ask you one more question on the XAI point here. I wonder when you're talking to people about the SpaceX IPO, how much does XAI actually come up in the conversation, given that the space part of the business is really the thing that is anchoring a lot of this. I mean, so much of the IPO story is about compute and data centers in space and data centers on the ground.

20:37And so the actual model that GROC is developing and the XAI business, like the actual revenue you see coming through there, people are maybe not too focused on that. It's all about the actual access to compute and the actual access to get compute into space. But that's still very, you know, that's very theoretical at this point. Or it's very forward-looking. And so that's what, that is the story you need to believe to buy SpaceX at$1 to$2 trillion. Great. Corey, I want to thank you for coming on. That is Corey Weinberg, our Deputy Bureau Chief of Finance, here at The Information. As the costs of AI show no signs of getting any less severe, my colleague Laura Bratton has new reporting that buyers of enterprise software are starting to adjust those contracts to make room for these ongoing AI investments.

21:30I want to bring her on to share with us what she knows. Laura, welcome back to the show. It's great to have you here. Tell us a little bit about what you mean here in your story. You talk about companies trying to make enterprise software contracts shorter. Unpack that for us a little bit. Yeah, so customers of enterprise software want more flexibility in their contracts. They want to be able to use traditional software, but for shorter terms in the case that they want to eventually rip out those traditional software systems for AI tools, or they want to switch to use different software systems.

22:06And I think this is important because we hear the SaaSpocalypse talked about in really black and white terms. Either software is dead or software is going to be improved a lot by AI and is going to be a big winner in all of this. And I think to me, my conversations with customers and the anecdotes I gathered were really the clearest signal of the near-term pressures that software companies are facing. So let's talk about those pressures. I mean, are we talking specifically here about Anthropic changing its pricing model or what pressures are you talking about? Yeah, so it's really an indirect link where the rise of all these AI tools, and I think we've seen that Anthropik, Claude Code, Claude Enterprise, Claude Cowork, like the Claude Enterprise sort of accounts and suite of tools, are the most popular among enterprises.

22:55And as AI providers and software providers in general begin to charge customers based on usage, we're seeing that enterprise software buyers are becoming a lot more picky about which software systems they use and how they're going to spend their budgets, what return they're seeing from the software that they use. So help me understand this. If they want their contracts with enterprise software companies to be shorter, how does that help with the expenses in the short term? Because in my mind, I sort of understand how I'm not committing to a contract that is maybe five years in length. I'm committing to something that is maybe two or three years.

23:34So I see that part. How does it help me with my cash flow in the short term then? Yeah, I mean, it doesn't necessarily, the part about the shortened contracts doesn't necessarily make it so that you're spending less in the short term, but it does make it easier to halt that spending at a nearer point in the future if you decide that you're not getting the return that you want. So really, it's a threat to the predictability of software firms' revenues rather than the gross value of those revenues at this moment. And then another thing that I heard from consultants is that net retention is under pressure within these software contracts.

24:16And what that really means is that customers that are renewing their contracts aren't growing their spending with their software vendors as much as they used to. And so I think that that's another really clear signal about how customers are being pickier and not necessarily expanding the scope of their contracts as much as they were previously. The contracts are shorter, which means that they could potentially leave their software vendors that they've had for a long time in one or two years, whereas they used to sign three to five-year contracts. And are the software vendors giving them the shorter contracts that they want?

24:53Are they changing the terms at all or increasing the price to make up for it? It really depends. We've seen a broad shift among enterprise software players to shift to charge customers based on how much AI they use. which, you know, for example, ServiceNow said that that could increase the spending by customers a lot or significantly. I can't remember the exact figure. I believe it was around 15 or 20 percent in the coming years. And so I think that as vendors shift their pricing models, they're going to be able to see customers pay more than they were previously for their AI tools. So I think that that can be seen as a response to this industry shift and them trying to get ahead of that.

25:39But from what I've heard, some vendors are agreeing to these shorter contracts just by anecdotally what I'm hearing from consultants and customers. Now, the other – and you hinted to this earlier, you know, this idea that it makes it easier for these enterprise software buyers to maybe taper off their contracts over time. You talked about net retention being something that was coming under pressure at these enterprise software companies. Can you unpack that a little bit more for us? I mean, this is basically the idea that this is the big risk is them not renewing after this shortened contract, right?

26:18Yeah, so net retention doesn't necessarily mean that customers aren't renewing their contracts. It just means that they're not increasing their spending with the provider when they do renew those contracts. So I talked to an executive at EY Parthenon, which is the strategy and M &A arm of Ernst & Young. And she told me that net retention that she's seeing among EY Parthenon's hundreds of clients is down about 15 percentage points in the last six to nine months, which I think is a clear signal that software… That's a lot. Yeah, it's still… That seems like a lot, right? I mean, it's still around 100%.

