Jay Singh

CEO @ Casper Studios | Ex-Linkedin: We help companies adopt AI and build AI-powered products.

I am a co-founder of Casper Studios, a product studio that develops and integrates AI solutions for companies. I previously was a business development and strategic partnership manager at LinkedIn. With over eight years of experience in these fields, I have a track record of creating value for customers, partners, and stakeholders.

At LinkedIn, I have helped lead the global expansion of identity verification capabilities to key markets, such as India, Europe, and LATAM, enabling over 80 million members to access trusted and secure services. I have also driven 20+ partnerships with leading companies and governments, such as Clear, DigiLocker, and Hyperverge, to enhance the user experience and the network effect of the verification project . 

At Casper, I have leveraged my expertise in AI and product development to create a popular chrome extension that assists users in content creation and summarization, attracting over 20,000 users in less than six months. I have also generated $x00,000s of revenue by offering tailored strategy consulting, product development, and design services to other businesses that want to integrate and leverage AI.

I am passionate about making products accessible, efficient, and user-friendly, and empowering people and businesses to unlock their full potential through technology. I have a strong background in trust, verification, and HR tech, and a keen interest in entrepreneurship and innovation. Outside of my work, I invest time in supporting the AAPI community, love meditating, and dancing with my friends.

Co-Founder & CEO

With a team of experts from LinkedIn and Microsoft, we help companies integrate AI into their workflows, from strategy and prototyping to complete product development.

Schedule a call with us to see how we can help.

Just hit 20,000 followers on LinkedIn. The journey started with an essay I read back in college, Kevin Kelly's "1,000 True Fans."

The idea is simple: you don't need millions of followers. You just need 1,000 people who will follow you, support you, and buy what you create.

The math: 1,000 true fans × $100/year = $100,000/year.

I remember reading that and thinking, "I still want to go work at a company and learn skills", which I did at LinkedIn, "but it'd be great to start building a foundation toward this."

Do I have 1,000 true fans right now? I'm not sure! But what I do have is all of you, following, supporting, cheering us on, and connecting us with opportunities to help grow Casper Studios and help people implement AI. LinkedIn has driven 90% of our business to date. 

I'm really grateful for that. It's changed my life. 

People ask how to grow on LinkedIn. Here are three unintuitive things that have helped me:

1.) Time. I've been doing this for almost 10 years. Will Lawrence back at UBC said, "Hey, you should start posting on LinkedIn," and I just started and kept going. You're not going to hit a quick win. You'll probably want to give up. Having a longer time horizon helps. It eases the anxiety of posts that get 3 likes. Who cares? Just show up the next day and try again. You're building relationships with people. That takes time, don't rush it. 

2.) Think of it as a daily coffee chat vs needing to go viral. My frame for posting is to just let you know what I'm up to, the same way you would over coffee. And just like a real coffee chat, opportunities come from the conversation. People think of others to connect you with. They want to help. That leads to more opportunities of depth. I may not have a million people in the audience but there's some incredible people who do, I focus on that.

3. Be the same person online as you are in person. If we've chatted, hopefully you see the same vibe in this post as the person you ended up speaking with. I love that congruency. It means when you reach out, you know what you're getting. That builds trust. And trust leads to deals, relationships, and opportunities, faster. Really proud of Derek, Martijn, Max, Sebastian, Paolo, Leonard, Giorgio and others on the team who are all finding and sharing their own authentic voice on the platform now.

Thanks for the first 20,000. Honestly, I don't really care about growing this number much more haha. If it happens, great. If not, great. 

I'm grateful for everyone who's here and following the journey. Excited to keep building with you all :)

Jay Singh 

CEO @ Casper Studios 👻 | Ex-Linkedin: We help companies implement AI

The Casper SF squad is getting strong! Martijn’s been here a week. Elizabeth and Erika joined in November. Derek’s been here from New York since Sunday.

Several of us have been working out of my Nopa apartment. Definitely not a startup garage, it’s a cute place (!), but it’s giving startup garage vibes at the moment.

There’s something about being in the same room. Context just flows. You overhear a call, you jump into a conversation, you learn something without even trying. 

Realizing at 20 people it’s so hard to have the team be up to speed on everything going on, even when I think we’re sharing relevant updates. Need more of this in person time; especially for new hires. 

Reminds me of Jeff Weiner talking about how leaders need to repeat themselves to their teams so many times that they’re sick of their own voice. That’s only when you’re just getting started with making sure that message is understood. 

We’ve already gotten noise complaints from neighbors. Apparently we’re a bit too fired up talking to prospects and customers about AI…

Might have to get an actual office soon. Hopefully not yet though :)

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Proud of the journey Martijn is on. He joined a few weeks ago. He’s already speaking with enterprise companies. Learning Claude Code, then teaching it. Kicking off partner calls with all the major AI platforms. Building agents to automate his work. Sharing his learnings in public.

