Sixfold Resources

Dive into our Q&A with Brian Moseley, Co-Founder and CTO at Sixfold. We're chatting about his tech journey, from the early days at Sega to his recent tenure at American Express, and what led him to Sixfold. Brian also shares insights into the team's 'chill, pragmatic, and adaptable' culture and talks about his passion for Warhorn, his own gaming community project.

What’s your career path and how did it lead you to becoming Sixfold's CTO?

My software career began in college when I joined my friend’s community and media startup; we were among the first to experiment with web-based advertising. Through this venture, I met many tech professionals in San Francisco, who got me excited about the emerging web scene there. Ultimately, I decided to leave school and move across the country to work at Sega of America, focusing on database administration for their website.

From there, I joined several early-stage startups, including Critical Path, where I was the 17th employee. I experienced growth through its IPO, becoming an engineering manager and software architect. Later, I worked at the Open Source Applications Foundation, implementing a number of obscure internet protocols as the lead of an open source calendaring server.

As my career progressed, I found myself being the first engineering hire at a startup and then the first employee of another, so the logical next step was to become a cofounder and the CTO of Hoodline, a hyperlocal journalism company. Unfortunately, we did not succeed in reinventing local news, so I decided to try my hand at a big company and started working for American Express. 

I made the leap to full-time engineering management at Amex and eventually spent five years as the firm’s Head of Developer Experience, serving a global crew of 10,000 software engineers. Working in a big company was an incredibly educational part of my career, but I increasingly had the itch to build something from scratch again. So, Alex’s pitch got my attention and ultimately led to me cofounding Sixfold AI.

What originally attracted you to Sixfold?

It was a combination of three things:

1️⃣ I’d been looking for some time for an opportunity to build a company, team, and product from scratch.

2️⃣ I had a great time working with Alex briefly back in the early 2000s, so the prospect of cofounding with him was super appealing.

3️⃣ It seemed like exactly the right moment to go after the opportunities unlocked by generative AI in vertical business domains. Everything I saw was focused on LLM infrastructure and tooling, but nobody was talking in public about using generative AI to solve problems for business users like insurance underwriters.‍

‍How is Sixfold different from other players in the field?

We aren’t encumbered with legacy technology, organizations, or ways of working. We’re building our team and product from the ground up, which means we get to experiment freely and iterate quickly.

Another aspect that sets us apart is our commitment to ensuring our product is something users look forward to, not something they complain about with each use. The complexity and challenging nature of many enterprise software interfaces can be daunting. That's why we focus on user-friendliness and intuitive design.

We value user delight! Sixfold is not only effective; it's also fun to use.

What aspects of Sixfold and its technology are you most passionate about and find particularly exciting?

I love all of my children equally 🙃
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That said, as you might expect, I’m engrossed in the rapidly developing craft of generative AI engineering. What we’re doing goes way beyond basic “chat with your document” scenarios. We have a whole new set of primitives to assemble into complex systems - and they are evolving so fast it’s hard to keep up! It’s particularly interesting to apply these techniques in near real time as part of the live user experience. 

Our AI pipelines are hybrids of batch and streaming, with the work distribution and scheduling needs of batch processing and the resiliency and throughput of a real-time system. “Notebook AI” solutions don’t scale or meet our availability and performance requirements without a lot of additional engineering.‍

How would you characterize the dynamic and strengths of the team?

‍Our founding team has so much experience starting and scaling companies, we’ve all done zero to one many times. That doesn’t mean we don’t make mistakes, but they tend to be new mistakes, not many of the ones we’ve seen before. And my co-founders are teaching me everything there is to know about insurance.

The core of our tech team is a group of veteran startup hands with deep experience in their functional areas who can all flex into team building and leadership as we grow. We built on this core with a group of 'smart and gets things done' engineers who can build fast and iterate quickly, especially the closer they get to the AI layer of our stack.

Ultimately, our tech team is able to build, test, and learn quickly while keeping the quality bar high. And our go-to-market team keeps us oriented, fusing an understanding of what our customers need with a compelling vision for the future of underwriting.

How do you contribute to the team's growth and development?

As a hands-on-keyboard software engineer for nearly 30 years, I lead our product and platform development from the front. I pair with our engineers to help them develop their core software skills, which include architecture, design, coding, troubleshooting, and operating in production. This also provides an opportunity for them to build mentorship skills, as there is much I can learn from them as well.

I strive to create opportunities for our team members to step outside their comfort zones. Most of our engineers arrived with a specialization in some technical area, whether it be front-end development, infrastructure, or AI. However, our team is most effective when any member can work on any feature, regardless of where it falls in our stack. Therefore, I encourage each engineer to become proficient in all our languages and frameworks. For example, an AI engineer might make changes to our core domain model in Ruby, or a front-end engineer could add a new step to our AI pipeline using Python.

