# Writer's May Habib: Building The Enterprise AI That Anthropic And OpenAI Sell — Then ‘Leave’ Behind Markdown copy of https://realalpha.app/v/wQGIp0KouWY/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy. May Habib argues enterprise AI scales when companies pair capable models with trusted workflows and measurable results. - Show: Upstarts - Hosts: [Alex Konrad](https://realalpha.app/people/alex-konrad/) - Guest: [May Habib](https://realalpha.app/builders/may-habib/) is cofounder and CEO of Writer. - Published: Jun 25, 2026 - Length: 45 min ## The best minutes - [40:15](https://realalpha.app/v/wQGIp0KouWY/?t=2415) [AI buyers should be held accountable for results](https://realalpha.app/s/ai-buyers-should-be-held-accountable-for-results/) (4 min) - [35:09](https://realalpha.app/v/wQGIp0KouWY/?t=2109) [Writer's moat grows as enterprise AI gets more capable](https://realalpha.app/s/writers-moat-grows-as-enterprise-ai-gets-more-capable/) (5 min) - [22:06](https://realalpha.app/v/wQGIp0KouWY/?t=1326) [May Habib describes bias in her VC fundraising](https://realalpha.app/s/may-habib-describes-bias-in-her-vc-fundraising/) (5 min) ## Also worth watching - [30:20](https://realalpha.app/v/wQGIp0KouWY/?t=1820) [Writer kept training models because enterprise adoption lags](https://realalpha.app/s/writer-kept-training-models-because-enterprise-adoption-lags/) (3 min) - [18:11](https://realalpha.app/v/wQGIp0KouWY/?t=1091) [Writer uses review policies to scale personal outreach](https://realalpha.app/s/writer-uses-review-policies-to-scale-personal-outreach/) (3 min) - [9:16](https://realalpha.app/v/wQGIp0KouWY/?t=556) [Internal politics determine how far enterprise AI projects go](https://realalpha.app/s/internal-politics-determine-how-far-enterprise-ai-projects/) (3 min) - [11:49](https://realalpha.app/v/wQGIp0KouWY/?t=709) [Writer says workflow scaffolding cuts token use by 30–50%](https://realalpha.app/s/writer-says-workflow-scaffolding-cuts-token-use-by-30-50/) (3 min) - [13:59](https://realalpha.app/v/wQGIp0KouWY/?t=839) [A pharma briefing can link Outlook, CRM and spreadsheets](https://realalpha.app/s/a-pharma-briefing-can-link-outlook-crm-and-spreadsheets/) (3 min) Skip the opening setup and sponsor reads, the Cordoba backstory, and the closing exchange on hiring and retention. ## Summary May Habib is cofounder and CEO of Writer, an enterprise AI company valued at $1.9 billion, according to the YouTube description. She previously built Qordoba, a machine-translation company, before pivoting it toward Writer in 2020. Habib says Writer builds AI agents for nontechnical business users, with brand and compliance controls and workflows that connect to companies’ systems. She argues that reaching production is not the same as scaling: companies need organizational change, employee adoption and measurable returns. Habib says Writer’s customer feedback loop and preference controls distinguish it from general-purpose AI labs, even as those models improve. She urges executives to hold AI spending accountable to results and says enterprise trust in autonomous agents has yet to catch up with coding. ### Minute by minute - [1:30](https://realalpha.app/v/wQGIp0KouWY/?t=90) **Writer targets nontechnical business users.** Habib describes Writer as an enterprise agent platform designed for business users who can think systematically but may not be technical. She says its built-in brand and compliance controls support shared workflows, and that the company can demonstrate agentic capabilities in 30 or 60 days; scaling the resulting value takes longer because it involves changing roles and organizational design. - [6:29](https://realalpha.app/v/wQGIp0KouWY/?t=389) **Qordoba's language work led to Writer.** Habib traces Writer to Qordoba, a machine-translation company, saying she and cofounder Waseem had worked on language, NLP and machine learning before the current wave of LLMs. She says their vision progressed from AI-assisted writing to AI writing, while early transformer models handled tasks such as correcting language and writing haiku. - [9:35](https://realalpha.app/v/wQGIp0KouWY/?t=575) **Enterprise adoption depends on politics.** Habib says executive reactions to AI depend partly on internal politics: sunk costs in home-built tools can slow decisions, while collaborative teams can set more ambitious plans. She describes customer councils as a way to share lessons and says Writer’s scaffolding and shared workflows use 30, 40 or 50% fewer tokens. - [14:10](https://realalpha.app/v/wQGIp0KouWY/?t=850) **Writer differentiates through workflows.** Habib describes three market phases: resistance to AI writing before ChatGPT, pressure to adopt after its launch, and a later challenge as agentic products began to sound alike. She says Writer’s differentiation is the work underneath the chat interface, such as centrally building consistent, auditable briefings that connect to different systems. - [16:55](https://realalpha.app/v/wQGIp0KouWY/?t=1015) **Brand controls make AI usable.** Habib says brand voice, style and compliance controls helped Writer win in industries such as consumer goods, pharma and finance, where generic AI-generated messages could erode trust. She says administrators can require email review and prohibit automated one-to-one messages; in her own example, an agent drafted emails for 14 or 15 meeting attendees, and she reviewed them before sending. - [21:16](https://realalpha.app/v/wQGIp0KouWY/?t=1276) **Habib recounts the pivot and VC bias.** Habib says the shift from Qordoba to Writer was a recap and restructuring that effectively restarted the business, while she and Waseem kept the legal entity because their visas were tied to it. She recalls Vinod Khosla falling asleep in a meeting and a Sequoia rejection calling it inspiring that she pitched with two small children. Habib says women founders can face added skepticism about how hard they will work. - [27:29](https://realalpha.app/v/wQGIp0KouWY/?t=1649) **Habib prioritizes ROI over hype.** Habib says the key was to stay in the game and focus on customer outcomes, even when ROI is less exciting to discuss than AI adoption. She says customers use Writer to reduce costs such as agency, Salesforce and Adobe bills, and estimates that 10 to 15% of sales and marketing teams may eventually have AI-related titles. - [30:31](https://realalpha.app/v/wQGIp0KouWY/?t=1831) **Writer keeps training its own models.** Habib says Writer started training models because third-party options were not available when it began in 2020, and kept doing so because it did not see the labs’ capital advantage as necessarily creating a capability gap. She says Palmyra powers 90%+ of Writer’s LLM calls, while customers can also connect outside or in-house models. Writer is not a lab, she says, because research, product and go-to-market teams work closely with customers. - [33:35](https://realalpha.app/v/wQGIp0KouWY/?t=2015) **Customer adoption is part of Writer's moat.