Dragonfly ＞|＜

Global since day one

Posts are not investment advice or an ad for investment services
→

[Dragonfly ＞|＜ @dragonfly]

We dropped the .xyz

New fit.
https://t.co/jpaP4Dj8HP // @dragonfly

[Rob Hadick ＞|＜ @HadickM]

Over the last four years during my time at Dragonfly, we’ve consistently discussed who we look up to, how we want the firm to evolve and exist many years from now, and what is the legacy we want to leave behind. The Benchmark partnership model and their ability to see around corners is one we have consistently come back to as a North Star, and I’m excited and proud to continue to help lead Dragonfly into that future, alongside Haseeb, Bo and Tom, as we grow and continue to back the best founders innovating across money, markets and intelligence.

[Haseeb Qureshi ＞|＜ @hosseeb]

News from the Dragonfly team: @HadickM and @tomhschmidt have been promoted to Managing Partners, leading @dragonfly alongside myself and Bo.

Both Tom and Rob have been central to building the firm into what it is today, from the deals we've led, our leadership in industry, to the founders we've stood behind through every cycle.

Our mission is the same: backing the founders building the future of money and markets. Going forward, Dragonfly is run by the four of us.

[Dragonfly ＞|＜ @dragonfly]

We are excited to announce @HadickM and @tomhschmidt have been promoted to Managing Partners, joining @hosseeb and Bo in leading Dragonfly.

The promotions recognize the role both have played in shaping Dragonfly into the firm it is today, and mark the firm’s move to a broader partnership. As co-leaders, Rob and Tom will help carry forward what Dragonfly has always done: backing the founders building the future of money and markets.

[The Chopping Block @_choppingblock]

Black October was a wake-up call, but is it over?

Naturally, we brought on the least technical technical guy we know to find out: @HadickM

Meanwhile, Robert says not that much broke. Tom says it's just the tip of the iceberg. Tarun says closed source is the real risk.

Timestamps
00:00 Intro
02:56 Black October: the web's worst 48 hours
09:13 Should we be scared?
12:06 Crypto got here first
15:16 Why Claude won't help you patch
17:13 Banks are blocking AI agents
22:07 Bernie Sanders says pause AI
26:41 Everything is crypto now
33:01 Joe Weisenthal, Hyperliquid, and blockchains
39:25 The Visa and Fireblocks rumor
43:08 2021 was a bubble
45:31 Who's the Fireblocks of AI?

🔥Stay updated with all the latest hot takes by following and subscribing to @_ChoppingBlock and @unchained_pod!

🎥 YouTube: https://t.co/2U5lB5Zpeh
🎧 Spotify: https://t.co/0ilprLbily
🍎 Apple: https://t.co/jrnmstoLAN
🎙 Podcast Home: https://t.co/r6OZC52hUx

[Digital Assets Forum @DAF_Global]

Institutional digital assets are being shaped across banking, investing, trading and regulation.

At DAF New York, Pete Najarian (@petenajarian1) -@RaptorDigitalHQ, Artem Korenyuk -@Barclays, Michael Schroeder -@Revolut, John D’Agostino (@johnjdagostino) -@coinbase, Kinjal Shah (@_kinjalbshah) -@bcap, Sebastian Pulido -@Grayscale, Tom Schmidt -@dragonfly and Serena McMullen - Aosphere bring those perspectives into the same room.

13 November. New York.
https://t.co/98WZwlXZQb

[Dragonfly ＞|＜ @dragonfly]

Our comment letter to the CFTC on compute derivatives contracts:

“The governing approach should be technology-neutral and risk-based”

Full letter: https://t.co/2MyXtuLMV9

[Lindsay Lin @LindsayxLin]

This week, @dragonfly filed a comment letter with the CFTC on compute derivatives. Compute is a swiftly growing expense for tech companies, yet the market for hedging its cost is still nascent.

The challenge starts with defining what’s being traded. Not all GPU-hours are equal: hardware, performance, and availability can materially affect their value. Liquid derivatives markets need comparable units of compute and reliable price benchmarks.

@HadickM @bryanmedelman @peteryshin and I advocate for technology-neutral standards, equal treatment of credible pricing sources, and support for perpetual futures to hedge ongoing compute costs.

We applaud @CFTC for taking on these important questions and laying the groundwork for a liquid, competitive compute derivatives market.