What is an achievement you are particularly proud of that the team has accomplished since the launch?

I’m most proud that we’ve been able to make the product work the way we envisioned it. It’s not just about our accuracy, which is great and getting even better. Remember the first time you experienced the magic of ChatGPT? Underwriters have that same feeling when they use Sixfold AI. They don’t have to read a hundred pages of tedious documents anymore just to find the three hidden nuggets that show the risk in an insurance case. They can sit back and let Sixfold find the nuggets for them in a matter of minutes. Magic!

In three words, how would you describe the team's culture?

Chill. I don’t mean we’re not working hard or that we don’t have high intensity about our venture. But you can tell that most of us have been in startups before because people handle the pressure really well. Nobody’s freaking out or creating negative vibes. We all have each others’ backs.
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Pragmatic. We aren’t striving for the perfect user experience or the most scalable systems right out of the gate. We’ll get there over time as we prove our right to be in business by delivering things customers want to pay for. We push ourselves to make “two-way door” decisions a little bit faster knowing that we can always iterate or reverse course later.

Adaptable. We develop in quick sprints and frequently stop to check in on what’s most important right now. Some weeks, that’s building features. Others, it’s improving resilience or shoring up security. At this stage of the company, every next customer engagement brings new problem statements and requirements. While we’ve introduced a measure of longer-term planning, we’re still keeping our heads on a swivel (as my high school football coach would say) to make sure our vision, roadmap, and near-term development plans evolve in the face of constant market discoveries.

How do you stay updated with the advancement in AI and LLMs, any particular newsletters or blogs that you like to follow?

I read 'Ben's Bites' daily, a resource recommended by Alex (our CEO) when I first joined. It's even included in our welcome email to all new team members. In addition, I follow 'The Information', particularly their newsletter 'AI Agenda', which I find very insightful and full of links to deeper reading.

Our team is also a significant source of discovery. Team members are constantly tuned into various niches and aspects of our industry, sharing relevant links and resources in Slack. We’re reading each other's stuff all the time.

Could you share some of your favorite tech tools or frameworks that you rely on heavily?

iTerm and Visual StudioCode - This is where I write and run my code. Others love their all-in-one commercial IDEs, but I do just fine with these tools.

Ruby and Rails - I’ve been building Rails apps and writing scripts and command line tools in Ruby since 2007. It just keeps getting better! I spend a lot of time with JavaScript as well, and it’s fine, you can’t really get away from it in the modern world, but I’ll always reach for Ruby when I can.

React - Again, I have been doing it since near the beginning, and it still scratches the itch. Haven’t had any reason to embrace the Hotwire part of the Rails omakase experience or to dabble in any of the post-React web frameworks. Maybe somebody out there will finally make me see the light?

Linear - Modern project management for product development that strikes an almost-perfect balance between the “all batteries in the universe included” and “bring your own batteries” approaches of pretty much everything else out there.

Mermaid - Being able to create a diagram by writing code has 10 x'ed my output of diagrams, which improves the clarity of my engineering dialogues.

Do you have a favorite AI solution that you would like to highlight?

Not yet! The gen AI ecosystem is still immature and changing rapidly. The popular tools and frameworks don’t always prioritize qualities we require for production usage - stable APIs, for example, or the ability to bring your own observability tools or work distribution systems. We’re having a better experience stripping down to the basics and devising our own abstractions over AI primitives (model and vector store APIs, for example) and in-house utilities.
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Ask me again in 12 months - I may well have a different answer!

Any fun tech projects that you're working on at the moment (non-Sixfold-related)? 

Yeah, there are two main things I'm focusing on outside of work. Firstly, I've recently picked up World of Warcraft again after about a year's break. It's been a fun way to spend time outside of building our company.

More to the point, I started a website back in 2001 called Warhorn, which I'm still running today, more than 20 years later. It's essentially a marketplace for tabletop role-playing games, board games, collectible card games, miniatures, word games, and more. I originally created it out of my love for tabletop role-playing, particularly tournament-style games like Dungeons and Dragons. It was born from the need to streamline the logistics, scheduling, and signups for large gaming events. 

The site was initially written in PHP in 2001, then I rewrote it in Ruby on Rails in 2011 and added a React front end around 2016 or 2017. Warhorn has been my laboratory for learning new technologies, such as GraphQL. It's a SaaS offering, which has helped me familiarize myself with various cloud providers and vendor systems. This experience has directly influenced my decisions at Sixfold and at previous jobs.