26:56So, you know, customers are growing their spending to some degree, but it's less than they did previously. And I think that that's an early signal of the pressure that software companies are seeing. Are there specific segments of the software sector that in particular are under pressure here? You know, I'm just thinking about, you know, there's CRM software, there's, I don't know, cybersecurity identity authentication software. There's data storage. Which one is most at risk here? One that I kept hearing come up was enterprise resource planning. Which is like what? Yeah, it stores critical business data and application, ERP applications are offered by like SAP, Oracle, Microsoft, a bunch of companies.

27:51And that's one that I heard come up, but I think it really remains to be seen. And I don't think that chief information officers, CTOs really know which software systems that they're going to want to use in three years. And they don't know which software vendors are going to win this, you know, quote unquote, AI race and which AI tools are going to be better. And that's kind of the point is that we don't know. And that's why they want more flexibility and they want shorter contracts. and in some cases, opt-out provisions, which I found really interesting. And that is basically, they're saying, software vendor, if you do not provide promised AI features by X date, I can exit this contract early.

28:32And that's another thing that came up. So it's not just shorter contracts, it's also some other sort of more favorable terms. And I think really this is just a broad signal that customers have more power in negotiations with their software vendors than they did in the past. All right. Well, Laura, I want to thank you for coming on. That is Laura Broughton, author of our Applied AI newsletter here on TIT. Okay. Meta has begun notifying thousands of employees that they are being laid off. The company is set to cut 8 ,000 jobs today, which amounts to roughly one-tenth of the company's overall headcount.

29:08The company is also restructuring its organization and will move thousands of other workers to new roles. For more analysis, I want to bring on Lloyd Walmsley, Managing Director and Internet Equity Research Analyst at Mizuho. Lloyd, welcome to the show. It's great to have you here. It's great to be here. Thanks for having me. So as best we know, these layoffs are underway today at Meta, and I know we've been expecting these for a long time. Tell me, in your opinion, are these layoffs warranted at the company? look i think we're seeing a shift in how you know these companies develop software and you know with ai they can do a lot more with fewer people so i think that's part of it and then look i think mark has done a good job of establishing uh very tight discipline at the company in in general and as they spend more in um capex and and you know for that matter opex on cloud expense to build out um ai product, AI infrastructure, they are holding the line on margins and operating income.

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30:14And so I think it's wise of him to try to be constantly tightening the belt, given how much they're investing in so many areas. So this whole discussion about how much of these layoffs, and now I'm talking in the layoffs broadly that we've seen at companies like Block, et cetera, there's a question, which ones are the result of overhiring and which ones are the result of actual AI efficiencies? Where do you stand on the split here? Are all these 8 ,000 efficiency true cuts, or is it the result of overhiring? Yeah, I think it's a little bit of both, clearly. But the company, Meta in particular, has been very disciplined ever since coming out of the pandemic and and honestly some of the challenges they saw in the ad business uh both coming out of the pandemic but also post the the you know the idfa uh changes from apple you know they you know really um when the revenue growth slowed down they got religion on margin and cost so they've been pretty tight in terms of um in terms of take reducing head count and being disciplined in growth.

31:32So I think they, more than a lot of companies we follow, they've been ahead of the pack in right sizing. And so this feels somewhat enabled by AI and then somewhat a reaction AI. They just, they need to trim costs in order to fund some of this investment. And so I think it's, it's a little bit, some of it is the AI, some of it is overhiring and some of it is just choosing to invest in other places. Have you done any modeling around the cost savings that Meta will incur with these layoffs and how much of a dent that would make in the tremendous CapEx that they have to budget for? Yeah, so we have done a little bit of analysis here and it will be significant.

32:21I mean, you can make estimates based on the average operating expense per head at the company, and it's significant in the neighborhood of high single-digit to low double-digit billions of dollars annualized is in theory where they could get to. Now, again, it's pretty significant. Now, again, they're spending a lot of money on AI in the form of CapEx, which they've guided to, but also on the operating expense line, they've got significantly expanding cloud relationships to supplement their own data center infrastructure. And that is harder to pin down in terms of how much of this savings just gets reinvested.

33:08I think for now, most of this is going to be reinvested, although I think there's opportunity for them for the costs to ultimately migrate from where they initially guided this year, given these cost savings and given the company's general trend towards discipline and conservative guidance. So all of this is in service of better AI, and yet it feels like we maybe haven't seen the better AI that everyone's hoping for. We've seen a taste of what Meta can come out with. They had that new family of models that they introduced, I believe, a couple weeks or months ago. But what's your assessment of how effective this investment is?

