jaysingh

Thanks for having me on the pod @nathanbarry!!

@signulll This team is great - landfallip.com

i know everyone is building ai software but is there anyone opening up an ai native law firm? like built from the ground up, every service, every area is a person or two empowered by custom built software.

Hi @AnthropicAI team - Jay here from of Casper Studios. Consider this my not-so-subtle application to become one of your partners. Who are we? Casper Studios is a ~25-person AI services firm. Our core team blends product, strategy, and engineering experience from top-tier consulting firms and industry-leading technology companies including LinkedIn, PwC Strategy&, Amazon, Accenture, Bain, and Elliott Management Who we work with: -Hedge funds managing $2B+ in AUM -A $10B ARR+ revenue healthcare provider -Financial services firms with $20B+ AUM -Oh and Netflix, where we helped ship what became the second-largest voice AI activation to date with 400k+ calls So what: We’re growing 25%+ month over month with a team of technical leads and product strategists focused on implementation. And across almost every enterprise client we work with, we’re already recommending and deploying Anthropic and Claude. So in many ways this partnership is already happening :) DM me - let us support! Also for friends reading this if you know anyone at Anthropic comment them below hehe

@scottbelsky I wonder how we can layer in more unique design into these images moving forward

absolutely wild how helpful NotebookLM is in taking a draft essay of your perspective (in this case a builder’s perspective on macro narrative ahead) and posing a mind map of how to think about it. good example of AI making us smarter.

Preach - @nathanbarry is a huge inspo. Not included below is how kind he is!

Chatted with 5+ PE funds this week. I think some of them that want AI implemented across their fund/portfolios may decide it’s easier to buy that business rather than hire it repeatedly. Let me explain... Right now it still feels early. Most funds are exploring. Portfolio companies have bought tools, but very little has actually been implemented across the organization. Those I’m speaking with all seem slightly unclear where to begin, what to prioritize, which portfolio companies to focus on first, and what the right timeline for implementation should be. We're starting to partner with many of these funds to help them to answer these questions. Here's a scenario that came to mind... Imagine acquiring an AI services firm at 6–10× EBITDA. The firm keeps operating normally, selling to external clients and growing through its own GTM channels. But the PE fund now has access to implementation capacity. When portfolio companies start AI projects, the firm gets introduced as a potential partner. Even if only a few portfolio companies become customers, it creates a baseline layer of demand while the firm continues to grow independently in the market. The costs that would otherwise leave the portfolio would be retained. If AI deployment improves EBITDA across even a few portfolio companies, the return on the acquisition can exceed the purchase price of the services firm itself. When we worked on the Netflix project with Omnicom, they were thinking about it the same way. Omnicom had previously acquired a technology agency to build internal capacity for technical development, so they could support more complex builds directly for their clients. From the fund’s perspective, the acquisition becomes two things at once: 1.) an operating capability that can help portfolio companies (and the fund) move faster on AI 2.) a standalone services business that continues compounding Whether this becomes a common strategy, still unclear. I'm also honestly learning more about this space myself. Challenge my POV pls! What do you think?

one is too light

You've bought a bajillion AI tools. Some work. Most don't work well together. Now you're sitting on a stack of point solutions. Each solves one narrow problem but creates a new coordination problem every time you add another. The next few months? Consolidation. Right now, all roads lead to Claude (Chat, Cowork, Code). Let me explain. Product designers have this concept called the Double Diamond. Start at a single point. Expand outward, explore the full problem space. Converge back to a focused insight. Expand again into solutions. Converge on the real answer. It's a framework for how complexity works - you start simple, things get messy, then they consolidate. Over and over. Platforms follow the same pattern. Craigslist had everything in one place. Jobs, apartments, dating, rides, furniture. All on one ugly beautiful website. Then each category unbundled into its own billion-dollar company. Airbnb took rentals. Uber took rides. Tinder took dating. LinkedIn took jobs. One platform became dozens of specialized ones. That's the first expansion. Over time, those companies get huge and split apart again. AI is in the same motion. Two years ago every company started at the same point: "I need AI." That turned into a spending spree. A writing tool here. A coding copilot there. Legal AI. Sales chatbots. Meeting summarizers. Healthcare AI. Fraud detection. Supply chain optimization. Image generation. Customer service automation. Workflow tools. So many tools. That's where we've been. The widest point of the diamond. Now the conversation is shifting. Especially with F100s. They don't need more tools. They need help converging. Redesigning systems. Taking those early bets and building an ecosystem that actually works together. Where it goes after that is the next diamond. Nobody knows how wide it opens. But sitting across 20+ engagements right now, the pattern is clear: the value isn't the tool anymore. It's how the system is designed. That's why we don't care which AI tool you use. We care about designing the system that makes it all work. This is where the work lives for the next 12 months. It's hard. It's change management. It requires hand-holding, time in person, trusted relationships. We're here for all of it.

