AI-Powered Revenue is Here

1. 0:00 – 0:05

   Intro

   1. DHDiana Hu0:00

      [upbeat music]

2. 0:05 – 0:33

   Letter.ai’s mission: AI-native sales enablement to speed ramp and deals

   1. DHDiana Hu0:05

      I'm excited today to welcome the founders of Letter.ai, who are announcing their 40 million Series B round. Here is Ali and Armen. Tell us, uh, what Letter.ai is.

   2. AAAli Akhtar0:18

      Hey, Diana, nice to be here. Uh, Letter.ai is an AI-native enablement platform, which means we help revenue teams ramp up more quickly with personalized training, coaching, and also deliver content to engage buyers, ultimately to accelerate the deal cycle.

3. 0:33 – 0:47

   Customer traction: enterprise logos plus fast-growing startups

   1. DHDiana Hu0:33

      Who are some of your top customers that are live right now?

   2. AAAli Akhtar0:36

      Yeah. We have a, a healthy mix of customers across large enterprises, like Lenovo, uh, Adobe, Novo Nordisk, uh, as well as fast-growing startups like Plaid and Kong.

4. 0:47 – 1:21

   Core use cases: onboarding, in-cycle content, and AI role-play practice

   1. DHDiana Hu0:47

      That's a pretty good list. What are some of the key use cases that they, that they handle with you?

   2. AAAli Akhtar0:51

      Across the spectrum. So, uh, first and foremost, onboarding new team members, making sure they're productive in about half the time as they were prior to Letter. Uh, second is through the sales cycle, as questions come up, as customers request content, being able to leverage AI to, uh, be able to curate personalized content to be able to share with the prospect at just the right time. We have an AI role-playing simulation capability as well, so you can practice before you go into a call with an actual buyer. Uh, and a whole host of new capabilities we're launching as well.

5. 1:21 – 1:37

   Why simulations matter: reducing risk in high-stakes sales conversations

   1. DHDiana Hu1:21

      Hmm. Sort of a simulation for sales folks before they actually do the actual sale conversation, right?

   2. AAAli Akhtar1:28

      Exactly. You don't wanna fail in a live conversation, especially with a high-stakes prospect, and so Letter allows you to practice many times before you ever go into that conversation.

6. 1:37 – 2:06

   From YC to Series B in 2.5 years—and a major pivot from Tractatus

   1. DHDiana Hu1:37

      So the interesting thing is, you guys were here doing YC not too long ago, and you already raised a Series B. You were here at YC just two and a half years ago. Uh, but not many people know that when you went through YC, you were a very different company-

   2. AAAli Akhtar1:56

      Yes

   3. DHDiana Hu1:57

      ... and had a different name. You were Tractatus.

   4. AAAli Akhtar2:00

      Yes.

   5. DHDiana Hu2:00

      What was then... What did you learn that that idea didn't work? And tell us a bit about that initial journey.

7. 2:06 – 3:08

   Why Tractatus didn’t work: saturated devtools and low stickiness

   1. AAAli Akhtar2:06

      Yeah, absolutely. Arm- Armen, you wanna tell the story of Tractatus? [chuckles]

   2. AFArmen Forget2:09

      Uh, yeah, we were basically doing, uh, developer tools for generative AI, and through the process of Y Combinator, um, we learned very quickly that this was, uh, probably not a great idea. Uh, the field was getting very saturated. Uh, we were trying to sell SaaS tools to developers who wanted to write Python code, and, uh, they would, uh, very quickly do prototyping in our platform, and then they would just go build it themselves, and so it wasn't very sticky. And, uh, you know, we changed the name as well to make it-

   3. DHDiana Hu2:40

      [chuckles]

   4. AFArmen Forget2:40

      ... a little bit more, more mem- memorable.

   5. DHDiana Hu2:42

      What was interesting is you landed on this idea, which, at the surface, seems like it should be very crowded or very old school. There's just so many tools in sales. Uh, but Ali, you figured out s- a unique insight during the batch, and what was that, and what happened? Because the impressive thing is, you were actually able to close Lenovo as a customer in the batch-

   6. AAAli Akhtar3:06

      Yeah

   7. DHDiana Hu3:06

      ... which is very rare.