Warhorn is not just my tech lab but also my way of contributing to the gaming community. It's a long-standing project with over 25,000 monthly active users. I've kept it running as a passion project, not for commercial purposes. It's a creative outlet for me, similar to painting on canvas. It's an enjoyable aspect of my life where my profession and hobby intersect, providing a way to relax and be creative.

Are you excited about the opportunity to work at Sixfold?

Check out our careers page!

We talked with Sixfold’s latest hire, Head of AI/ML Ian P. Cook, PhD about his career journey, how emerging technology will overcome long-standing industry challenges, and his new role as Sixfold’s data science leader.

Welcome to the team, Ian! Walk us through your career journey up to this point.

I caught the bug for quantitative work when I was in grad school studying Public Policy at the University of Chicago. After graduation, I worked in various policy analysis roles, including at the RAND Corporation as well as doing work for all the major defense agencies and other federal orgs.

While doing policy work, I was simultaneously pursuing my PhD at the University of Pittsburgh for Political Science. My trusty “dad joke” is that I wasn’t smart enough to do grad school just once. As part of my research, I taught myself Python and found that my skills in econometrics translated well to the then-exploding field of data science. After I received my degree, I worked with startups and went from building tech products to building tech teams as Chief Data Scientist with a GovTech company and Chief Technical Officer for a business analytics SaaS.

Are there any tech projects you’re particularly proud of?  

One of my favorite projects was a matching & recommendation tool for patients. A significant predictor of poor health outcomes is missing doctor appointments, but as it turns out people don’t just “miss” them, they avoid them when they’re not happy with the style or approach of a doctor or practice. This was a problem that me and my team believed could be engineered around. 

I oversaw the team building the machine learning functionality for a web tool that assessed both patient preferences and the style of healthcare providers and then turned that into a kind of Match.com for healthcare. Not only was it fun to build, but I’m particularly proud to know that it helped keep people getting the care they need.

Why Sixfold?

Sixfold immediately piqued my interest. The company is attacking a clear and sizable pain point for a well-defined customer (anyone with startup experience will tell you that’s not always the case). Plus, they’re doing it with what I see as generation-defining tech—LLMs are amazing in their own right, and having the opportunity to put them to practical use is an exciting opportunity. After meeting with the team and the leadership, I knew that this was where I wanted the next step of my career to be. Excited to get to work with an amazing crew—tip of the hat to Stewart, Drew, and the whole engineering team!

Everyone’s talking about LLM-powered generative AI these days. From your perspective, what are the most intriguing possibilities and potential risks of this emerging generation of tech?

I sit somewhere in the middle between the extremes of the AI discourse: I don’t think AI will give rise to a post-human apocalypse, but I also don’t believe we can just sit back and toss every hard problem at an AI and implement whatever solution pops out. 

We’re going to see these tools accelerate transformation across every industry. In most cases, that will ultimately be a good thing. However, without clear intention behind how they’re applied and oversight into how they’re trained and deployed, there’s a real risk for these tools to cause harm—unintentional or otherwise. Part of the attraction to Sixfold was their emphasis on applying AI responsibly.

As someone with a strong data science background, what does it mean for data to be useful, not just accessible?

Access is an aspect of keeping data well-controlled—like security measures and access control for personally identifiable information, health records, financial information, and other sensitive material. 

For data to be useful, it has to address real problems and it has to have been corralled in a thoughtful, purposeful manner. Usefulness requires someone to understand the question the data is meant to help answer and to be aware of potential biases—both statistical and human-generated—which might limit the applicability of the data.

How do you see your role as the AI/ML leader at Sixfold?

I see my chief responsibility as empowering underwriters to do their best work ever by augmenting Sixfold’s product with AI-powered tools. Achieving that means supporting the people who are developing, testing, and deploying those tools. Some days that might mean coordinating priorities and ensuring everyone has the information and resources to deliver. Some days it might mean being chest-deep in the code myself. And some days, I’m sure it’ll be a little of both. 

What do you see as the challenges of implementing AI in insurance vs other industries?

I’ll admit to being relatively new to the insurance industry. That said, even a n00b like myself understands that it comes with unique challenges like complying with regulations across multiple levels of government; implementing stringent processes to handle and distribute the personal, closely-held data of both individuals and corporations; and making a convincing argument for change in a well-established industry where many are content using tools and methods that’ve been around for decades.

As a seasoned technologist, do you think there are types of tasks that will always be better suited for humans, rather than machines? 

AI is going to take on the tasks that slow us down. I like to think of it as a bionic-like tool that augments and improves human performance.

It’ll free us up to focus on the most important—and frankly most meaningful and rewarding—parts of our jobs.