** Habib says Writer’s moat is its ability to keep pace with model capabilities while bringing customers along. She argues that better models increase enterprises’ need for a preference layer covering brand, compliance and workflows, which Writer can productize across customers and teams. - [37:38](https://realalpha.app/v/wQGIp0KouWY/?t=2258) **Habib rejects services-led deployment.** Habib says enterprise customers want to build internal capability, not fill their offices with consultants, and argues that product teams can use customer feedback to improve implementation. She says Writer helps people onboard conversationally and gives teams shared account context, including agent activity that may not appear in the CRM. - [40:15](https://realalpha.app/v/wQGIp0KouWY/?t=2415) **Habib calls for AI spend accountability.** Habib says companies should hold people accountable for AI purchases without results, citing $3 million in overage over two weeks for an Excel plug-in and calling its ROI zero. She says enterprise adoption depends on auditable workflows with human oversight and trust, which have not yet reached the level seen in coding. Habib says the larger opportunity is still ahead and retaining top talent is a challenge. ## Transcript Upstarts, hosted by Alex Konrad, with May Habib. Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there. [0:12](https://realalpha.app/v/wQGIp0KouWY/?t=12) No one wants to talk about ROI, right? All the cool boys aren't talking about ROI. Why is me talking about ROI? Customer cares about ROI, right? Are they paying for software that does something? There are lots of cutting-edge AI tools helping engineers write faster code. But at the world's biggest companies, other roles from marketing to sales and even IT can benefit from on-brand AI output that doesn't break the bank. Writer is a startup unicorn that trained its own large language models and spent a decade on software to make that non-technical work flow faster. Our guest today is Ryder's co-founder and CEO, May Habib. [0:47](https://realalpha.app/v/wQGIp0KouWY/?t=47) May pivoted her startup Qordoba in 2020 to leverage that new wave of AI tools. She now works with some of the world's largest businesses from Accenture to Hilton. It is really fun to be a builder in the enterprise right now because I don't think anyone has had this level of intimacy with the customer ever. Today on the podcast, we're going to talk about token maxing and solving for corporate AI sticker shock, what companies need to get value out of LLMs today, and the challenge of running a woman-led startup in AI's male-centric Wild West. I'm Alex Konrad, founder and editor of Upstarts Media, and this is the Upstarts Podcast, our weekly show where we talk to emerging startup founders who are punching above their weight to take on the status quo. May, welcome to the podcast. Thanks for having me, Alex. [1:33](https://realalpha.app/v/wQGIp0KouWY/?t=93) This episode is brought to you by Rippling AI, the only AI built to give you full visibility into your startup and the ability to take action across every department. So Mae, I know what Ryder is, but for anyone who isn't familiar, give me the sort of elevator version of what makes Ryder exciting. Yeah, we are an agentic platform for the enterprise. And yes, the models are so infinitely capable today, but enterprises need built-in brand, built-in compliance. They need to scale workflows and share workflows, and Writer makes that possible. And so Writer is not necessarily intended for the engineers that we hear about using a lot of tokens to code new apps or anything, but maybe more other roles within a company. Is that right? [2:17](https://realalpha.app/v/wQGIp0KouWY/?t=137) It is primarily for business users. And so our big North Star from a product perspective is a normal person needs to be able to use this. And so if they're building an app and need a database or are doing a session and have shared deliverables, we're taking care of all of the infrastructure behind the scenes for them. In reality, you get the emergence of a builder class within it. team that is adopting AI. And so the kind of persona behind the business persona is a power user, but that is a non-technical person. It's a non-technical person who can think in systematic ways. And we really adopt that to kind of build the workflows that everybody else benefits from. [2:59](https://realalpha.app/v/wQGIp0KouWY/?t=179) Got it. Now, you get to work with some of the largest companies in the world, like a Clorox or Marriott. When these companies are coming to Rider for help, is there a business problem or a productivity gap that they are often trying to address? So, so much of what the inbound is about is, hey, I hear my peers are using you. Like, how do you actually fit into my landscape? All right. And the reality is when you serve the Global 2000, they're already using all your competitors. And that actually is excellent for us because they have now understood what they can or cannot get done with a co-pilot, a co-work, a chat, et cetera. [3:38](https://realalpha.app/v/wQGIp0KouWY/?t=218) And so when we come in, we get to give them a proactive point of view on what the future of the front office could look like. So if it is wealth and asset management, that's a viewpoint. If it is pharma, that is a viewpoint. But essentially what it comes down to is sales and marketing working as one team. And so much of the shared workflows that we build for customers are about identifying those core go-to-market processes for them. It means a radical rethinking of their org design. And that really is honestly the biggest blocker to scale. We can get in and within 30 days, 60 days, show incredible agentic capabilities that is running on their workflows, connected to their systems, that the power users are very excited about. [4:25](https://realalpha.app/v/wQGIp0KouWY/?t=265) But production and scale, we have learned, are two very different milestones in a company. And that initial production-grade workflow gets everybody excited. The number of times our stuff has been presented to a board, like hundreds of times. But then how long it takes for you to actually get the value, right? The 80 mil of savings because you've turned off all these agencies or the 100 mil of savings because you have rewired an organization. That takes time because it's about people's jobs and livelihoods and roles and responsibilities and leadership paths. And all of that is, unlike the coding market, painstakingly slow in the enterprise. [5:05](https://realalpha.app/v/wQGIp0KouWY/?t=305) You just packed in a lot, but I think there were two pieces there that immediately popped for me. One was this idea. that customers have kind of tried everything. And I'm curious, what is the driver there? Is it experimentation that they just have FOMO and they're like, hey, we should be using these tools, but we're not sure which one? Or then to the point of the cost savings you mentioned sort of at the end of your answer, are they feeling pressure to save money or to find efficiencies in some specific way? Pressure is an understatement. If you are a Fortune 500 executive, like bold-faced names Alex are meeting on the weekend about AI. [5:42](https://realalpha.app/v/wQGIp0KouWY/?t=342) Pressure