8. 3:08 – 3:57

   The enablement insight: expensive legacy tools with low adoption

   1. AAAli Akhtar3:08

      Yeah. Yeah, it was, it was quite incredible. And for us, y- you know, the big insight was, uh, it really driven by personal experience. So when I was at Samsara and at Project 44, I had used some of the legacy enablement stack. Uh, I remember every single week I would get pinged by a seller at Samsara. There, I was director of engineering for machine learning. Uh, nothing, no involvement with the sales org by role, but I'd get pinged by sellers asking: "How does this product work? Can you tell me about these features? Can you come and give a talk on it?" And I remember saying, "Hey, why don't you go find all the content we put together, all the learning we put together in our legacy enablement tool?" And the sellers would say, "I can't find anything in there. I barely log in." Uh, and so, uh, you know, that was kind of light bulb moment number one, is there's this really expensive tool, which by the way, I couldn't even get a license to-

   2. DHDiana Hu3:57

      Mm

9. 3:57 – 4:27

   AI as the unlock: personalize content without staffing an army of humans

   1. AAAli Akhtar3:57

      ... uh, because it was so expensive, uh, that it's getting very low adoption. Uh, and the second kind of insight here was, um, a lot of times to get leverage and adoption out of enablement tools, you really need to throw a lot of humans at it, and so humans need to be out there curating content, building content, building training. And we found that with AI, you could actually tap into existing sources of knowledge and accelerate the process of highly personalized content development, and speed is what matters in today's day and age for, you know, uh,

10. 4:27 – 5:03

    Enterprise-ready early: how Lenovo became a rare YC-batch customer win

    1. AAAli Akhtar4:27

       high-velocity sales organizations. Uh, and so we thought, "Let's just rethink this entire set of use cases using AI," and that's how Letter came to be. Uh, and Lenovo actually started through, you know, uh, someone I knew there, uh, from a previous job, uh, who, you know, was kind enough to see what we were trying to do, and it lit a light bulb in his mind, and he connected us to the right folks within sales. And once they saw what we were building... And we took a few steps to make sure we were enterprise-ready early on in the journey. Uh, that helped us unlock, uh, you know, a fairly substantial deal with them that's since grown 10x, uh, over the course of the past, uh, two years.

11. 5:03 – 5:38

    Bridging product velocity and sales readiness: translating fast shipping into sales materials

    1. DHDiana Hu5:03

       So that's kinda interesting. So you're telling me there's this gap between basically the product engineering team that's shipping things very fast, especially now-

    2. AAAli Akhtar5:13

       Yeah

    3. DHDiana Hu5:13

       ... in the age of intelligence, product velocity is very fast, and then there's this gap of translating what is in the product to the sales team-

    4. AAAli Akhtar5:23

       Yeah

    5. DHDiana Hu5:23

       ... who's not technical, can't necessarily read the code. But now, with AI, you basically supercharge them and automatically produce all the features and, and, and sales materials for the team to go at it.

    6. AAAli Akhtar5:38

       Yeah.

12. 5:38 – 6:40

    Customer impact story: acquisition onboarding compressed from a month to a weekend

    1. DHDiana Hu5:38

       So can you tell us about what are some of these results with some of your customers? Because you were telling me about, um, this story of a customer that just acquired a company, and-

    2. AAAli Akhtar5:49

       Yeah

    3. DHDiana Hu5:49

       ... what was that before you and with you?

    4. AAAli Akhtar5:53

       Yeah, absolutely. We have a customer who's a Fortune 100 customer and, uh, made an acquisition, a global acquisition, and was onboarding hundreds of new sellers, uh, into the company. Uh, they announced that acquisition internally on a Friday.... and by Monday, they had a whole certification in terms of wrapping up these new sellers onto the acquiring company's way of doing business. Uh, and what they told us is, pre-Letter, an exercise like this would've taken them at least a month and tons of folks to get done, and with Letter, they were, they were able to do it over a weekend with just about two or three folks online. Uh, and that's the kind of impact and velocity that you need today, uh, particularly because the entire industry's evolving so quickly with everything we're seeing happen with LLMs and AI.

