May Habib: Pioneering AI Innovator and CEO of Writer.com – Episode 14

May Habib May Habib is the CEO at Writer.com, a generative-AI platform that has been helping enterprises use AI since 2020. Her company builds its own award-winning large language models and is pioneering approaches like "headless AI" to help employees across an enterprise use AI to be more creative and productive. We talked about: her work as CEO at Writer.com, a "full-stack generative-AI platform," for the past four years her decade-long work in the AI and NLP space, beginning with translation solutions her take on the "over-chat-ification" of AI products, the reliance on chat interfaces as opposed to other ways to access AI capabilities her prediction that 2024 will the "get real" year for AI the use of fine-tuning and/or RAG to connect learning models the inadequacies of vector databases for knowledge retrieval and their exploration of knowledge graphs to fill the gap a new role, the "AI ontologist" another new role, the "AI program director" which includes a mix of left- and right-brain thinking and technical skills some of the use cases for "headless" AI their approach to securing and protecting the various kinds of data used in their LLM how she sees the role of data scientists in AI their tactical approach to building knowledge graphs for specific business use cases their work at Writer on no-code and low-code tooling to help their customers build solutions and tooling on the platform new content job roles that are emerging as AI takes hold in enterprises May's bio May Habib is CEO and co-founder of Writer, the only fully-integrated generative AI platform built for enterprises. Leading companies, including Vanguard, Intuit, L’Oreal, Accenture, Spotify, Uber, and more, choose Writer to help them deploy generative AI across their businesses, allowing them to automate and augment key operational activities and increase employee creativity and productivity. Writer’s family of large language models (LLMs) are state-of-the-art, topping leaderboards for natural language understanding and generation. The company’s security-first approach means that Writer’s large language models and generative AI platform are deployed inside an enterprise’s own computing infrastructure. Launched in 2020, Writer has seen immense success with customer adoption, has grown revenues by 10x in the last two years, and has over 150% net revenue retention. May and the Writer team have successfully raised over $126M in funding from notable investors, including ICONIQ Growth, Balderton Capital, and Insight Partners. May began her entrepreneurial journey as a teenager, and founded her first language startup, Qordoba, a localization software company, 10 years ago. May is an expert in AI-driven language generation, AI-related organizational change, and the evolving ways we use language online. She has been recognized for many different awards, including the recent 2023 Forbes AI 50 and Inc.'s 2023 Female Founder Award. She is a MELI Fellow with the Aspen Institute. She graduated from Harvard University and spends her time between San Francisco, where Writer is based, and London, where her two children live. Connect with May online LinkedIn email may at writer dot com Video Here’s the video version of our conversation: https://youtu.be/lFTfA4X8CkA Podcast intro transcript This is the Content and AI podcast, episode number 14. Over the past year and a half, innovative artificial intelligence startups have taken the tech and content worlds by storm. In her position as the CEO of the generative AI platfom Writer.com, May Habib has been right in the middle of the excitement, and out in front of it. Writer and their clients were deploying LLM-driven generative AI programs inside of large enterprises long before OpenAI's ChatGPT 3 captured the headlines and launched the current wave of AI disruption. Interview transcript Larry: Hey everyone. Welcome to episode number 14 of the Content and AI podcast. I am really delighted today to welcome to the show Me Habib. May is the CEO and co-founder at Writer, an app many of you're familiar with. They're just having a great year and I was excited to get her on the show towards the end of 2023 to talk about topping the MMLU leaderboard with the Palmyra, their LLM, closed the nice funding round. Sounds like things are going well at Writer, May. May: Oh, thanks Larry. It's so nice to come back and chat with you. Yeah, we've had a great year, thank goodness. I've got our last all-hands of the year after this conversation, and so it was definitely nice to look back. We do these weekly updates to the whole company. I write them, and I went back and looked at week one and compared it to week 52, and then one's like, "Oh, let's go back a little further." I went 2022, week 52, and then 2021, week 52, and yeah, it's awesome to see things build and all the progress. Larry: Yeah. Well and one thing, and