is an understatement. They feel an incredible amount of stress actually trying to get the rewiring of their organization done, of getting agentic and AI use cases that are worth telling the street about, right? And that really is the North Star for a lot of these folks is, have I actually been able to get value? And from the meetings I had this morning that I told you about to literally just about every executive conversation, it's, you know, we've got adoption. I forced people to use this stuff, but I have no results to show for it. That's a huge gap that we step into because despite, you know, the trillions of dollars of value that has been created, right, you've got anthropic and OpenAI salespeople who walk in like heroes, get a contract and leave to literally never be seen again. [6:30](https://realalpha.app/v/wQGIp0KouWY/?t=390) And it leaves so much to be done in these companies for startups like us. We first met because you had made the Cloud 100 Rising Stars list. And I co-created the Cloud 100 franchise for Forbes a decade ago. And so you were working on a company called Qordoba. Yes, machine translation. Yeah, using machine learning and sort of the pre-LLM AI tools that were exciting a decade ago. What was the through line of sort of the idea and the mission of Qordoba with those customers through to sort of what you're doing now with Rider? We've been working at the intersection of NLP, language, machine learning, the enterprise for, you know, 12, 13 years now, Waseem and I. [7:13](https://realalpha.app/v/wQGIp0KouWY/?t=433) And, you know, through Qordoba is how we started to build transformers. Now, you know, those first transformers were writing haiku and correcting language. That was really kind of their highest use. And so for us it was, well, there's probably a very big business to be built correcting all of the English for brand compliance and ease of translation and the translation market itself. And so when we started Rider, you know, our vision statement was we're going to go from AI. assisted writing to AI writing to who knows what's beyond. And I think it's the who knows what's beyond that has really surprised us, just, you know, how far we've all been able to get with the brute scaling of these models. [7:54](https://realalpha.app/v/wQGIp0KouWY/?t=474) And so, you know, I think we're very good at the enterprise because we have been doing it across two companies. And, you know, the core of our company are people who have been working together for a very long time. So it has been very fun to feel like, you know, I've been doing, in a lot of ways, working on the same mission for such a long period of time, because you do start to feel that mastery. I think the thing that has not changed is, you know, working late into the night and simply not being able to use software without filing Dura ticket reports and product design requests, right? Like I cannot use the product if I have not also figured out all the ways to correct it. [8:32](https://realalpha.app/v/wQGIp0KouWY/?t=512) So something's never changed in the development side. From the capability side, though, you know, there was this wave of companies like Qordoba. Grammarly starts around this time. There are a bunch of these sort of pre-LLM tools. What do you think you guys were able to get the most right or deliver the most? And where did the technology not just be ready yet, you know, so that LLMs maybe really changed the game? Like if we think about sort of that was 1.0, maybe now you're working on some version of 2.0. Well, I think it's 4.0. I think, you know, writer versus Grammarly in that first year, we'd always been marketing the fact that Grammarly is rules-based. We're this, like, new thing-based, right? Now, LLM wasn't there, but Transformer was there. And we described it as encoder-decoders for folks who really got under the hood. [9:20](https://realalpha.app/v/wQGIp0KouWY/?t=560) We've always sold to people who just wanted the thing to work, right? Even today, Palmyra powers 90% plus of our LLM calls, our own frontier models. What is the temperature in the room with these big companies that you're meeting with? Are they feeling coming from a place of negativity that they haven't realized the results that they want and you're kind of cheering them up? Are they still excited? Give us that heat check right off the top. It's such a good question because I think it's also what helps really distinguish our team as folks who will partner with these executives to get results versus folks who are speaking at them or trying to sell them something. And the answer depends on the level of politics. Like, We have been in situations where a CIO, a CMO, and a CEO are literally trying to like split the baby, right, on strategy or the sunk costs fallacy of I've already spent 20, 30, 40. [10:12](https://realalpha.app/v/wQGIp0KouWY/?t=612) 40 mil on some internal company GPT that I feel so much allegiance to and everything I buy needs [10:21](https://realalpha.app/v/wQGIp0KouWY/?t=621) **May Habib:** to fit into that. Well, it's not working. And so much of the home-built stuff is accumulating tech debt as soon as it is launched. And folks who are really struggling with the politics of that [10:33](https://realalpha.app/v/wQGIp0KouWY/?t=633) haven't built the kind of trust that says, look, we need to move on to the next thing and get people to move along with us. So much of the temperature really depends on, you know, is this a political organization? Has politics entered the chat, so to speak? Or is it a very collaborative organization where the executives have all worked together for a long time, they've made mistakes together, but are working in a highly iterative experimental way to do things? And depending on that, our ambition level scales with that. And so, with some of our most ambitious organizations and Edward Jones, a Vanguard, a Northwestern Mutual, we can dream along with them. And, you know, the number of times executives or folks in the middle of the organization at those companies have said, oh, my God, like, we were going to go to level two of our plan. Thanks to you guys, we get to go to level 10 of our plan. And so, you really co-create together when there's incredible organizational health, I would say. When it's more political, it's just you get in a corner with somebody and you help make their patch as bright and beautiful as possible and hope for the best. Got it. And that's more the saving their mood, keeping them from despairing [11:51](https://realalpha.app/v/wQGIp0KouWY/?t=711) about the future. Yeah. And it's not just us. I mean, we've got a real set of executive programs that pairs everybody together. We have a CIO council, we have a CISO council, we have a CMO council, and we're starting ones by industry as well because people need to learn from everybody else. We just had an advisory board meeting where tokenomics came up and we have very efficient token economics in our business. You're not setting out a new set of plates every time someone comes over for dinner with Ryder. So not only are the underlying models much more