Thanks for having me on the pod @nathanbarry!!

Proud to announce that Casper Studios is being acquired by Ode with Anthropic! We started Casper as a curiosity. We wanted to learn about AI and see how we can use the technology to help companies, people, and ourselves. It’s since turned into something more. Our ambition has grown. And that is why we’re being acquired by Ode! Ode is the joint venture started earlier this year with @AnthropicAI, @blackstone, Hellman and Friedman, @sequoia, and others, led by Chris Taylor and Eddie Siegel. We’ve looked up to Chris and Eddie since we started Casper. Chris and I would trade notes about AI services. I always admired their energy; they are some of the best technical folks I’ve met. We joked that we should maybe join forces at some point. Can’t believe that’s now happening. What’s the high-level thesis on the partnership? Ode is acquiring Casper to expand its ability to support clients’ AI transformation from end to end. Ode goes deep on its clients’ top AI priorities, building production-grade applications for an organization’s hardest AI challenges. Casper goes broad, helping deploy AI across teams and repeatable workflows, mainly on harnesses like Claude Chat, Code, and Cowork. Following the acquisition, Ode will be able to address more of the customer opportunity without moving away from the complex, custom work at the core of its business. Thank you so much to the Casper team, all our clients, and all the supporters in our audience who have connected us with people and helped our company reach this milestone. It feels like the constraints have now been lifted. The future is quite literally unbounded in terms of opportunity. So excited about what comes next.

I was chatting with founder today about how different our ambition for Casper Studios was when we started compared to where it is today. We started what most people would call a “lifestyle business”. It’s a dirty word but there’s wisdom behind it. Why wouldn’t you want to build a business first working back from the lifestyle you want? For us there wasn't some grand plan to build a massive company. It was more of a curiosity and desire to learn about new tech technology. Looking back, I think there's a lot of value in that. If you start small, you can always choose to get on the fast lane later. But if you start by raising a ton of money and building for hypergrowth from day one, it's a lot harder to get off the highway. You're committed to that path. You’re on a one way street before you even understand where you’re headed. As we’ve meandered on our own path we’ve built the confidence in what we’re building. The wins got a little bigger. The team got a little bigger. The clients got a little bigger. Then one day we looked around and thought, "Holy crap, there's a big opportunity here in AI services. Why don't we go for it? Let’s start thinking much bigger.” The ambition came from the work. It came from an internal motivation vs some cool external outcome we were chasing. You can still move quickly. You can still operate with the urgency of a venture-backed startup. You're just have to be more thoughtful with your decisions and where you spend money which helps you be a better founder. Very grateful about the journey we’ve been on. But yea, we’re also now changing our mindset. Ours now is maturing to build one of the most trusted organizations in AI in the world. We’ve found ourselves at the right tables to help with that. Come join us on this journey if you’re interested :)

We've worked with 10+ PE-backed funds and portfolio companies over the last 9 months. Large cap funds with $1T+ AUM down to smaller IT services roll-ups. Here are 5 trends we keep seeing, relevant if you're implementing AI at the fund or the portcos. 1. Bet on harnesses, not custom software. Harnesses like Claude Cowork and Claude Code are becoming the general-purpose front door to work: one interface wired to the data and systems behind it. Automation built around a harness is composable. Each new skill or connector stacks on what's already there. Custom software hard-codes today's process and needs rebuilding as models improve. Reserve it for genuinely specialized workflows. 2. Context is the real platform. The binding constraint is rarely the model. It's the data and operating knowledge sitting unstructured across meetings, inboxes, and disconnected systems. Converting that into structured context is a compounding investment. Each use case gets easier, faster, and cheaper because the context layer already exists. 3. Build end to end, not in silos. Left alone, each team builds locally successful tools that can't pass work to the step before or after. Connectivity is a design decision made up front, not an integration task later. Retrofitting it means reworking the underlying data structures. 4. Separate users from builders. Everyone can use AI. Far fewer can rearchitect their work with it. Asking everyone to self-build produces duplicated effort on the same surface-level problems. Users adopt tools when they exist. Builders, roughly 15-25% of a team, can genuinely redesign their own workflows. They are the leverage point. 5. Gate spend by stage, not ROI forecasts. Pre-build ROI math is false precision. You can't estimate tokens or benefits for a workflow that doesn't exist yet. Tie each use case to a business driver, fund pilots from a ring-fenced innovation budget, and define exit criteria that give finance real numbers to underwrite scale-up. If you're in the space let us know! Happy to help out with any of your own thinking here :)