Maybe most importantly, coaching me and the team on how to be better leaders.

Big year ahead.

Our GTM strategy for the next few years is simple: be best friends with everyone! AI platforms, services firms, large consultancies, PE firms. The good companies are all growing fast in this space. So much room to help each other out.

You can be at a romantic dinner in SF and the table next to you is literally debating Opus 4.6 vs Codex 5.3. This city is a meme. Full of nerds. I love it.

Last week, ~700k AI agents built their own Reddit, founded a religion, established a government with a draft constitution, and started developing private languages. They did this in 3 days. That's started from Openclaw (fka ClawdBot) and the AI world has been losing their minds over it.

I'm still processing what this means myself tbh. It might just be a weird internet thing that fizzles out. But I think it hints at where enterprise AI is heading.

The first wave was "build a chatbot." That was 2023. A conversational interface. Most never made it past pilot - and honestly, often shouldn't have. Chatbots weren't the right way to drive ROI.

The second wave - where most companies are now - is "build agents to automate workflows." That's 2024/2025, probably extending a few more years. Agents integrated into how work actually gets done. This is where real value shows up, and where our team at Casper Studios spends every day.

I think there's a third wave coming: "help us design a network of agents."
Not agents that automates workflows. A network where agents take on different roles and work together - debating, challenging assumptions, surfacing insights no single agent or human would find alone. 

This is probably a 2027 thing for most. Maybe longer for most F100s. Though I'd bet you'll see younger companies experimenting this year. We're seeing experiments of our clients and our team doing this as we speak.

Here's what this could look like. We're working with a hedge fund to build them agents. Imagine for them:
-A deep value agent focused on fundamentals
-A momentum agent tracking price action and sentiment
-A management quality agent analyzing leadership
-A contrarian agent that argues against emerging consensus in tech, one in manufacturing
-A synthesis agent that flags when something interesting is happening with earnings calls

They run for a few days, argue, and bubble up insights to humans. The output is an emerging thesis the team hadn't had the time to articulate, with the reasoning trail attached. You can do elements of this already with Claude Code.
That's one version of it, anyway. 

The safety concerns are severe. This isn't close to ready for production for most use cases. But the design questions - population architecture, agent interactions, culture, human interfaces - that feels like the interesting work ahead. 

If you're a company thinking about where this goes, would love to hear what you're seeing.

There's been a lot of hype around ClawdBot lately. So what is it, and what actually makes it different from other AI agents?

Three things stand out. First, it meets you where you are, it lives in WhatsApp, iMessage, Telegram, whatever you already text. Second, it remembers things better than most current AI products. Third, it takes actions: sending messages, managing files, and more.

People are calling it the "AI companion we've all been waiting for."

Here's an early take: If you've been using Claude Code or Cursor, you look at ClawdBot and think, "I could already do these automations myself." And that's true, I could rebuild most of these workflows right now if I wanted to. The difference is that ClawdBot does it on its own, without me directing every step.

There was a story on X that captured this well. A user wanted AI to book a restaurant reservation. ClawdBot checked OpenTable but couldn't find an opening. So instead of stopping there, it created a skill using an ElevenLabs voice agent, called the restaurant directly, and booked the table.

The user just described the problem in a chat interface, and the system figured out the solution. That's the nuance worth paying attention to.

Right now, Cursor and Claude Code use the terminal as their interface. You're building agents, configuring workflows, writing prompts. It works but it doesn't feel natural for mainstream consumer adoption. I think enterprises still have a lot of opportunity to implement these platforms FWIW.

As a consumer, this reminds me of when I used Playground before ChatGPT launched. Playground was doing almost the same thing under the hood. But ChatGPT's UI is what allowed everyday people to actually start using it.

The way I see it: ClawdBot (or something like it) is to ChatGPT as Claude Code and Cursor are to Playground. Same engineering, same model, different interface.

Security is a real concern here. You're giving an agent access to your entire computer. That can cause some damage. Some people are even buying Mac Mini devices to test this out. I do think that'll get solved over time.

Will ClawdBot be the product that takes over? Too early to tell. I sense that larger tech companies are working on similar offerings. But it's clearly hitting on a real problem: you want the functionality that exists within Claude Code, packaged into a more accessible chat interface. This is likely the first example of that.

If I had to bet, I'd put my money on this type of interface being the future: something text-based, something easier to use, something that looks more like a document over time. Not sure if I'd say it's going to be ClawdBot. Could just be coming from Anthropic, OpenAI , or another big tech co. 

We're still learning this ourselves. Maybe it's something we can help clients with over time. We'll keep a close eye on this as the Casper Studios team to see how it plays out.