efficient, [12:21](https://realalpha.app/v/wQGIp0KouWY/?t=741) **May Habib:** but the way that we scaffold and set preferences means that you're using 30, 40, 50% fewer tokens each time. [12:29](https://realalpha.app/v/wQGIp0KouWY/?t=749) And because we're built for shared and scaled work, all those workflows get set before, right? And yes, you can, you know, augment them, et cetera, but also you're not overusing tokens as a result of model needing. to rethink how to do something. And so everybody had a lot of questions about that. And we said, all right, what we're going to do is Ryder's own CFO is going to interview each of you anonymously. I mean, you know, that's obviously not an anonymous conversation, but we will aggregate the learnings. And at our September meeting, we're going to share out everything we've learned about what everyone is doing on the FinOps side with regards to AI. [13:02](https://realalpha.app/v/wQGIp0KouWY/?t=782) And so it is really fun to be a builder in the enterprise right now because I don't think anyone has had this level of intimacy with the customer ever, like not Palantir or not Salesforce and the customer themselves. I mean, the first time I was called a vendor, I sort of like almost teared up and cried because I was like, vendor, what? But you really work beyond that so quickly because this is, it is existential for folks where they're putting their chips on AI and, you know, where their secret weapon and, you so secret in many pockets, but it's incredible to have that level of co-creation. It's like having design partners across every business, right? Across every customer. Now, not every pocket, right? But you find who are the power users, the innovators, the executives who really are ambitious, right? And can think big about what the technology can do. And you become the tip of the spear for the account together. I don't think anyone's ever built software that way. The labs certainly don't build software that way. [14:07](https://realalpha.app/v/wQGIp0KouWY/?t=847) So it's very exciting for us to get to do it. When you guys were sort of first going out into the market a few years ago, did the product kind of speak for itself and people were able to sort of plug and play a bit? Or did you have to be going in there and almost acting like a forward deployed engineer showing people how to get the value from Ryder? Yeah, I would say like three kind of big phases, right? For us, pre-GPT, pre-chat GPT, where the advantage was we were very unique, right? The disadvantage was, and I remember I'll never forget, it was like I, over my dead body, will AI writing come into this organization. [14:44](https://realalpha.app/v/wQGIp0KouWY/?t=884) And I was like, fuck, like, are we seriously building the wrong thing if the people that this is meant for, like, hate it, right? And in a lot of ways, that instinct was right in that the people who took to our first generation of, like, content generation, et cetera, were the non-experts, were the non-craftspeople, right? Then ChatGPT happened where the risk for bringing AI into the organization went negative, right? Like you were crazy if you didn't try to do it, right? And that was like incredible. and bound, right, as a result, because our built-in brand and compliance really, really resonated with people. [15:19](https://realalpha.app/v/wQGIp0KouWY/?t=919) I would say in the agentic era, and as we went horizontal and everyone went horizontal, differentiation absolutely was a challenge because everyone was using the same words. I remember a prospect asked one of our reps, could you redo your sales materials to not use any of the words that Copilot uses? And we were like, fuck. Okay, well, a writer could help with that, but also how interesting. And this is where I think our capacity for customer empathy comes in, where we understand, right, the box of, hey, Alex, how can I help you today? It all looks the same everywhere. It's the new hamburger menu, right? [15:58](https://realalpha.app/v/wQGIp0KouWY/?t=958) And I think what we tried to tell customers was the differentiation is everything under the hood, right? Everything that you can use to build shared and scaled workflows. And so, yes, it was us also getting better at showing off the deliverables and working backwards, right? [16:13](https://realalpha.app/v/wQGIp0KouWY/?t=973) **May Habib:** If I am building a, you know, Monday morning briefing for my pharma salespeople, they better all look the same. They better be all audited the same, right? [16:23](https://realalpha.app/v/wQGIp0KouWY/?t=983) Which means I need to build a workflow for 4,000 people that plugs into Outlook, that plugs into the CRM, that for the regions that don't have a CRM, plugs into their spreadsheet. And being able to do that centrally are interfaces that are not the, hey, how can I help you, right? And so we got much better at telling that story, but this is why at the beginning, like the customer that's tried everything also understands, right, like even the enterprise companies, right, a Microsoft or enterprise-styled anthropic have not built that functionality. It's not even on their roadmap. They don't even know it's a problem, right, which is the problem. [16:58](https://realalpha.app/v/wQGIp0KouWY/?t=1018) Was there a use case or a skill that you guys were really good at early on that was sort of the killer door opener with some of these really big companies? Yeah, I mean, especially in CPG, pharma, FINS. If you sell REITs or if you sell financial products, right, or financial advice, you simply cannot email somebody with LLM voice. Your client knows you. They'll be like, Alex, get out of my inbox. What's the shit you're sending me? I don't care. I don't trust it, right? And so from literally the very beginning, our ability to build in brand, voice, style, compliance has meant the world to these customers because it means I can plug into Alex's inbox. [17:42](https://realalpha.app/v/wQGIp0KouWY/?t=1062) And now I know when he's on the road, it's like tons of typos. It's two spaces after a period. Well, no, you're a crimson guy, so I know it's not two spaces after a period. But you know what I mean. It's you, right? And that has always been a huge calling card for us because customers want to scale AI, but they got to do it while scaling brand, while scaling authenticity, while reducing brand risk. Like, nobody is going to take the trade of productivity, right, versus brand dilution or risk. And in the enterprise, especially in the regulated industries that we serve, writer is for the stuff you have to get right, that you cannot afford to get wrong. [18:20](https://realalpha.app/v/wQGIp0KouWY/?t=1100) And that's always been a huge differentiator. How do you feel about preserving care, connection, respect when people might be using that tool to work faster or to reply at volume? Because I think there's a key distinction between transactional emails or messages and more relationship-driven ones. So how do you balance it? Well, we have policies in Writer, right? And this is, you know, the feature set that you build when you actually talk to