33:59And when are we going to get the good stuff? That is the crux of the question. And I think we've started to see some really positive signs, but it's still really - Like what? Like what? Yeah. So I think for one, I think the big investors initially when they saw the amount of CapEx, I think were disturbed because we had so little visibility into whether or not they could build a good model, whether or not they could catch up to the frontier. And then what are they going to build on top of that? Like, does the world need another chatbot? And I think what the company has addressed so far is, you know, with Muse Spark model, they have, you know, I think established significant credibility in, you know, building a high quality LLM model, you know, at the cusp of the frontier in a very short order, nine months, since they put the MSL team together.

35:00So that is remarkable speed. And they've been very clear that the next set of models will be even more meaningful. So I think they've checked an important box in terms of their model building prowess. But then there's still significant other questions, which is, okay, so what are you going to do with that? And we've gotten hints of that from the earnings call. Clearly, the company is very agentically focused. They're very consumer focused, but there's also a business element to it. They work with a lot of SMBs on the Facebook or meta advertising platform, and they can help those companies across not just their advertising, but more broadly across their businesses.

35:48But I think a lot of this is consumer. You were impressed by the Spark model then. Yeah, I think it is a solid model. And I think the feedback, generally speaking, has been this was better than people expected for V1 coming out of MSL. now you also talked about agentic focus and we know that they bought manis and then i believe the uh the the government in china sort of ordered that they uh that they divest manis i hope i have this or maybe i'm not remembering the details but what what's the current state of the manis acquisition yeah so i think you're right the the chinese government has said this you know this can't go through.

36:34And I think it's a little bit up in the air. There was a great interview recently with Alexander Wang, where he demurred on really commenting specifically. It's possible there's some negotiations going on behind the scenes, you know, between the company and the Chinese government and the US government to try to make it happen. But it's most definitely up in the air at the moment. Do you think it'll go through in the end? I don't have a strong view on it but i think they i think the company can work with manis even if they're forced to divest it and then and then clearly i think one of the most interesting things coming out of the alexander wang interview recently was that the company is saying they're moving out of the sort of rebuild the infrastructure phase to the rapid scale phase uh associated with their ai product development so i think they're going to be able to you know with time recreate a lot of what a lot of the functionality that Manus was doing if they need to.

37:35Let me ask you one last question here, more on the infrastructure note that you were just talking about. I've wondered what the likelihood could be of Meta moving into the business of being a cloud provider. Do you think that that is a short-term, long-term option for them? Is this something they should look into? Yeah, I think it's something that they could do. It's not likely that they'll do this, but what they may end up doing is with the SMBs and AI, they could end up providing a lot of services to SMBs related to AI that look and feel a little bit like a cloud business, but abstracting away some of the infrastructure layer.

38:21So they may end up participating. Like what? Um, like just helping them with a gentic, you know, which they're already doing to some extent, they're, they're providing a gentic tools to businesses that they can use on their own website, not just with regards to activity on, on the meta platform. And so they could provide more help with sort of e-commerce tools for their advertising customers. You know, for now, they're not charging. They could, I'm sure this will help them generate more ad revenue, but they could eventually have subscription packages for businesses that look like similar things that are offered by cloud computing competitors.

39:02Although at the start of your answer, you said maybe it's not likely that meta goes into the, not the SMB business, I'm talking the broader cloud provider business. Why do you think it's not likely? Well, I mean, the existing cloud infrastructure business is pretty crowded and pretty non-core. I think they're likely to try to address things that could help SMBs in a way that predominantly drives their core business, which is advertising. But yeah, I wouldn't be surprised if they do sort of cloud-light type of services to SMBs. but I don't think they're going to enter the broadly defined cloud business to help companies like my bank port their data infrastructure into the cloud.

39:54That doesn't seem likely. Right, right. Before you go, you also cover Google, and we had Google I.O. in the background this week. Any high-level reactions to what you saw them release? Yeah, look, I mean, I think the first reaction would be, We feel better about the core search business. They continue to bring more AI into the product in a way that re-deepens their competitive moat. Secondly, the pace of innovation is clearly accelerating massively. I think that is clear and aided by their advances in coding tools with the new 2.0 version of anti-gravity. third thing you know we we came out of that with a little bit more of an appreciation for why meta is building their own models clearly you know google's you know infiltrating every product they offer with ai and i think increasingly it will be um key to have their own model at meta and then last takeaway would just be some of the competitive fears throughout the internet uh particularly on the marketplace, internet marketplace models, things like online travel agencies, food delivery.