I'm starting to realize that 4-5 key people will change the trajectory of your entire career or business. Some archetypes this can look like: - A fantastic boss/manager - A champion at a first customer that opens doors for you - A colleague that vouches for you to get a job that's out of your league - A mentor that gives you honest feedback of your current business and what you need to change Finding those 4-5 people is way more important than being popular, having followers, etc. Find whatever spaces that will have the highest likelihood of those 4-5 people being there.

One of my best engineers just showed me how to set up OpenClaw securely & without a Mac Mini. Here's his step-by-step: 1) Spin up a VPS on Hetzner It's a virtual server in the cloud. basically a computer you rent for $5-10/month. Pick 8GB RAM, Ubuntu, US East. Takes 2 minutes. 2) Install @Tailscale This makes your server invisible to the public internet. Think of it like moving from a house on Google Maps into a gated community where only your devices can get in. Without this, bots start attacking your server within seconds of it going live. 3) Harden the server SSH keys only. Firewall. Intrusion prevention. Auto security updates. CJ actually uses AI to red team his own servers. Tells it to try and break in, then patches whatever it finds. 4) Install @openclaw and run the onboarding. You pick your model provider, connect Telegram via BotFather, and configure hooks that give your agent long-term memory. The hooks auto-save sessions and context so the agent gets smarter over time. 5) Set up the gateway This is the piece that makes it actually powerful. It's a message bus that lets your main agent talk to sub-agents, receive messages from Telegram/Discord/Slack, and orchestrate everything. this is what keeps it running 24/7. 6) Hatch your claw and start training it Dump as much info about yourself as possible. tell it your preferences, your workflows, your tools. CJ's agent monitors his email, Slack, and manages his to-do list autonomously. Watch the video for the full break-down & follow @seejayhess for more AI engineering sauce.

The main insight on how we already working with large F1000s? We're getting procured through their consulting firm of record; the one that’s been working with them for 10+ years. We join their team, and they deploy us to their larger clients. This helps in several ways. We can move faster to provide value to clients. We can also provide value to the consulting or agency of record by teaching them how to use AI faster. And then when the trust is high, we can cross-sell into other clients they have in their portfolio. This is where the BD and partnership chops really come in handy. It’s also why I don’t really think, at least today, anyone is a “competitor.” Show me a competitor and I’ll tell you how we can support each other and grow both of our businesses. Our GTM strategy for the next 2-3 years is literally to be best friends with everyone.

Great article from @GergelyOrosz. Below is an excerpt from a convo with the CTO of Atlassian on how he had to go buy his own laptop just to play around with new AI tools! That’s kind of wild. If even senior leaders have to jump through hoops from their own IT teams to experiment, something’s off. Big companies need a different procurement mode otherwise they won’t move fast enough to adopt these tools