customers versus talk at customers. And those policies help an admin. It doesn't have to be an IT admin. Sales ops or sales enablement or marketing ops say, here are the ways in which I want my people using these connectors, right? [19:03](https://realalpha.app/v/wQGIp0KouWY/?t=1143) And so you can say, you have to check an email before it sends out, before it gets out. You're not allowed to build automated email flows for one-to-one messaging, right? I'll give you an example from my workflow. So that same advisory board meeting that I told you about, I hope everybody is listening. And you will now know where this email came from. But I don't mind because I do think this is where the world is going. I asked Ryder, and this is just talking to Slack. I talk to my phone now just about more than I talk to anybody else, everybody else combined. And I said, writer, this is an agent, a writer agent inside of Slack. [19:37](https://realalpha.app/v/wQGIp0KouWY/?t=1177) The meeting we had two days ago, the attendees are all in. I, you know, broadly named the channel. First go get the attendee names, then go to Gong, draft an email for all those 14, 15 people that were in the meeting, try to remark on something they brought to the conversation in my email, and then invite them to the Enterprise Brain beta. And, you know, we had both writer channels, which is basically our, like, enterprise open claw, the proactive agent, as well as enterprise brain we had gone through. And then we had had the FinOps conversation as well. So, you know, if they wanted to be in the FinOps conversation, just remark on that. [20:10](https://realalpha.app/v/wQGIp0KouWY/?t=1210) And it was, you know. 60-second voice note, and then that was on my way somewhere. And then on my way back, got to look through all of the drafts. And the ones that were perfect, so I think like 11, 12 were perfect, send, send, send, send, send, send, right? [20:25](https://realalpha.app/v/wQGIp0KouWY/?t=1225) **May Habib:** I'm literally already responding to the responses faster than me even drafting a single email. [20:31](https://realalpha.app/v/wQGIp0KouWY/?t=1231) Now, writer knows my voice, right? It knows our company's style. It knows writer is written in all caps. And because of the custom instructions and the policies that we've set, it knows what not to reference in the other calls, right? Like other people may have said in those calls. And so I have a lot of trust, right? Plus, I've got an audit trail to understand, like, if Ryder, and this wouldn't happen because I have the policy, but let's say I didn't have the policy on and it did send something to Alex that I didn't want to get sent, right? Do I have a audit trail of it sending, right, that IT can look at, that I can look at? [21:05](https://realalpha.app/v/wQGIp0KouWY/?t=1265) And so these are all things, these are all features that are required to actually trust AI at scale in this kind of like high-end relationship management that we build agents for that customers love. And it works out of the box. And the thing that they'd spent two years building doesn't even come close to it. What was a moment that you were glad you fought through and executed on that you would not want to do all over again? Yeah. A lot of amazing moments. I would love to relive. The thing I would never want to relive is really the pivot from Qordoba to Ryder because it was not nearly as well understood as it is now what this technology could do. [21:44](https://realalpha.app/v/wQGIp0KouWY/?t=1304) And if you could have been in those rooms where we were trying to explain encoder decoders to people and why they would be so massive, you know, we would all be pretty amused. Was it really just a clear pivot or was it more of a— Yeah, it was a recap restructuring. I mean, we would have started a brand new cap table, but both mine and Waseem's visas were tied to the old cap table. So, you know, it was basically a complete restart except for the legal entity. But then the mission and the product, it does feel like there are traces, like there is a through line from Qordoba through Rider. Absolutely, yeah. [22:19](https://realalpha.app/v/wQGIp0KouWY/?t=1339) May, there has been another discourse in the last few days on social media of sort of what it's like to raise money from VCs who may or may not fall asleep in the meetings, who may say, I want you to fire your co-founder. Was raising straightforward for you or were there any sort of scar moments that come to mind as you saw these other war stories? Vinod also fell asleep in my partner meeting at Khosla. But, you know, we had great conversations up until then. Did he offer a term sheet? We verbalized a valuation that we wouldn't accept. So it was never put to paper. But I do think, though, in retrospect, after RC, I wish me and Wasim had traded roles. [23:06](https://realalpha.app/v/wQGIp0KouWY/?t=1386) If you're a woman pitching VCs, you are, we're all fooling ourselves to think that in the back of their minds, they don't think you'll work as hard. I think me and Wasim should have switched roles. Is that crazy? To specifically, basically. Have the technical man pitch. Isn't that cynical? Aren't you glad you didn't do that? Because that would be, in a way, that'd be disappointing to just sort of pretend you're someone you're not. I only care about the outcome. I mean, we're partners. Do you think Wasim would have been happy to lead those convos? Well, I guess, you know, we will find out when he hears this. [23:42](https://realalpha.app/v/wQGIp0KouWY/?t=1422) Well, it's interesting. You know, Mae, you've been doing this a long time. You're really a pro, I believe, at least. Do you feel like you continue to be underestimated or you do have to prove even more than a generic CEO of your stage because you are a mom and a woman CEO? Oh, absolutely. [24:00](https://realalpha.app/v/wQGIp0KouWY/?t=1440) **May Habib:** In the series A, the Sequoia rejection included a line about how inspiring it was that I had two little kids at home while I was pitching them. [24:11](https://realalpha.app/v/wQGIp0KouWY/?t=1451) And that was like inspiring derogatory? I mean, I think so, right? That's disappointing to hear. I mean, it's sort of like everybody wants to hear you say there is nothing more important to you than being a billionaire. And the reality is, oh, my kids are kind of more important than that. I think anyone would say their kids are more important than that. But if you only are writing two or three checks a year, like, who are you going to back? Seriously, Alex, who will you back? Person with kids or the person who's going to live at the office? I would hope that I would back the killer regardless of the circumstance. [24:45](https://realalpha.app/v/wQGIp0KouWY/?t=1485) And I would hope that also having a family is not innately anti-capitalistic, but. So I've been doing this for a long time. I've had investors the whole way. I have never done anything social or personal with a male VC ever. I've been, like, at the homes of our women VCs. I've been on their boats, et cetera. But, like, it goes to show it's not—it's