41:12I think we're starting to see those risks start to materialize more in the sense that Google is making their agents more and more capable. And then, you know, they recently, or yesterday, they announced that they were extending some of their agentic capabilities into lodging, which is more of a risk for companies like Booking Holdings and Expedia. So those were the - And it's kind of interesting too, because we know that OpenAI, they, I forget what the, was it called apps or something like that? Anyway, the integrations that OpenAI has been working on with companies like Booking.com, we've had the CEO of Booking.com on the show and I've asked him about the results of that integration.

41:54And I think that was about a month out from when they started it. So it was still too early to tell. But as you point out, I mean, while OpenAI is pursuing that approach of trying to work with these players, Google has an offering that is really targeted at eliminating all of it altogether. And so certainly an interesting dynamic there to watch. Lloyd, I want to thank you for coming on. That is Lloyd Walmsley, Managing Director and Internet Equity Research Analyst at Mizzuto here on TI TV. Earlier this month, a fast-growing fintech company called Parker, which plays in the online credit card space, filed for bankruptcy.

42:36It is a story with many layers to it, and my colleague Anne Guillen got to the bottom of it all in today's finance newsletter. I want to bring her on to talk all about it, and welcome back to the show. Tell us, who was what was, rather, Parker, the fintech company? Well, you hit the nail on the head. Parker was a fintech startup that mainly focused on corporate credit cards for e-commerce businesses. And if that sounds like kind of a niche idea, Parker was one of several companies that took kind of this playbook or idea that was very popular a couple of years ago when fintech was a really hot startup category of trying to lend and provide capital to a very specific niche of businesses.

43:26So in Parker's case, they were focused on e-commerce. And I think this idea in theory makes a lot of sense because typically small e-commerce businesses, they have a lot of upfront costs that they need capital for. So they need to buy inventory. They need to pay for that ahead of time before they can sell it. They also need to pay for ads on Facebook and Instagram and anywhere else they are trying to reach their customers. So there's lots of demand for credit among these kinds of businesses, and they also typically have a harder time accessing traditional financing from banks. A lot of banks require things like a personal guarantee from executives or things that could be kind of a barrier if you're trying to quickly start and scale a business.

44:19So there definitely was a market and demand for businesses for an offering like this. And for a while, like I mentioned, these companies all started when fintech was a hot category for VCs. So investors were on board for a while too. How big did the company get in the end? Parker raised almost$200 million in funding. So some of that was equity from VCs. And then some of it was debt financing that they used to then lend to their own customers. And so we can get into, you know, kind of how you need to balance the two. How you take on debt to then issue some form of debt. It's a tricky model to make it all work.

45:07What was so tricky about why did the company fail in the end? So these VC-backed lenders in particular, they need to balance growing their book of loans. the, you know, the customers that they're lending money to, while also making sure that they're not lending to borrowers that are super risky, that are never going to pay them back, that, you know, are going to use the money to do sketchy stuff. And so at the same time, since they rely on the equity funding that they're getting from VCs to kind of fund the daily operations, keep the lights on, pay for things like employees and software, there's a lot of pressure for them to bring in revenue very quickly in order to cover those fixed costs so that they don't just burn through all their equity.

45:55Um, and then also by kind of growing that base that they're lending to you, they can also usually get cheaper or better terms on the debt financing. But they, you know, they're not banks, so they need to, they're kind of a middleman. So, uh, they're, they do have to kind of pay a premium for access to this debt. So it all kind of, it's a delicate balance. You know, you need to be bringing in revenue, but at the same time, you can't be growing like crazy by bringing on. But one of the interesting parts of the story was, you know, you have this cash management cycle here, bringing in enough revenue to pay down your debt so they can issue the debt.

46:39But then there was this change with Meta. What happened there that really impacted them? Yeah, so I think what we've seen with Parker and some of these other more specialized lenders is that it's already kind of a tricky balance to make this venture-backed model work. But if you're very concentrated in lending to one specific industry like e-com, if there's a big macro change that's affecting the whole industry, then that can very quickly create problems for basically all of your customers. And so what happened with Meta was earlier this year, Meta changed their policies around how lots of advertisers pay for ads on Facebook and Instagram.

47:25And so for a lot of e-commerce companies, that's one of their biggest expenses. And then so, you know, the cards that they're using to pay for the ads, that's a huge source of transaction volume for them. So Meta changing the rules to make it so that most advertisers can't pay with credit cards for ads anymore. They now need to either pay directly from a bank account or use a debit card. That wiped out a lot of transaction volume, not only for Parker, but for any fintech with a lot of e-commerce customers. And Meta basically made this change because, what, advertisers were not making good on the, well, I'm just trying to think about it.