I’ll also add this: the better the machines get, the more we’re going to lean on philosophy, the most thoroughly human of disciplines. Discussions about LLMs are loaded with terms like “reasoning,” “thought,” and “knowledge,” which philosophers have been wrestling with for centuries. I’m reminded of the discourse in my philosophy courses around intention and will, which are completely distinct from the mechanistic processes in deep learning architectures. Philosophy is often derided as a field with little practicality, but as a technologist, I see it becoming more practical by the day.

How do you keep up with the latest developments in your field?

A lot of reading! There are tons of great newsletters that cover the field. Ben’s Bites is fantastic, but there are tons of great ones across Medium, Substack, and Beehiiv. I’m also a fan of podcasts like AI Daily Brief, The Cognitive Revolution, and Talking Machines. I like listening to those while doing chores, walking my dog, driving, etc. 

Keeping up with the latest research is always a challenge—it was an issue even back in my PhD days because there were always new papers coming out. Part of me feels lucky to have gone through that back then because now AI is moving at warp speed and it’s even harder to keep up. But I’ve learned to master the art of “informed skimming,” which means quickly reviewing summaries, conclusions, and writeups to find key terms that will tell you if the paper is relevant to the problem area you’re taking on.

What tools do you rely on the most for your work?

I’m a devoted fan of Pycharm for coding. I’ve tried switching to VS Code and other flashy new IDEs when they come up, but I always go back to Pycharm. For note-taking, I stick to Apple Notes. There’s a whole world of “second brain”/knowledge management tools out there for taking notes, but I have to refrain from those (anyone familiar with the word “Zettelkasten” knows the depths of that particular rabbit hole).

I learned during grad school that the more extensible a tool is, the more time I waste fiddling with configurations. Tweaking color themes is not “optimizing my workflow,” no matter how many times I repeat it to myself.

What is the best thing a person can do who wants to pursue a career in AI/ML?

Some requirements are hard to skip over: a decent amount of math, and enough knowledge to turn that math into code.

But you don’t have to be a genius at either one. Learn some matrix math, and then play with those matrices and see how you can apply them in predictive software. Then learn a little more, and implement a little more. The key to mastering any skill set is repetition and perseverance. To parrot that old quote about how one becomes a writer: write.

More specifically, I think there are three things everyone who wants to work in this field needs to know: SQL, Git, and enough of one programming language to be productive. SQL is the language of data: getting it, moving it, storing it, everything—if you can’t get at the data, it’s going to be hard to trust that you can work with it. Git proves that you understand versioning, reproducibility, and collaboration. When it comes to becoming thoroughly fluent in at least one programming language, I’ll sidestep the religious wars about which language is best or most useful and just say that the important thing is becoming really productive in at least one language.

Any fun tech projects that you're working on at the moment (non-Sixfold-related)?

I’m a fly fisher in my spare time, and I use a fly fishing app called onWater Fish. I reached out to the app’s dev team and learned they needed some ML-like support. So I pitched in to try out some new ideas. We’ve been successful in implementing some cool in-app computer vision work that anglers can use to record their catches (and brag to friends) all with one picture. It’s been a great way to apply my skills to a personal passion of mine, which has been truly rewarding. 

How can people follow your work?

I’m on LinkedIn, and try to post regularly on the practical application of AI, the future of work, and whatever else where I might have a useful take. For other social media, I can usually be found by searching @ianpcook.

Want to join Ian and the rest of the Sixfold team on our mission to transform insurance underwriting with AI? Check out our career page. 

We had an opportunity to chat with Sixfold's Co-founder and COO Jane Tran about the company’s amazing first year and the vision for the years to come, as well as her career journey, giving back, and tips on running a fast-paced AI startup.

What was your first job and how did that influence your career?

My very first job ever was as a cashier at an Italian deli around the corner from my parents’ house.

I think everyone should do a service job because it emphasizes the importance of good customer service like how to treat people. I also learned how to be quick because it's New York. New Yorkers don’t like to wait for their Bacon, Egg, and Cheese.

Walk us through your career journey from the Italian deli to co-founder and COO at  Sixfold.

I’ve had a good mix of enterprise and startup experience. I started my career at JP Morgan as part of their rotational analyst program. One of my last rotations was with the Turnaround & Process Improvement team for the Chief Information Officer—that’s where I fell in love with tech. I worked on really cool projects like improving the eDiscovery process and improving data governance. I had a blast. 

After that, I spent several years at Marsh and MetLife working with the CIOs on different strategy and planning projects before I decided to give startups to go. I was on the founding team at Unqork where I was Head of Solutions before becoming COO.