you've been part of that progress. ChatGPT, which is where the current kerfuffle is all about, that's barely a year old, but Writer's older, and Cordova was even older than that, right? May: Yeah, well we've been in the NLP space for a decade, me and Waseem, and starting in machine translation. I think we were able to come to the world of transformers with maybe two distinct advantages, I think, over the folks that are in the space now, OpenAI and others as well included in that. May: One is, we were very much less a technology and search for a problem. Because we saw so many content challenges in the enterprise that could be solved with AI, having come from translation. So, it allowed us to really take a solution-based, outcome-based approach to thinking about how to productize this cool technology versus not. May: Now, obviously a general-purpose AI-based chat has captured the imagination, and has been an incredible thing that the OpenAI team has introduced that we obviously didn't think of, but in a lot of ways what it's done is open up what people thought could be possible with AI, and it's made room for solutions like ours to really explode, because we really serve that enterprise need, that very solution-specific application that is enterprise-ready, is secure. So anyway, it has been a fun road and a really fun four years with Writer. Larry: One of the implications, and you know as much about this stuff as anybody, in fact you're right up there with OpenAI in terms of your accomplishments and the power, the service you offer. I'm curious, what are you like... And I think there's a couple of things in this question and that I'm hoping to get out of this conversation. One is just the general state of the AI market. A lot of what you just said, I think it's going to help people ground themselves and feel it. But I think one of my questions is, for example, is this just another SaaS app that the software in the background is an LLM, or will there be fundamentally different things you think that content folks have to consider as they go into both working with these tools and working on these tools? May: Yeah, I think maybe taking that question a couple of ways. One, the user-experience cut of the market, and then the where-are-dollars-being-spent cut of the market. I think it'll allow you to see the gap that we see and that we feel, actually, looking at it in these two ways. I think from an end-user perspective, that cut of the market, there is this over-chatification of what AI can do, and everything is a fricking dialogue to get stuff out of AI, and it's just so early, and the interfaces obviously shouldn't all be chat UIs, but that's kind of the case right now. Whether somebody gave you a Copilot license or you're personally paying for ChatGPT Enterprise, I think most people aren't getting the value they thought they would, given all of the headlines. May: That adoption gap isn't because the capabilities aren't there because we are building the capabilities. They are fricking crazy magical, and I think when we chatted last, I said probably something along the lines, if this was 18 months ago, I probably said, "Larry generative AI is like giving everybody an assistant and a chief of staff." I mean, that's not what it's like anymore. It's giving you the best version of yourself, 20-years expert into the future. There is so much, even in 18 months, so much that the models can do. May: Anyway, all to say that the end-user experience cut of the market is super under-optimized and today, despite all of the hubbub, I can't go into my sales force and say, "I'm in London in January, who should I see of our deals that are closing in Q1?" So even the AI that's supposed to get built into all of our systems of record, isn't really doing the things that we want it to do. Folks who are trying to connect Copilot to their Microsoft data aren't seeing the kind of answers they would like. And I think power users who have figured out how to get a lot of value from ChatGPT are, but your median user really isn't. So, that's that cut of the market. May: In terms of where there are real dollars being spent here, I think the enterprise is probably over-investing in the infrastructure and the utility model layer, and are trying to rebuild from scratch every use case, and there are a lot of things that are breaking about that experience. And the total cost of ownership, I think, isn't making sense for a lot of companies. The accuracy and business impact of some of these pilots and POCs isn't materializing. May: So, next year is going to be get-real year, which is exciting. I think we'll see a lot more exciting end-user interfaces and experience that build on the toy making and piloting of tools this year. And then I think enterprises are going to be really looking for just more comprehensive solutions to filling generative AI needs internally. Larry: Yeah, a couple of follow-ups. First thing,