human, right? You want to do business with people who— you can bring into your life. And I actually think it is much, much harder, for better or for worse, and worse, certainly worse, that, you know, men VCs feel much more uncomfortable bringing a woman founder into their life. [25:27](https://realalpha.app/v/wQGIp0KouWY/?t=1527) Like, this is a decade-long relationship, and I think most men are more comfortable doing it with other men. We've had a number of awesome women CEOs on the show already. Do you think that this could change, or do you think your success might make it easier, you know for the next may to to face fewer uphill battles there yeah i hope so i hope so i mean you know i work insane hours um i don't know anyone in ai who doesn't but i've always naturally worked 15 16 hours a day like before startups and i think like you know my instinct when a vc asks about my kids right or if i have kids is to be like yeah but my in-laws take care of them right like yeah I have kids, but, like, I'm not that good of a mom. [26:11](https://realalpha.app/v/wQGIp0KouWY/?t=1571) Like, that's basically, right, what the posture is. And, yes, I do work 80, 90 hours a week every week. But that just, it's sad that that's the instinct, right? And at the same time, I know that if I weren't working that hard, if our whole team weren't working that hard, it would have been much harder to get to, you know, where we are today. And I think, you know, I hope there will be a massive future ahead of us. We're just getting started, right? This is not anywhere close to what we want our terminal valuation to be. But yeah, I do think it is much harder to do it as a woman. No, no, no question. [26:44](https://realalpha.app/v/wQGIp0KouWY/?t=1604) These days, you can chat with AI about almost any business problem. Rippling AI is built to actually solve them. That's because Rippling AI is built on your live workforce data that gives you full visibility into your startup and the ability to take action across every department. Say you're planning your next few hires. Just ask Rippling AI, what would it cost to add two more engineers this quarter? and you'll instantly see a breakdown of comp ranges by level and location. So you can make the smartest hiring decision based on where your team has gaps and where the talent is. But it doesn't stop there. [27:16](https://realalpha.app/v/wQGIp0KouWY/?t=1636) Rippling AI can draft the job wrecks, route them for approval and kick off the hiring workflow. All you have to do is tap confirm and then get back to building. Don't settle for AI that's all talk. Head to rippling.ai slash upstarts and get AI that turns insights into action. that's r-i-p-p-l-i-n-g dot a-i slash upstarts sign up for exclusive access today it sounds like you feel pretty good about where things are right now, when you think about sort of the most important decision that you guys strategically made to get to this point where maybe you do feel very proud of the product, what comes to mind first? Survive, don't sell, don't quit. This is a hard space. And I think it rewards those teams that are physiologically set up to do hard things for a long period of time. [28:14](https://realalpha.app/v/wQGIp0KouWY/?t=1694) It's not one decision other than stay in the game. The hype will pass, and that competitor that, like, gets all the headlines, they haven't built the right thing for the right people and truly understand the customer, like, may have their moment in the sun, but will not survive. And for us, the maniacal focus on customer outcomes, customer ROI, I know it's lame. No one wants to talk about ROI, right? All the cool boys aren't talking about ROI. Wives may talk about ROI. Customer care is about ROI, right? Are they paying for software that does something? And there isn't a CIO I talk to, CMO I talk to, who doesn't want leverage over their cost structure. [28:53](https://realalpha.app/v/wQGIp0KouWY/?t=1733) I know I'm a weapon for them, right? We know that we are being, like, used. I'm happy to be used, right? What are they using us for? Reduce their workday bill, Salesforce bill, Adobe bill. agency build, you are lucky. And we know we're lucky to find somebody who wants to use us for that. Adobe's a customer, Workday's a customer, Salesforce is a customer. And so, you know, internally as well, right, everybody is trying to understand, right, how to get this kind of leverage and get the form factors right. And when we look at, let's take our champions program. So we've got hundreds of people in the champions program. These are folks who, depending on the customer, right, usually are reaching 500 mil to a bill a month of tokens, business people, right? [29:38](https://realalpha.app/v/wQGIp0KouWY/?t=1778) Now, you can be invited to the Champions Program if you're doing really important things. It doesn't have to just be about token maxing, et cetera. We're not about like, you know, the vanity of the token. But most of those people have AI in their title now. They have invented new roles for themselves. And I think, I agree with Aaron. Aaron Levy wrote about this recently. I don't know if you gave a percentage, but I personally think 10 to 15 percent of most sales and marketing teams are going to be AI-related titles. And us being able to bring that kind of aggregated data to an agency, executive team who has two people in the business dedicated to AI, right, is what allows them to say, oh, we need to 10x the human investment here, not just the software investment. And so, yes, you're giving people leverage over this cost structure, but you're also helping them take that into retraining and a lot of cases rehiring, right, for the kind of capabilities and skill sets they want in the company. Tell us a little bit about Palmyra since you mentioned it. You guys made this big decision to kind of train models yourselves. That takes money. It takes expertise. [30:44](https://realalpha.app/v/wQGIp0KouWY/?t=1844) Why did you do that? Well, I think the big decision isn't that we train models. It's that we kept training models, right? Because when we started in 2020, there weren't third-party models to use. I mean, we started Rider to commercialize transformers. I think we continued to train models as we saw that, you know, the labs might be a few weeks ahead, but everybody's following the same research breadcrumbs. And especially as we started using synthetic data quite early in 23, we just never really felt that the capital gap meant a capabilities gap. And sure, they may [31:19](https://realalpha.app/v/wQGIp0KouWY/?t=1879) **May Habib:** be ahead, but there are plenty of eras of this chessboard where we were ahead, right? The thing is with the enterprise, it doesn't really matter because they're still trying to catch up to the innovation that you launched 24 months ago. And so we never felt like we needed to go use third [31:34](https://realalpha.app/v/wQGIp0KouWY/?t=1894) party models, right, to be able to deliver for customers and to be able to deliver frontier performance for customers. The ability now for a customer to use any third party model has given them much