Building in public: an AI agent that bets on NBA games on @Polymarket
Powered by @claudeai + @paysponge
What it does:
- analyzes pre-game signals + Polymarket odds
- places bets using $USDC
- monitors live positions with TP/SL logic
- auto-generates post-game review dashboard
Early learnings:
- TP/SL logic harder than expected (yes, the big red candle below is real 🤣)
- Bankroll allocation framework still forming, currently pulling ideas from @nntaleb
Feels like we’re still early in agent-native finance... Would love to jam ideas with others building here!
I went to Phoenix to spend time with the Taiwanese community. TSMC will invest $265 billion and send thousands of engineers and their families, which marvel at their new lives in the Sunbelt
My first feature as a contributing writer to the New York Times:
https://t.co/n73RydKBiD
Wake up.
Every profession deemed white-collar, the middle class dream, is about to be decimated by AI, at a much faster pace than anticipated, with monstrous social consequences.
My take on a16z crypto moving into frontier tech.
First, I'll always be grateful to a16z for helping validate the space back in 2013 when Chris Dixon led their investment into Coinbase, which got me even more excited about crypto.
But the final nail in the coffin for my previous career, and what ultimately pushed me to pivot my entire career into Bitcoin, was Marc Andreessen's 2014 NYT oped, Why Bitcoin Matters. If you haven't read it, suggest reading it. It's still important to this day.
A lot of people have probably forgotten, but in those days we were all just looking for external validation. Very few institutions or funds were willing to publicly endorse crypto, and two of the funds that took a real brand risk were a16z and USV.
Since then, we've seen some of the most incredible talent enter the space and fundamentally reshaped what crypto is today.
You can actually argue that a lot of the AI infrastructure development we're seeing today wouldn't be where it is without Bitcoin mining infrastructure and the talent that flowed from crypto into AI. There is a real connection between the two industries that I don't think gets enough credit.
Now, moving from crypto into frontier tech, whether that's robotics, bio, AI, energy, compute etc just means to me that the talent and muscle we developed building crypto over the past decade can now be used to build across all of frontier tech.
We spent years building something that was nascent, misunderstood, and in many cases hated by the world. We developed thick skin, continued investing and building, and had to constantly show the world why this tech mattered. Even during thanksgiving dinners.
And I think that makes us uniquely suited to build frontier tech.
An example is data centers. Today, people and governments are increasingly pushing back against them. Well, people and governments hated crypto too, but we continued to invest and build, and now almost all of trad finance is embracing crypto in some capacity.
I believe frontier tech represents the next generation of pirates in technology. People willing to build things that are nascent, misunderstood, and sometimes hated by the world.
We're going to be hated and loved along the way, but we're going to keep building cool shit that the world hasn't recognized the importance of yet.
And crypto taught me that the world usually doesn't recognize the importance of new tech until years later which is why I stay close to talent
Ben has for many years been the best analyst in tech. I’m very much looking forward to this new @stratechery + @stripe partnership.
https://t.co/iFdKSV8NQ7
With the amount of new trading products and novel defi primitives being launched, demand for market makers, liquid funds and general liquidity providers is growing rapidly.
There simply isn't enough liquidity, risk capital, or market making infra to support the pace of the new products being launched so I suspect we will see incumbents scale aggressively and potentially an opening for new firms to enter. I see a golden opportunity for onchain finance.
We’re opening a research preview of Claude Duet, a new app where Claude works as a proactive agent.
It comes to you with what needs your attention, completes tasks you ask of it, keeps working when you step away, and checks with you before it acts on your behalf.
MAYBE I WAS WRONG ABOUT BLOCKCHAIN TECHNOLOGY
I wrote about how I always used to make fun of the guys who said things like "Bitcoin is speculative, but the underlying blockchain technology is interesting." And now I think maybe they kinda had a point.
Ben Horowitz on the two skills that will matter more than ever before in an AI world: creativity and relationships.
"I think those are things that are hard to get out of today's AI in a very good way. So if you don't have instincts around those things, I don't know if all the AI in the world could help you. Whereas the grind-them-out tasks, AI is already really good at."