48:13No, not necessarily. They get paid, yeah. So what was the issue there? It's cheaper for Meta to not have to pay credit card processing fees. So that's a couple of percentage points on each transaction. And also that can also kind of speed up how quickly they're able to get that money from the advertisers. So the meta change, I mean, was this the central reason that Parker really hit a wall? Or was it really more of the cash management issues in the broader state of the business? I just want to make that clear. Like I said, I think the meta issue kind of exemplifies what can happen if you are really concentrated in one specific industry with your customer base.

49:01I know Parker was trying to expand beyond e-commerce, but, you know, trying to grow that business while also keeping the credit book really high quality, you know, that's tricky. And so the business, I think, you know, according to my reporting, was growing much slower than it had been in the past. and then going out and either trying to raise more funding from VCs or get acquired, and you have a big growth slowdown, you know, that's a tough thing to explain and not necessarily what investors or potential acquirers want to see. And we should also say, I mean, you know, in the meantime, you have companies like Brex and Ramp.

49:44Sure. You know, these are the online corporate credit card darlings. Brex obviously got acquired. But, I mean, these would be direct competitors to Parker that I imagine, you know, customers sort of look to as a safer alternative potentially. Yeah, I think you see some of the bigger players like Brex and Ramp starting to kind of zero in on e-commerce companies more as potential customers. So that's certainly a factor. But I think you've also seen, you know, some of the startups in this space that have been more successful. they've either anchored around banking or they've been able to sell their customers on other kinds of add-ons, like other software that can help you manage your finances, like a kind of better version of something like QuickBooks.

50:33So I think Parker really just kind of exemplifies how difficult it is to build the business on lending alone. And especially with this kind of VC-backed model, you know, they're certainly not the first startup in this space to have collapsed. So I think it just kind of illustrates how this model can be super, super tricky to make it all work. Last question for you. What's been the reaction from folks in the corporate credit card space to this bankruptcy and also from customers? Yeah. So, I mean, you see this. I wrote about the collapse of another lender, Ampla, which was focused on CPG and food and beverage startups a couple of years ago.

51:18And while that was all happening, anytime, you know, these companies collapse, there are customers that are left out, you know, hung out to dry a little bit. So there are definitely competitors that are trying to win a bunch of new business right now. There's another company that's similar to Parker called Flex. They said they had gotten something like 5 ,000 new business or new customer inquiries following Parker's bankruptcy. But then you also see, like you said, you know, companies like Brex and Ramp trying to move into the space. And even companies like Shopify, which they already have a lot of financial service offerings, but they have been kind of laying the groundwork for potentially some new offerings in that space.

52:05So it's certainly super, super competitive, but it's also very tricky to get right. So definitely we'll be keeping a very close eye on how that all plays out. Great. And I want to thank you for coming on. That is Anne Guillen, our e-commerce reporter here at The Information. 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 eastern if you can't make it then episodes are available on theinformation.com on our youtube channel or wherever you get your podcasts make sure to follow us on social media on x instagram and tiktok i'm already excited for our next show tomorrow have a great rest of your wednesday bye-bye for now

From the publisher

Google Reporter Erin Woo talks with TITV Host Akash Pasricha about Google’s AI convergence between Search and Gemini. We also talk with Deputy Bureau Chief of Finance Cory Weinberg about SpaceX's financials ahead of its blockbuster IPO, AI Reporter Laura Bratton about how enterprise software buyers are altering vendor contracts to fund AI, and Mizuho Managing Director Lloyd Walmsley about Meta’s 8,000 workforce layoffs and its AI margin protections. Lastly, we get into the bankruptcy of e-commerce credit card darling Parker with our e-comm reporter Ann Gehan.


Articles discussed on this episode: 

https://www.theinformation.com/articles/5-charts-make-sense-spacexs-ipo-numbers

https://www.theinformation.com/briefings/google-unveils-new-video-model-search-upgrades

https://www.theinformation.com/newsletters/the-briefing/googles-ai-search-leap-forward

https://www.theinformation.com/briefings/meta-begins-cutting-8-000-jobs

https://www.theinformation.com/newsletters/ai-agenda/google-pitches-ai-coding-tools-cost-effective-option


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Chapters:

00:00 - Introduction

01:13 - Google IO: Search vs. Gemini Continuity

12:56 - SpaceX IPO: Launch Margins & xAI Compute

22:46 - The SaaS Apocalypse: Shorter Tech Contracts

29:57 - Inside Meta's AI Efficiencies & Layoffs

43:29 - E-Commerce Crisis: Why Fintech Parker Failed


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