Invest Like the Best with Patrick O'Shaughnessy
Tom Digan & Greg Stewart - Building the World’s Best Fitness App - [Invest Like the Best, EP.454]
13 Jan 2026
Chapter 1: What is the main topic discussed in this episode?
Here's an interesting question to think about. If your finance team suddenly had an extra week every month, what would you have them work on? Most CFOs don't know because their finance teams are grinding it out on lost expense reports, invoice coding, and tracking down receipts until the last possible minute. That's exactly the problem that Ramp set out to solve.
Looking at the parts of finance, everyone quietly hates and asking why are humans doing any of this?
Chapter 2: What is the backstory behind Ladder's founding?
Turns out they don't need to. Ramp's AI handles 85% of expense reviews automatically with 99% accuracy. which means your finance team stops being the department that processes stuff and starts being the team that thinks about stuff. Here's the real shift. Companies using ramp aren't just saving time, they're reallocating it.
While competitors spend two weeks closing their books, you're already planning next quarter. While they're cleaning up spreadsheets, you're thinking about new pricing strategy, new markets, and where the next dollar of ROI comes from. That difference compounds.
Go to ramp.com slash invest to try ramp and see how much leverage your team gains when the work you have to do stops getting in the way of the work that you want to do. Investing is hard. It's an apprenticeship industry with messy data, complicated workflows, and decisions that demand judgment.
Chapter 3: How did Ladder navigate its darkest moments?
Investing needs specialized AI, and that's why I'm so excited about Rogo. Rogo is an AI platform purpose-built for Wall Street, not a generic chatbot, but a suite of agents designed around how bankers and investors actually work, from sourcing, diligence, and modeling, to turning analysis into deliverables. Finance requires deep domain expertise far beyond your average chatbot.
As listeners of this podcast know, every investment firm is unique, with its own thesis, internal notes, templates, and ways of investing. Generic AI can be impressive, but it doesn't actually understand your process, and that's where the advantage lives. For me, three things set Rogo apart. One, it connects directly to your system, so it can work with your actual data, internal and external.
Two, it understands your workflows, how work really happens across a deal or an investment. And three, it runs end-to-end and produces real outputs in the way that your best people do. Auditable spreadsheets, investment memos, diligence materials, and slide decks that match your standards. Rogo is built by a deeply technical AI team with real finance DNA.
Large language models for finance professionals by finance professionals. I'm fully bought into that vision, and I think their work will fundamentally reshape investing. Learn more at rogo.ai slash invest. If you're a longtime listener of this show, you've heard the same pattern play out across so many great companies.
Chapter 4: What strategies helped Ladder find product-market fit?
The moment a product finds early traction, the constraints shift from engineering curiosity to enterprise execution. And one of the biggest hurdles, whether you're OpenAI, Cursor, Perplexity, Vercel, or a brand new startup is identity and access. SSO, SCIM, RBAC, audit logs, these are the capabilities that give enterprises the confidence to adopt your product at scale.
That's where WorkOS comes in. It's become the default way fast-growing software companies get enterprise-ready. Instead of spending months building SSO or provisioning or permissions in-house, WorkOS gives you all the core features enterprises require through clean, modern APIs. And in the era of AI, this matters more than ever.
AI-native companies scale faster than anything we saw in classic SaaS. They can't afford to wait on enterprise compliance. They need it on day zero. That's why so many of the top AI teams you hear about already run on WorkOS. If you're building software and want to unlock larger customers or just avoid reinventing a very unglamorous wheel, head to WorkOS.com.
Chapter 5: How did Ladder build a successful TikTok growth engine?
It's the fastest way to become enterprise-ready and stay focused on what actually moves the needle your product. Visit WorkOS.com to get started. Hello and welcome, everyone. I'm Patrick O'Shaughnessy, and this is Invest Like the Best. This show is an open-ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money.
If you enjoy these conversations and want to go deeper, check out Colossus, our quarterly publication with in-depth profiles of the people shaping business and investing. You can find Colossus along with all of our podcasts at colossus.com.