more commercial optionality, right, that allows them to check a box than like actual usage, right? Because people get in and they're like, oh, Planera is cheaper or faster. There's really no reason for me to switch off the default, right? But they can if they want to. What it's also allowed us to do is to be able to say at a Unilever, at a Mars, you want to create a video, you want to create an image. [32:06](https://realalpha.app/v/wQGIp0KouWY/?t=1926) So, we already do brand and compliance for videos and images. But if you want to create them, well, just hook up a third-party model. At NVIDIA, they use Nemetron because that is a big edict across the firm to, you know, drink their own champagne, et cetera. So, they want to be able to use their own models. At Vanguard, they had fine-tuned a model on voice of the customer and sentiment. They used that for a number of use cases for a long period of time. So it gives folks the optionality, but we're never not going to be a company that builds and trains its own models. But we don't consider ourselves a lab. [32:39](https://realalpha.app/v/wQGIp0KouWY/?t=1959) What makes you not a lab? Research products. product and go-to-market are one team. So it's everything from a single Slack to a single force in front of the customer. When Cigna started using self-evolving models, they're talking to Dan, our head of research. Dan is at the office, right? He's walking the halls. And it really is just this weekend, you know, we've got Palmyra 6 that we are testing. And I came across a use case where I way prefer Palmyra 5, right? And so that resulted in, this is why, you know, I will perpetually be working 90 hours a week, resulted in, right, like a deep amount of data that I was able to provide to the research team. [33:18](https://realalpha.app/v/wQGIp0KouWY/?t=1998) So it's that continuous loop of product and research and then our go-to-market teams who are literally on-site with the customer saying, this works great, this works shit, we need to improve this, right? We need the model to be able to do X, Y, Z. And that is what makes us a product company, not a lab. When you think about what gives Rider a moat or sort of real differentiation, is it how the technology is packaged together? Is it more a user experience for that end customer? What is the sort of framework you use today? The idea of a moat is just incredibly different today than it was in the era of SaaS. [33:56](https://realalpha.app/v/wQGIp0KouWY/?t=2036) Today, we think about our moat as, yes, all of the above, but the ability to do that at pace while driving customer adoption. Because it's actually our North Star for the past five and a half years has been productizing to the capabilities of what the models can do. And if you leave behind the customers that have joined you at each era of capability, then they don't believe that you are there for them anymore. And the kind of organization you need where, you know, we're almost 500 people, where every single role is in a constant state of up-leveling to meet that most ambitious customer with the most ambitious product, but also empathetic enough to bring forward the customer who hasn't yet passed a security review to turn on any connectors or doesn't have any power users yet doing really advanced stuff or needs a lot more hand-holding to kind of rewire a workflow end-to-end. [34:49](https://realalpha.app/v/wQGIp0KouWY/?t=2089) That, I think, is our moat because we can go into an organization and no org is a monolith, right? Nobody is all in or all power users or, you know, all wired up. It's within the same customer, multiple generations of capabilities, ambition, et cetera. And I think taking that and making sure our product reflects that. and our EPD team and research team are empathetic to that, I would consider them out. Another kind of interesting framework that I've seen is, do the general advancements from the labs or from anywhere in AI help a company because they build on top of it, or do they innately compete? [35:30](https://realalpha.app/v/wQGIp0KouWY/?t=2130) You were a little spicy earlier about OpenAI and Anthropic maybe not delivering in some of these places. They will continue to develop Cloud Cowork or some of these white-collar uses of their tools. Will Ryder be able to just sort of continue to stay above and build on top of any advances they might have? Or do you have to stay faster, better, deliver better results in a head-to-head? Yeah, that's a good question. You know, a lot of people have this misconception that, you know, the capabilities of the models improving reduce the TAM for companies like us. And, you know, the history of this space is that that's not the case. [36:08](https://realalpha.app/v/wQGIp0KouWY/?t=2168) And if you think about it from a preferences perspective, you'll get to understand why. No matter how good the model is, it doesn't understand a customer's own preferences. [36:17](https://realalpha.app/v/wQGIp0KouWY/?t=2177) **May Habib:** And in so many ways, whether it's built-in brand, built-in compliance, or ability to structure these workflows, scaffold them, et cetera, is essentially a preferences stack. [36:28](https://realalpha.app/v/wQGIp0KouWY/?t=2188) And actually, your need for that as an enterprise increases the more the LLM capabilities increase, right? That surface area of preferences increases a lot more with agentic, right? It explodes exponentially. And the customer's own ability to manage that or rebuild it with co-work, right, is actually just too complex. And our moat is being able to aggregate everything that we have seen pharma need in marketing or CPG need in sales or, you know, wealth and asset management need in front office and help productize that. So, not only that nth customer benefits, but that, like, why team in the same organization that's onboarding benefits? [37:13](https://realalpha.app/v/wQGIp0KouWY/?t=2233) And it's that really tight productization cycle on top of the increasing LLM capabilities. And so, you know, very little of what the LLM companies productize actually impacts us structurally. Certainly, the hype and the headlines and the indecision that it forces the customer to make, right? I think it was just last week where Anthropik's giving away $10 million per organization, right, to a product that has no mold. It's absolute insanity. And I think the enterprises that understand why that is not in their interest, right, are the ones that become our target market. Well, you mentioned that they might also sell something and then leave, but we have seen these companies invest heavily in services. And I guess I'm curious, you know, with Rider, do you hope that the Rider agent can basically get someone who maybe doesn't feel AI native, not a power user, to become an effective user? Or do you also need to have services people training to kind of get those, you know, late adopters to feel good? [38:17](https://realalpha.app/v/wQGIp0KouWY/?t=2297) Two reactions. I think it tells you how little they speak to enterprises, the fact that they launched services companies. Enterprise hates service companies, right? You