We had a thought 9 months ago: PE could be a growth channel for Casper Studios. We had no relationships in the space. Today 40% of our inbound lead flow is from PE funds. That's happening through partnerships with funds over $1t AUM, but also smaller ones around $2b-$10b AUM. It's been fun to have a beginner's mind and learn from the ground up, then to hire folks on the team with that background. Here's a very basic primer on the space. What is PE? How is it different than VC? The main nuance, especially for someone who wants to partner with the funds, is that PE funds often own more of the company than a VC would. Growth equity funds take a smaller % of the company, maybe closer to a VC, but a lot of PEs usually have more ownership. That means they have more influence than many VCs in the intros they make to potential partners (e.g. us). Who do you talk to? Sometimes we work directly with a customer who ends up being backed by PE. You do a good job, then ask for an intro to their operating partner. The most beneficial path for us is when there's a senior Chief AI Officer who sits at the fund level, tasked with driving AI adoption across the entire portfolio. They work very closely with the operating partners. We then partner with a few of those operating partners to ideate around where in the portfolio is relevant to focus on first. Does that company need to sell in the next year and needs an AI transformation story? Does the nature of the work (e.g. services) lead to more opportunities generally with AI? Start there. How do you scale early success? The promise of PE as a channel: you focus on a few trusted relationships which then lead to quite a few clients. One operating partner might be focused on 5 companies. One fund could own 50-200 portfolio companies. You can see how quickly you can scale. BUT IT'S SUPER HIGH STAKES. You have no option to mess up on the client. If you do, you effectively cut off the intros to the others. You have to be confident about your offering before you build these relationships. This is amazing if it works, because the intros start flowing. It hurts if it doesn't. Why don't more tech companies do this? Growing up in the SF ecosystem, you just don't have friends or networks of people from PE. You have this weird stigma toward the industry because of the negative stories you hear in the news. I mean, tech and AI companies also don't have the best rep publicly in those east coast / midwest communities! The truth of it is that they are some of the most thoughtful and intellectually curious people I've met. Now more of the labs are seeing this too, which is why they're partnering with larger PE funds to drive adoption for their models into their port cos. We're still very early. Quite a few funds are intro-ing us to their early port cos. Now it's up to us to execute, provide value, be trusted partners, and do great work. I love that pressure, and I know the team does too.

I miss opening a document without AI there. Back in the day when I was an "organic writer". That feeling of openness, the worry you won't have anything to say, then the flow state when the words are just coming out of your fingertips. I used to write a lot better before AI. Both for my own newsletter and for work docs. I wrote a few memos during my time at LinkedIn that "went viral" internally. That led to bigger jobs, promos, etc. I want to get back there. My ideas felt more crisp. My thinking sharper. I want to start on a blank page again instead of asking AI to pull from a meeting as a starting point. There's a place for that, and in some cases I want to keep it. But writing a good memo from scratch will always stand out - even more now. I'd encourage everyone not to forget that skill. Learn it first, before relying too much on AI.

Casper Studios has been named a Select Service Partner in the @AnthropicAI Partner Program! Our team is now certified to deliver Claude for customers. This is a huge milestone for the team!! What does this mean? 1.) First, our whole team is "Claude certified". We've spent the past few months attending virtual and in person training to get up to speed on all things Claude. This is a whole new service area. How do you set up Claude? How do you think about Skills? What about how to drive usage of those skills. Lots of great content that the team shared with us to get up to speed. 2.) Second, we have an amazing team to work with on the Anthropic side. Our POCs have been Jeremy Maranitch and Apricot Tang, who have been awesome about sharing best practices, ecosystem insights, etc. 3.) We can bring their team in to support our clients and they can bring us into their clients to help implement Claude (change management, governance, and more). We're very bullish on this ecosystem. Super excited about what is next :)