[Lindsay Lin @LindsayxLin]

This week, @dragonfly filed a comment letter with the CFTC on compute derivatives. Compute is a swiftly growing expense for tech companies, yet the market for hedging its cost is still nascent.

The challenge starts with defining what’s being traded. Not all GPU-hours are equal: hardware, performance, and availability can materially affect their value. Liquid derivatives markets need comparable units of compute and reliable price benchmarks.

@HadickM @bryanmedelman @peteryshin and I advocate for technology-neutral standards, equal treatment of credible pricing sources, and support for perpetual futures to hedge ongoing compute costs.

We applaud @CFTC for taking on these important questions and laying the groundwork for a liquid, competitive compute derivatives market.

[Haseeb Qureshi ＞|＜ @hosseeb]

I was wrong.

Agents don't need crypto. It's us humans who do.

I break down what the industry got wrong in my @token2049 talk, Agents + Crypto: What's Real and What's Cope 👇

[Dragonfly ＞|＜ @dragonfly]

.@HadickM on @MTSlive re: agents + money:

“When you’re built on top of Plaid, you have a bunch of failures, failure rates at 2% or so for ACH. And there’s a lot of capital inefficiency in it as well.”

“If you ask your LLM what bank should you use that is agent friendly, they’ll tell you Mercury. They won’t tell you JPMorgan.”

“A financial institution that controls those different accounts and is able to monetize those different accounts, that is AI first and agent first, that is where you’re likely to see a lot of this happen.”

“The concern is the surplus will continue to shift from banks to fintechs.”

[Casey Taylor @casatay]

New addition for the crypto podcast roster 👀

[Money Code @MoneyCodePod]

🎙️A new season. A new duo. Money Code Season 2 welcomes @HadickM and @Nick_van_Eck as your new hosts.

Rob is a General Partner at @dragonfly, investing across stablecoins, payments and financial infrastructure. He previously helped build GoldenTree’s digital asset strategy, with earlier roles at Goldman Sachs and PJT Partners.

Nick is the CEO and Co-founder of @withAUSD, a modern money and banking platform. A former Partner at General Catalyst, he’s gone from backing software and blockchain companies to building one.

On Money Code, they’ll speak with founders, operators, allocators and policymakers about stablecoins, tokenized assets and AI.

What’s ready for adoption? Where are the investment opportunities? What still needs to be built?

Insights to help you make better build, buy, partner and investment decisions.

What would you ask an investor and a stablecoin founder?

Episode 1 is coming soon. Subscribe to Money Code wherever you get your podcasts.

Presented by @thestablecon.

[Nick van Eck @Nick_van_Eck]

High quality guests, strong opinions, and a ton of fun.

@HadickM and I will be bringing on incredible operators this year. Grateful the @thestablecon team asked us to host.

[Dragonfly ＞|＜ @dragonfly]

We’re featured in @elwood_io’s latest case study!

@joshraphaellim sat down with our portfolio company to break down how we track our token positions across the full lifecycle ⤵️

[Elwood @elwood_io]

New case study: how @dragonfly runs a token portfolio from locked to liquid.

https://t.co/03BYbHo1iN

-

For professional clients only. Not for retail clients.

Elwood is a technology provider; clients trade through their own venue and counterparty relationships. Dragonfly is also an investor in Elwood.

[Bitcoin.com News @BitcoinNews]

“It was the right idea, the wrong time.”

At @kbwofficial, @dragonfly GP @tomhschmidt tells @_dsencil what Polymarket and Ethena taught him about timing, then looks ahead to perp DEXs, prediction markets and crypto AI.

Watch now.
In a year, this may read very differently. ⏬

[Dragonfly ＞|＜ @dragonfly]

@hosseeb podcast credit // @laboss https://t.co/0rysx2jwuZ

[Alex LaBossiere @laboss]

What happened to crypto?

I sat down with Haseeb Qureshi (@hosseeb), Managing Partner at Dragonfly, to find out.

We spoke about digital dollars, nationalized banks, bubbles and speculation, Iran and BlackRock, jaywalking, and beanie babies.