When I decided to leave Unqork, I kept in contact with Alex [Schmelkin, founding team at Unqork, and co-founder of Sixfold]. When he came up with the idea for what would become Sixfold, he asked me to join him to get this idea off the ground.

What does the name Sixfold mean and who came up with it?

So, all kudos due to Alex’s daughter Nina Schmelkin for that! She was doing a project for school around patterns. A sixfold pattern is considered one of the most interesting, naturally occurring patterns—snowflakes are a sixfold pattern. And so, when it came to choosing a name for the company, we were thinking about AI and the role that patterns play, and “Sixfold” seemed like an ideal fit.

Sixfold just turned one year old. How would you describe year one?

A ton of fun! We’re building really tangible use cases using cutting-edge tech. This first year has reinforced the importance of anchoring your work in first principles. AI is obviously super hot and evolving at warp speed, but we can't ignore the things that support great software development and great user experiences. That meant getting that foundation and discipline in place while at the same time making room for extensive R&D and a ton of iterations. 

We learned a lot. We tweaked a bunch. And I think we found product market fit. Our early customers are already starting to see value, and I’m really excited to see where that grows this year.

Do you have any notable “wow” moments from the first year?

Yeah, when we delivered our first end-to-end underwriting pilots and heard the underwriters say “we were able to complete this task in a fifth of the time.” I particularly love hearing how much they trust the tool.

Hearing that first positive user feedback feels like a major achievement! And, obviously, the recent closing of our Series A funding round.

Who are your role models and how did they influence your career? 

My parents. My mom runs a small business in kitchen supplies with her siblings — it was one of those things where they just sort of fell into it. They knew they could offer a really good product and create a fit within the market. They understood what customers wanted and knew that they could manufacture it. So they just went for it. That takes a lot of bravery. On the flip side, my dad hung wallpaper for a living. He's retired now, but he had that hard work ethic and true care for his craft. He developed a reputation for excellence and really worked his way up.

I think the combination of entrepreneurship, work ethic, and quality very much influences who I am.

A common conversation for startups is balancing “the need for speed” with employee happiness. How do you build that balance into the company culture? 

Unfortunately, I don't have a magic formula. I would say that from the get-go, Sixfold’s three founders — Brian, Alex, and myself — anchored ourselves on our Mission and a handful of operating principles like putting the customer first and being direct while being kind. We try to surround ourselves with people who share those principles so that naturally becomes the culture of the company. 

The three of us really care about who works for us and how we all work together. Sometimes we may not have the best balance, but we always strive to be better. As founders, we care a lot about our work, but we also care deeply about family, friends, and life outside work. We understand that people who work with us have the same need for a balanced life outside work.

Do you have any tips when it comes to hiring?

Instinct is a huge part of it. It’s also helpful to have a great HR team in place — kudos to Marie [Sixfold’s HR Business Partner] for doing a lot of the initial groundwork, so by the time a candidate gets to me, they fit a lot of our criteria for that role. From there, a lot of it just comes down to just instinct. Ask yourself if they'll fit within the culture of this company.

Tell us about your mentoring work for different startups and organizations.

I'm on the board of directors and co-chair for an organization called Womankind. It helps survivors of gender-based violence in New York, with a focus on the AAPI community. They've been around for more than 40 years. They started with a single hotline for the NYC area, but have expanded to serve thousands of women every year across the US as one of the few true end-to-end organizations. So families get to stay together. They get legal help. They get job placement. Their kids have a safe place to be while they're figuring out, you know, the next steps. I'm really proud to be part of that organization. 

I've also mentored and advised a few other early-stage startups that I think are doing something new and interesting. This also helps me to understand what else is out there in the ecosystem. I’ve mostly been focused on B2B enterprise throughout my career, so I like learning about retail or other sectors.

I love being around people who are building interesting things. It’s super fun and it can be super informational too.

What are your top work tools that you feel like you couldn’t do without?

I don't do a lot of the things that “productivity hackers” do. I would say Apple Notes and Google Tasks are central to my workday. I keep extensive notes on my meetings— so that’s a lot of Apple notes. And then, for the important things with a deadline, I'll set up a Google task or calendar reminder. And that's how I organize.

What are you excited about for Sixfold’s second year? 

This year will be about continuing to mature our product and getting a lot of new customer use cases live.

We're working with a lot of great people and a lot of great customers. I’m looking forward to showcasing what we can do within this market and at this fidelity — a year ago, I don't think anyone would have thought that we’d be able to do what we’re doing, so I can’t wait to see what the next year or two will bring!

Want to work with Jane and the rest of the Sixfold team? Check out our career page.