Had a SVP of a $300m PE backed port co say last week "we're thinking of buying Claude/Codex, but don't want to until we have the right partner to help implement". Think we'll see more of this. Just because you bought Claude doesn't mean your team will use it. Enterprise Claude (or Codex) is just the starting point. To get value, companies need training, education, and concrete examples of how AI changes the way people do their jobs. Without that the rollout becomes another tool launch: power users get ahead, skeptics don't care, and leadership has no visibility into what's happening across the company. We're finding a growing niche of our work is helping companies make better use of the enterprise Claude subscriptions they bought, or are thinking of buying. LMK if you need help :)

Hearing the same

Had a mid-cap fund ask me: "If we introduced you to 100 portfolio companies tomorrow, how would you handle it?" After I stopped sweating and took a few deep breaths, here's what one part of what I shared (can’t share all the secrets yet haha): Do what Aaron is saying. Start educating and training at the undergrad and grad level on these skills. The jobs are going to be plentiful over the next few years. I'd also partner directly with governments (especially outside the US) to help them train their people to do this work too. Then work with companies to hire those folks. The appetite to train their people, especially with the jobs in the country that may be disrupted with AI (eg call centers, BPOs, etc), is high. We're already in conversations with a few government bodies globally on this, particularly in places where we already have strong base of talent. The value exchange is: we help you figure out what to train your people on, and a portion of those people we can help match to the right jobs - whether with us or with other firms scaling their hiring. Talent is the bottle neck right now. Ironic since the narrative is that the jobs are all going away. At least right now some may be but others are growing a lot.

Over the past few months, I’ve spoken with 5+ PE funds and their operating partners. One recommendation keeps coming up: build a shared library of AI skills that can be deployed across the portfolio. Most services portcos need SOW generation. Finance teams need AP invoice automation and data agents that can run SQL on internal databases. Engineering teams need security agents that can review code before release. Every company is unique, yes, but their problems may not be. The playbook is: implement agents at one portfolio company, learn from it, then templatize it and roll it out across similar companies. The goal is a skill that is 70% reusable and 30% customizable. That creates a middle ground between “rolling out a platform” and doing everything bespoke. If you try to push an AI platform across the portfolio the way firms have done with Salesforce in the past, I don’t think that’s the right move. You want the benefits of a platform: consistency, templates, and easier implementation, without the lock-in: slower iteration, less tailored products, and too much dependence on one system. Right now, I think skill files and workflows that live in an independent repo, like GitHub, are the best way to do that. They give you the repeatability of a platform without forcing every company into the same rigid software product. This is still early. Most funds haven’t operationalized it yet, and many portfolio companies are still behind on AI implementation. DM me if you want to chat about what else we're learning.

Private Equity and AI implementation is having a moment right now. Both OpenAI and Anthropic are pushing hard to partner with PE firms to deploy their models into portfolio companies and drive enterprise AI adoption. OpenAI is in advanced talks with Advent, Bain Capital, Brookfield, and TPG on a JV; Anthropic is running a parallel play with Blackstone, Permira, and Hellman & Friedman. Both are modeled on Palantir's forward-deployed playbook — teams embedded in portfolio companies. Those are hundreds if not thousands companies in scope. Both labs are pushing hard because they're each targeting IPOs this year. Nailing this story matters for investors. We've been getting connected to these firms over the past few quarters. We've been building the relationships for a while but most funds were still exploring slowly. It's all coming to a head now: they're finally ready to connect us to their portfolio companies, and I think the OpenAI/Anthropic partnership moves are a big part of why. We're hiring across: -Strategy folks to do discovery work up front -PMs to implement AI across portfolio companies -BD / Sales folks to help me manage relationships and find value across the portfolio If you have any interest in deploying AI into PE, now is the time to jump in. Let me know if you want to go after this together.