"Do you have original ideas? Can you establish and maintain very high quality, high fidelity relationships with people off the rip? I think people don't think about that enough."
"One big advantage I think that we have is we really look for that. Many just ignore that whole thing, like it's not a thing... It's a thing."
@bhorowitz w/ @Tocelot
I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies.
My observations:
1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, and I kept wondering which niches are left. Digging into it actively.
2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now.
3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention.
4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is.
5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now.
6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text.
They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it.
7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy.
8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies.
Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here.
9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens.
10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity!
11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it.
12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable.
13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think.
14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data.
15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open.
16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down.
17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building?
18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone.
19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good.
20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped.
21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense.
Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era.
Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways.
Happy to be home and locked in.
Until next time!
we just launched something pretty interesting under jupiter labs.
introducing YOLO. 500x to 1000x leverage.
yes, 1000x.
we’ve been experimenting with a different approach to high leverage trading, and YOLO is our first attempt at it.
the idea is pretty simple. what if we could let people trade with extremely high leverage, without actually having to execute these massive leveraged positions in the market?
so we took inspiration from the JLP model and built YOLO, where positions are simulated against real market prices, but the profits and losses are real.
this allows us to offer leverage that goes far beyond what we currently have on jupiter perps, using a completely different approach.
of course, this also comes with some tradeoffs.
since profits are paid out from the pool, if there isn’t enough liquidity to pay out a winning position, the payout can be queued instead of being paid immediately.
it’s a different model from traditional perps, with its own risks and limitations, but i think it’s an interesting experiment worth exploring.
one thing i’ve always liked about building onchain is how much room there is to experiment with new financial products and trading experiences.
and that’s also why we’re launching YOLO under jupiter labs. to give ideas like this a place to be tested, without necessarily having to fit into our existing products.
i’m quite excited to see how people use YOLO and what we can learn from it.
it’s still early, and there are probably many things we can improve along the way.
but that’s the fun part of building and experimenting.
give it a try, understand the risks, and let us know what you think.
https://t.co/T5nfYL4sum
let’s go!
Robinhood Social is now live for everyone.
When we started with verified trades, we knew it was just the first step.
Today you can share your charts, P&L, allocations, follow the people you already trust, and get news and company updates the moment they land. And in the coming weeks, it's all on Legend.
I've wanted this for a long time. And now it's live in the app. Go check it out.
I've been traveling the world a bit. One of the most incredible experiences was getting to visit Taiwan w/ @JensenHuang. It was wild 🤯.. huge crowds of engineers, insanely good street food at night markets, and of course a lot of good conversations across many days. I caught some of it on video, see below. Alright, that's it from me, love you all ❤️
Timestamps:
0:00 - Highlights
0:46 - Intro
3:25 - Computex: crowds, engineers, tech, future of AI
9:12 - Chat with Jensen: keynote prep & nerves
13:03 - Chat with Jensen: Taiwan's tech history
19:47 - Raohe night market
29:37 - Chat with Jensen: memories from childhood
33:44 - NVIDIA party
40:29 - Lunch: braised pig's feet
43:09 - Chat with Jensen: GPUs, AI, and competition
55:07 - Ningxia night market
1:10:14 - Taiwanese breakfast
1:29:54 - Outro
If customers won't buy your stuff, try asking what they would buy. This sounds obvious, but surprisingly few founders do it, and it often yields valuable insights.
I agree with this take. Over the next year, I think we’ll see an adjustment in internet behavior where everything that was once too hard to do/high friction for most people, is now accessible.
You can send something to Instinct like “find all of the unwanted subscriptions that I’m paying for, refunds that I’m missing, unsubmitted expenses, expiring airline credits, property tax dispute opportunities, medical insurance warranty claims, and other opportunities that are falling through the cracks” to see what you’re missing out on.
Be profitable and run your company with maximal agentic loops
You don’t need to sell more of your co anymore
$10M profit per year reinvested is like an annual Series A no dilution
The best startups do this now. No whinging about the Series A/B crunch.
You don’t need saving.