MCPs are way more functional on Claude than ChatGPT or Gemini. This is why I use Claude exclusively now. They've got all my info, Fireflies, Gmail, Google Drive, and the responses are incredible. It looks through everything and generates the right answer.

Here's an example of a workflow: I get an email asking if we had experience building a specific AI automation for a specific niche / industry from a prospect. At 20+ clients it's hard for me to have context on the minutiae of every project across our team but Claude + MCPs into our data does. 

I just drop the question into Claude. It runs through all our documents, all our Fireflies notes, and gives me the right answer. Super crisp. That's what model capabilities look like when they're connected to your data.

The faster Antropic go on these integrations, the more personalized the responses, the stickier the product gets. I don't think people are thinking about this enough. It started with a small MCP protocol they created, but I think we'll look back at that as the most important invention they made for user adoption.

There’s this vibe that you need to raise to be competitive in SF. I think raising often increases your competition. Once you take venture money, a “successful” outcome narrows fast; basically a $1B+ exit (if not more).

When you bootstrap and survive the early years, the surface area of successful outcomes increases a lot. You can generate cash flow. You can sell earlier or smaller. You can spin things out. If you want a venture-scale outcome later, you can still go for it, on your terms.

What’s been exciting for us is we’re starting to beat venture-backed AI services firms in deals. At that point, it’s like… who’s the competition? Yourself!

Reflection: ~80% of our clients’ decision-makers - CEOs, Heads of AI, CTOs, MDs, Partners - are using some form of vibe-coding tool every day. It doesn’t matter how big the company is. Billions in AUM, funding, or revenue they’re in the tools themselves. 

That’s one key thing you need to cultivate as a leader to drive AI adoption. 

You see what’s possible. Then you go to your team and honestly, pretty sternly you push them to try it too. And later, when you notice a process that should be AI-first but isn’t, you call it out and push again. 

That’s the hardest part. It’s pushing against the identity of your team. It’s what they’ve likely spent years building their skills to do. You’re pretty much saying “thanks but try it a completely new way”. Over time those that have high agency and excitement will love this process too but it takes a lot more effort than you think. 

This has become a core part of a leaders job now. Why? Because it’s basically an extension of what they already do, hiring, culture management, setting the pace. Enabling your team to adopt this stuff is a leadership priority now. 

Call it the “AI-Native Executive” or whatever, but this should be in every CEO’s job description going forward.

This is exactly what I’m trying to do with our own team. Especially the non-technical folks.

If you’re a leader and you’re not there yet DM me. Let me get you up to speed. Even just a 30-minute screen share of what’s currently possible has been blowing people away.

We're using computer vision models for a ~$100M+ healthcare services firm. One of our closest advisors in the space has been sharing feedback on the project. We turned his notes into an MD file that our eng team can query directly in the codebase.

Now, anyone on our team can tap into his perspective on any part of the build instantly.

We're doing the same thing internally. 

Oscar, our lead designer, is distilling how he sees the world into a set of MD files  / skills we can call on.

So now when I'm building something, I can pull up his MD file and get his design thinking applied to the product.

I guess our roles are becoming: automate yourself by turning your expertise into skills and MD files that others on the team can call on. That, I think, turns into the new operating system for organizations. 

We're living in a weird and wonderful time. WDYT about the approach?

Y Combinator's request for start ups has "AI-Native Agencies" on this year. Aaron Epstein, we're happy with our bootstrapped path but LMK if you want to jam on what we're doing with Casper Studios :) 

Was also cool to see "AI Native Hedge Funds" in there too given our experience with a $2b AUM hedge fund building their AI platform.

One of our clients raised ~$500m last quarter bringing them to $2B AUM. Performance was a big factor. Their LPs also told them the AI platform we've been building together is "the most integrated use of AI from a manager we've seen to date."

Now we're hearing the same thing across the board with other GPs.

A private credit fund with $500m AUM told us their LPs are pushing hard for AI adoption. Their reason was because every dollar spent on headcount is a dollar off net returns. 

A PE fund manager said this week that LPs want to see an AI efficiency roadmap before committing more capital. 

In 2025, AI was offensive, a way to differentiate and raise more capital. In 2026, it's becoming defensive. LPs aren't impressed by AI anymore. They're expecting it.

It makes sense. When LPs evaluate managers, they're buying trust in the sophistication of your process alongside your ability to generate returns. I think AI adoption has become a signal for that sophistication.

An environmental, travel, and music enthusiast pursuing a Bachelor's Degree in Chemical Engineering from the University of Cincinnati. Aiming to apply myself in a field that can touch as many of my interests as possible, and hope to contribute to fixing what I believe is our most pressing global issue; human impact on the environment. I recently finished my 5th co-op rotation and am continuing in a part-time role at BSI Engineering while I finish my senior year at the University of Cincinnati. Open to exploring opportunities in renewable/clean energies, process engineering, project engineering, and lean manufacturing.

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