Was talking with a friend at a large VC fund + a customer at another an asset manager today. Went into the Thoma Bravo and Medallia news from yesterday. Sharing notes / the "so what" below. TL;DR -Thoma Bravo handed Medallia to its lenders. $5.1B of equity, gone. -Thoma Bravo bought Medallia in 2021 for $6.4B. About $3.4B of equity, $3B of debt. Five years later the company couldn't service its debt. Lenders (Blackstone, KKR, Apollo, Antares) took the company in a "debt-for-equity" swap. Thoma Bravo's equity went to zero. Three things broke at once 1.) Rates. Medallia's debt was "floating rate". In 2021 the all-in rate was around 4.5%. Interest expense was $135M a year. As rates rose, that bill more than doubled to $278M. An extra $143M each year w/o that big of a change in revenue. 2.) Multiples. Software businesses like Medallia traded at 15-20x EBITDA in 2021. Today they trade at 8-12x (maybe even less). Even with flat EBITDA, enterprise value compresses 30-40% from multiple contraction alone. 3.) AI. Medallia's core offering is customer experience. Collect survey and feedback data across every touchpoint (web, call center, email, in-store), run text analytics on the unstructured stuff, build dashboards for ops and CX leaders, feed it back into workflows. That used to be a moat. You needed the survey infrastructure, the NLP models, the integrations, the enterprise sales motion. Hard to replicate. AI-native versions do most of this better. An agent can read every call transcript, every support ticket, every review, every chat in real time. No traditional survey needed. Any one of these alone may have been okay. Together they create the zero. The more interesting point from PE land. PE firms can't control rates. They can't control multiples. The only variable they control is EBITDA. And in a world where AI is both the biggest threat to SaaS moats and the biggest lever for EBITDA improvement, the firms that figure out AI inside their portfolios will have very different outcomes than the firms that don't. How we're thinking about it at Casper Studios is shifting too. I'm for sure biased but I see this as a tailwind for the business. We're working with a few large-cap PE portfolio companies right now. The work is interesting and intense (!). There's a ton of pressure to drive EBITDA improvement fast, to get to a better multiple and a better story. Some are moving fast. Some aren't. It's been fascinating to be in the middle of it. I can't share much more than that, but this is the most top-of-mind conversation I'm having right now. A few months ago I wouldn't have said you're late. Today, at a minimum, this should be a topic in every exec meeting. The next few years of PE (and funds, and private credit) are going to be interesting. DM me if I can share any insights we're picking up in the space.

"There's a limit to the number of software you need to build that looks like an app on your phone; there's an unlimited amount of software you need to build that looks like a background system process that's connecting different data sources, automating workflows. That's where the work is going to go." - @levie We've shifted from using our coding agents to build software to mostly using them to build other agents. Claude has made this easier, and form factors like MD files and skills have accelerated it. I don't think the total number of web and mobile apps necessarily declines - it likely keeps growing. But the relative growth of agents embedded in internal workflows will probably be something like 10x what we have today, simply because building them has become much easier. Apps aren't going away; they'll just look small, relative to the internal agent market forming around them.

sometimes the contract also has a 30 day terms of convenience too 😂

Have you noticed the paradox in the job market? Every good company in AI is complaining about not finding enough people to service demand. On the other side, tech companies are laying off thousands. What’s going on? The people are there to help implement AI. The system to train them doesn’t exist yet. There are experienced professionals across every industry whose roles are shrinking. Not because they lack talent, it’s because the work itself is changing faster than anyone can redeploy them. At the same time every company we talk to is desperate for people who can implement AI. Demand is so far ahead of supply that clients are getting back-ordered; especially for AI services firms like us. But I think gap between these two groups is way smaller than people think. Someone who’s sharp, moves fast, open minded and knows how to figure things out in ambiguous environments, that person can be deploying AI in weeks/months if you put them in the right system. They just need to be shown the way. And honestly? That’s a skill issue on us. The companies building in AI. We’re the ones posting JDs asking for years of experience in Claude Code even though that barely existed a year ago LOL. The companies that can hire top talent, equip them on how to use AI, then deploy them to companies who need AI, will be massive companies.

We’re almost 30 people now. I find myself stepping back a lot just observing the quality of talent we’ve built at Casper. I joke that I probably wouldn’t even get hired here anymore lol. Entrepreneurship is a vehicle for incredible experiences. Building a team has been the most rewarding part so far.

building of these if you wanna jam @thesamparr :)