a quick trip in Costa Rica. I’ve been noodling on a piece of short fiction set in SF, 2035. Sharing early thoughts - curious to get your feedback. The premise: What happens when we finally learn to quiet the voice in our heads (the anxious one, the 3am one, the one Buddhism, meditation and therapy spent millennia trying to quiet) and then replace it with a “better” AI one? The story follows a guy named Jay (lol) through a single Tuesday. Morning coffee chosen for him based on his cortisol levels and sleep scores. Work meetings where both sides are being coached in real time by their AI. A bike ride over the Golden Gate where the product schedules 90 seconds of silence at the exact moment the ocean view hits. Because it knows that view will move him. The tension is a mix of utopia and dystopia. That’s what makes this and life generally more interesting to me; especially when our world is so black or white. The AI makes his life better by every measurable standard. He’s faster, healthier, better at his job. The issue is that he can’t remember the last time he made a decision without it. He doesn’t know if he likes his own coffee. He can’t choose a cereal. The muscle for deciding anything has gone away. Then his AI goes quiet for an afternoon. There’s a bug. And the world gets louder and messier and harder and more alive than it’s been in years. He tells his wife. He tells his friends. “I’m feeling naked”. He tries to convince others that they should try turning the voice off too. It’ll be more authentic. Some listen others think he’s a Luddite. A few themes I’m playing with: 1.) Autonomy as a luxury good. The wealthy pride themselves on making their own decisions. Everyone else can’t afford to get things wrong so they need the AI safety net. 2.) The gap between experience and narration. The AI fills the space where experience lives. The moment between the sensation and the label. When the AI is off, that gap opens back up and the world gets larger. 3.) Authenticity on command. At dinner with friends, the AI whispers “now is a good time to be vulnerable.” So can you be? Sharing this early because I want to pressure test the concept. Does this resonate? What’s missing?

An idea I’m playing with: AI tools are so easy to build now that trying one is like learning a new insight from the market. An insight shouldn’t need 12 months of procurement. It should take weeks/months to come into the company. There are ways for larger companies to move way faster on adopting new tools, but not with the same processes we’ve been running pre-AI. We’re working with a $10b ARR company that has a seperate sandbox with old / mock data, with tools that each have 1-3 months of a contract signed, to just test things before pushing them to production. It’s been exciting to start to now, over the last few months, see that same experimentation lead to production projects. What do you think are the new procurement processes larger companies need to set up now?

idea I’m playing with: AI tools are so easy to build now that trying one is like learning a new insight from the market. An insight shouldn’t need 12 months of procurement. It should take weeks/months to come into the company. There are ways for larger companies to move way faster on adopting new tools, but not with the same processes we’ve been running pre-AI. We’re working with a $10b ARR company that has a seperate sandbox with old / mock data, with tools that each have 1-3 months of a contract signed, to just test things before pushing them to production. It’s been exciting to start to now, over the last few months, see that same experimentation lead to production projects. What do you think are the new procurement processes larger companies need to set up now?

I’ve been enjoying Chamath creating his own content outside of All In. It’s refreshing. His interview with the founder of Binance was great too. Appreciate more of this vibe from him. Keep it up!

@awilkinson HMU homie

I need to hire someone to build an openclaw army to automate a few businesses we own. Would be a fulltime-ish for 3-6 months, contract gig, and I'm going to promote the hell out of it if successful. If you're interested, email ava@follypartners.com with why you're the one :-)

@nrmehta this was really good

This is the best articulation of a wake-up call for incumbents around AI that I've seen

Was speaking with a PE friend who's exploring buying a traditional SaaS business for $5m-$10m with plans to "AI-ify" it. My honest (and tbh biased) take: just rebuild it from scratch with AI instead. Work with that team, understand the workflows their offered to clients deeply, and give them a piece of the company to go on that ride with you. It's a harder sell emotionally (but what about all the work I've done over the past 5+ yrs...), but retrofitting AI onto an existing business is slower than starting from first principles and asking "what would this look like if AI was at the core from day one? We help companies with both, and honestly enjoy both. But if you have a choice, and the business is still relatively small (< $10m ARR), the difference in velocity and change management effort is so significant that starting from scratch might just be the smarter move.

Built a fun automation that I think will help us close an additional $5-10m in revenue over the next year or two... Here's what we did in in a few hours: 1.) Exported my LinkedIn connections 2.) Uploaded it into Cursor with Claude Code 3.) Asked to filter those folks by our ICP in Cursor 4.) Ran each person and company through a research query (who they are, what problems they're solving, what their peers are doing in AI) 5.) Connected that it to our Google Drive case studies + Fireflies meeting transcripts via MCP The output? A personalized note for each person.... "Hey Jay, looks like we've been connected for a while. We've already helped companies like yours with [specific use case]. Here are a couple case studies. Happy to trade notes on AI if you'd like :)" I'll likely still massage the messaging. But this is so powerful.

We were on a sales call with a $1b company and after our intro they said, “So you’re basically the Best Buy Geek Squad for AI?” Hilarious.