13. 6:40 – 7:25

    From ‘nice-to-have’ to essential: near-100% adoption and daily workflow pull

    1. DHDiana Hu6:40

       Interesting. So one of the thing that happens in this space with sales tools, they tend to be a lot of times sort of just nice to have, but you've found something unique where you've become a core essential. Tell us about, about that.

    2. AAAli Akhtar6:54

       Yeah. One of the things we love to hear about Letter is, particularly compared to the legacy tools, where adoption can sometimes be less than 50%, we see customers with close to 100% adoption. Sellers are going in there every single day, every single week. Uh, and in fact, we heard an anecdote from one customer that if Letter disappeared, there would be a line of folks outside the door of the enablement team banging and asking for it to come back. Uh, and I think a part of how we're making Letter essential is actually related to a new product that we're launching called

14. 7:25 – 8:23

    Product expansion: Letter Compass and a new vision for CRM-like guidance

    1. AAAli Akhtar7:25

       Letter Compass. Uh, Letter Compass takes the broader enablement content and enablement material that sales teams have historically surfaced to the field, you know, things like content, pitch decks, training, certifications, role plays, and it automatically personalizes it to the book of business that a particular seller or a customer success manager owns. So now when you log into Letter, it's no longer a generic training on XYZ product, it's a training that's relevant to the deal that you're pursuing today. It's insights and follow-ups that tap into your conversational intelligence data and CRM data to help you really push the deal forward in a very tangible way. Uh, and I think that moves Letter more and more to being an essential tool, and really, it forces you to rethink, like, what does the future of CRM look like? You know, is that really what customer relationship management should be, where AI is presenting insights for you to moti- motivate and move a deal forward? Uh, and, you know, we think that's where the world's headed.

15. 8:23 – 9:19

    Under the hood: MCP servers and agent-to-agent integrations for customer AI stacks

    1. DHDiana Hu8:23

       So what are some of the interesting things you've built on the tech right now, especially with AI, that has made all this possible?

    2. AFArmen Forget8:32

       Yeah, we've been noticing a lot of our customers are becoming also very AI-centric, and they're building their own internal tools or even, uh, tools that are customer-facing to their, their customers that are using AI, like agents, and, uh, they're now using MCP servers and things like that. So we've been building, uh, our own, like, Letter AI MCP servers. We have agent-to-agent protocol that allows, uh, you know, our customers, uh, either their... from their web applications, their agents to talk to ours for distributed, uh, thinking, for example. Uh, or they- their salespeople, uh, now are sometimes in Cursor, and they're doing their own research, and now they can use the Letter AI MCP server to get the content or get answers to the questions they need like that. So it's very, uh, you know, very productive for them.

16. 9:19 – 10:20

    Where Letter.ai is headed: ‘Never sell alone’ as the daily operating system for sellers

    1. DHDiana Hu9:19

       So now, where is, uh, Letter AI headed?

    2. AAAli Akhtar9:23

       The future of Letter AI is to be the single most important tool in a seller's toolkit, the single most important platform that they log into every single day. We like to use this term, "Never sell alone with Letter," and so we think of Letter agents, uh, the Letter, uh, platform capabilities being something that's essential in the day-to-day operational workflow of every customer-facing team member. And so, uh, we're super excited to be launching Letter Compass as a huge advancement, uh, in that particular direction, as well as Armen was saying, becoming a core part of our customers' internal AI investments, and even customer-facing AI investments, uh, through what we're doing on our agent-to-agent protocol and, uh, on the MCP server side.

    3. DHDiana Hu10:06

       This is great. Thank you for coming and joining us. Congratulations on the Series B announcement again.

    4. AAAli Akhtar10:11

       Thank you.

    5. AFArmen Forget10:11

       Thank you. [upbeat music]

Episode duration: 10:20