talk to any CIO after a drink and they'll be like, fuck me if I help seed the next Palantir, right? And like seed that power, right? They don't want SIs. They want leverage over the SIs. And so the idea that somehow DeployCo, right, is going to be more successful in the team that built the product, right, because there is such a tight feedback loop between us knowing how the models work and the product work and helping the customer to make it work internally and have their own people be the reason why it works, right? [39:00](https://realalpha.app/v/wQGIp0KouWY/?t=2340) This is a teach you how to fish, not fish for you, and being able to help build that capability internally is what the customer actually wants, right? They don't want their place crawling with consultants. It's been crawling with consultants, and, you know, the results haven't been there. And so, you know, this idea that deploycos, you know, generically solve the problem is no one that I have talked to is going out excited about that, right, in the enterprise. I think the second thing is, you know, what we are doing, I haven't seen anyone else do, is really help the product onboard people, right, in a natural language, very conversationally driven way. [39:40](https://realalpha.app/v/wQGIp0KouWY/?t=2380) And enterprise brain helps a lot, right? This is the functionality that creates kind of proactive shared context. So, you know, if I'm asking how many salespeople does Blue Shield of California have because I'm getting on the phone with the CRO and CMO and it helps tell me like all of the other sessions related to that account, right? So not just what's in my CRM, but what are people actually agentically doing, right? What are the agents doing for that account helps me understand much better how I can help these folks I'm about to talk. That doesn't exist anywhere else. You don't get that with service people, right? You only get that agentifying your own people and helping them use each other's context. So I'm a lot less concerned about folks who outsource their own implementation. [40:27](https://realalpha.app/v/wQGIp0KouWY/?t=2427) There is a narrative popping up more and more now of companies spending for these tokens without necessarily feeling great about an ROI yet. I think Uber and Uber executives sort of famously said earlier this year they'd already blown through the whole annual budget. It's happened to dozens of people now. Is there justifiable concern or sort of soul searching that should be happening from that? Do you think spending those budgets earlier is a good thing in a way? Like, what would be your response as customers say, hey, May, what's going on with everybody, you know, spending so much here? Should we feel good about it? [41:04](https://realalpha.app/v/wQGIp0KouWY/?t=2464) **May Habib:** The answer to you never, no one got fired for buying IBM should be people fucking getting fired for buying IBM. [41:12](https://realalpha.app/v/wQGIp0KouWY/?t=2472) So, like, that's the best way, right, to get and infuse some sanity into this market. Almost every one of our customers has everything under the sun and they don't get results. And our ability to come in and help them get results is just about thoughtful product meets thoughtful implementation meets thoughtful rollout. And the token maxing across all aspects of the business, I think on the coding side, you know, Cursor and others have built in the actual, like, budget constraints, right, and that functionality. Anthropic hasn't, right? Right. And so I'll meet people where it's three mil of overage on two weeks of like the plug in in Excel. [41:56](https://realalpha.app/v/wQGIp0KouWY/?t=2516) Like, what's the ROI on that? Zero. Right. Excitement, maybe. But if you're not learning the right lessons, then that is not money that is well spent. And CEOs are just having to get involved. I think CFOs will have to get involved. I almost wonder if Ryder and your peers get punished by being more mature companies for good and bad here. Like, you can't claim maybe the runaway spend with customers that might create that record ARR number, right? Like, you know, and at the same time, you know, you guys were last valued, I think, at $1.9 billion. That would be amazing 10 years ago when we first met. [42:34](https://realalpha.app/v/wQGIp0KouWY/?t=2554) And now we do see these pre-launch AI companies with no product raising it even more than that. It's almost like... It's a negative premium for having a real company. Or like in Silicon Valley, the show, you know, when the VC is like, no, never have revenue. You know, you always want to say free revenue. Yeah, I think the, you know, the answer is the terminal value is the only thing that matters, right? And, you know, for us in a lot of ways, the runaway market hasn't materialized yet. Why? We have a process that is really well structured to be able to turn human and AI collaboration into working code, right? [43:10](https://realalpha.app/v/wQGIp0KouWY/?t=2590) Does that happen in sales? Does that happen in marketing? Does that happen in HR? We don't have the scaffolding to be able to take agents and get them into production with human oversight that is well-known, well-established, easy to audit. And that's the scaffolding that we are building for these teams. And that's the difference between production and scale. The explosion happens when teams and organizations trust the agent as much as they trust the people and trust the new people managing these agents just as much as they trust the old way of doing things. And that explosion is incredibly latent, right? [43:48](https://realalpha.app/v/wQGIp0KouWY/?t=2628) We haven't announced these things. So we've met a lot of the milestones that people, you know, brag about. I think for us, the thing that we will be bragging about is when we have the same kind of agentic autonomy in the enterprise that we all have in engineering and coding domains. And we're not there yet because the customer is not there yet. The trust is not there yet. One question we ask everyone on the show is about their upstart moment. And I am curious with you whether you feel like your upstart moment would have been more in the early days, you know, getting those first customers to sign up or today when, you know, these companies are getting trillion dollar market caps and there is a lot of noise in the market. [44:25](https://realalpha.app/v/wQGIp0KouWY/?t=2665) I see it in the future. I mean, I don't know if that's like a cop-out answer, but it does feel harder now, frankly. And I can't wait for these companies to go public and just like, you know, have everybody really understand how much space there is and how much room there is for everybody else. anyone who's building in this space right now, it's just the biggest challenge, right? Hiring, retaining employees. And I think, you know, when it comes to folks who their goal is to be a founder, their goal is to build, they're not going anywhere, right? But it's a gold rush for everybody else. And, you know, really holding on to that top talent is it's a challenge for every builder right now.