We'll be right back.
Ladder was my first angel investment ever. It was made entirely on trust in Tom Deegan at a point when I had no idea what I was doing in venture capital. What followed over the next seven years is one of the most unlikely and dramatic business stories that I've been a part of. Today, Ladder is the number one strength training app.
They're approaching $100 million in ARR and more than 300,000 paying members. But the path from near death to dominant fitness app involved debt collectors, leadership changes, and a full reset during the pandemic pivot.
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Chapter 6: What lessons were learned from customer feedback?
At one point, Greg Stewart entered what he calls a cave process, where a huge amount of effort and time went into cracking the TikTok algorithm just to make sure from content work as a growth engine.
Chapter 7: How is AI influencing Ladder's future plans?
Tom and Greg built Ladder by being relentlessly empirical about their customers, ruthless about prioritization, raising whatever amount of money they could from any investor, and willing to do whatever it took when most founders would have quit.
In this conversation, we cover the messy early years when survival meant negotiating creditors at 20 cents on the dollar, how they figured out their customer by reading thousands of app store reviews, and how they built the TikTok growth engine without any performance marketing background.
Tom and Greg share their long-term vision for becoming the system of record for health and fitness, their approach to AI, and why they still have no managers on a 30-person team. This is a conversation about how hard it is to really build something valuable, told by two people who lived through every part of it. Please enjoy.
Ladder was the first ever angel investment that I made, which effectively was a bet on Tom. This was before I had any idea what I was doing in private markets. And I've learned a lot from watching you guys build over the years.
The story is fairly amazing and unlikely and dramatic, which is why I'm excited to do this with you guys to tell the story of the business that you've built so far and where it might go. The idea, I think, for our conversation today is to show people how incredibly hard it is to build something that ends up being very valuable and the twists and turns that happen along the way.
It's amazing that you've ended where you are, but I find it all the more interesting how you got here.
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Chapter 8: What challenges did Ladder face in fundraising?
And of course, we'll also talk about where you're going. Maybe to begin, since not everyone will know what the business is, just literally describe what the actual product and business is. And then I want to tell the real dirty version of the story of how you got here.
Ladder is the number one app for strength training. We've built a system that's designed to make it as easy as possible to maintain a consistent routine. We spend a lot of time thinking about personal training, arguably the most reliable way to get to the results that you're looking for as hiring coach, unattainable for most, inaccessible for most.
But personal training, if you think about how it breaks down to programming, coaching, and accountability. Programming, you know exactly what to do. Someone prepared it for you. There's no guesswork. There's no thinking. Coaching, you have an expert there to guide you, answer your questions. And accountability, you have a coach standing in front of you. You don't want to piss off your coach.
He's a really powerful motivator. Then we took those three pillars and designed an experience from ground up to get as close as possible to that experience.
How has it been so successful? Because I feel like this is almost a Silicon Valley meme. You have a fitness app, like there's 4,000 million fitness apps. To what would you attribute the fact that this one is the one that seems to have come to dominate in a sea of competition?
It's going to sound simple, but it's understanding your customers, being an engineering first business. If you look at most companies in our space, they're started by creators and they're good products. They're good companies, but the creator is the face of that business. They make every decision and they don't have a DNA that's rooted in engineering and problem solving.
And when you look at these apps, they're mostly just content libraries and the motion is just constantly creating more and more content. But what we saw was nobody was spending time thinking about how to use these incredible levers to deliver an experience that actually increases the odds of you continuing on.
We looked at apps like social networks and we looked at Duolingo, all these apps that were using all these powerful motivational mechanics and pointing them at an action for social media networks and selling your attention. For Duolingo, it's learning a language.
And so we took that mentality of how do we use software to create an experience that's totally different than what exists today that isn't reliant on a never-ending content machine. And it's been guided by our members. We spend more time than you could imagine just speaking to our members, dissecting exactly what we should focus on based on what they care about.
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