0:00 – Intro
1:23 – What Happened to Crypto?
3:18 – Stablecoins and Escape Velocity
7:04 – Bitcoin, Gold, and the Generational Trade
10:34 – War and Stores of Value
15:06 – Retail, Nvidia, and Capital Flight
18:23 – Stablecoins 101
20:00 – Eurodollars, Venmo, and AI Agents
23:00 – Dollarization and the Black Market
25:28 – Banks, Airwaves, and the Balance of Power
31:20 – Too Many Currencies
36:11 – Institutions and Cypherpunks
40:08 – Iran and BlackRock
41:00 – Speculation and Bubbles
43:12 – Prediction Markets and the Overton Window
51:04 – Skin in the Game and the Rational Voter
54:06 – Staying in Crypto
57:13 – When Crypto VC Ends
58:57 – What Would Change Haseeb’s Mind on Crypto
1:03:00 – What Should More People Be Thinking About?

[Dragonfly ＞|＜ @dragonfly]

.@hosseeb on speculative mania:

"There's no financial revolution that has taken place without some kind of speculative mania... Now we see it happening with AI, and of course we've seen it many times now with crypto."

"The thing that really explains speculation is human behavior, and ultimately people's willingness to believe and to pull forward the expectations of the future."

"One thing that you can see from all the bubbles that previously took place within crypto is that they were all correct. They were all right that crypto was going to take over the world, that it was going to expand like a wildfire, and that it was going to be way bigger than anybody at the time was contemplating."

[Haseeb Qureshi ＞|＜ @hosseeb]

I should probably also mention, @dragonfly is investing in @typesafeai's latest round! :)

My quick thesis on decision models, since I've been having a lot of conversations about this lately:

LLMs are amazing because they are fully general. You can use them for pretty much anything. But they are slow, expensive, and too unreliable to embed in software at runtime. Unless your product is literally chat, real-time LLM calls are unworkable for the majority of use cases. (Especially in finance!)

Decision models change that. To abuse an analogy, they are the ASICs of LLMs. They give up the generality of an LLM, but in exchange for constraining your outputs, you get MASSIVE gains in cost-efficiency, throughput, and latency.

In the early days of the AI boom, people understandably tried to shove LLMs into everything. But like with ASICs, you will eventually constrain your problem enough to burn it into the machine. Once your problem is an if-else, a buy or sell, a label, a choice, or a well-defined state machine like an onchain smart contract, a decision model will clobber the LLM on cost, speed, and reliability.

Most systems are not language-in, language-out.

Going forward, LLMs will write our code (since coding is high-dimensional and general), but that code will embed decision models to make runtime software intelligent and capable.

That's the bet we're making with Typesafe. They identified this path and proved that it works. 25%+ of the Fortune 500 is already using Jev, and it launched less than a month ago.

Of course, there are murmurings on the timeline that decision models are easy to copy. OpenAI, Microsoft, Amazon, and Cloudflare have all launched decision models in the weeks since Jev launched, realizing that this is going to be an enormous market and they don't want to lose it.

To be sure, anyone can lop off the last layer of Qwen, fine-tune it to create a classifier, and copy the Typesafe SDK's API. But there's a lot more that goes into a world-class decision model, and there's a reason why Jev is still cheaper, faster, and more general than these other alternatives. (Decision model benchmarking started all of 10 minutes ago, but if you ask devs who've tried them, they'll tell you Jev is far and away the best right now.)

There's no guarantee that lead lasts forever though. Decision models are too big of a market to be able to coast into a monopoly. From here, the onus is on them. They have to keep training better models ($$ helps), ship great products, serve their models better, faster, and cheaper than anyone else (many more tricks there), and win developers with their community-first philosophy. But they've been at this for years and have a lot up their sleeves (they were expecting a bevy of copycats if Jev took off). Diogo knows from his years at OpenAI how to sustain a research advantage. And as with all startups, focus is how you beat the incumbents.

Super bullish on this team.

And if you're a dev and you haven't tried Jev yet, get on it.

[Digital Assets Forum @DAF_Global]

The next wave of crypto companies will need more than a strong narrative.

Tom Schmidt (@tomhschmidt), General Partner at @dragonfly, joins DAF New York to discuss where venture investors are finding conviction across infrastructure, DeFi, stablecoins, payments and new market technologies.

Meet Tom and other leading investors at DAF New York:
https://t.co/98WZwlXZQb

[Dragonfly ＞|＜ @dragonfly]

Full interview via Bloomberg: https://t.co/YnjkZlvm7i

[Dragonfly ＞|＜ @dragonfly]

Is crypto VC going extinct?

"No, I think it's evolving."

"If you rewind the clock back to 2021–2022, there were a lot more VCs who raised money on the idea that they were going to deploy into a crypto venture."

"And the idea was that, well, anybody can do this. You just have to sling some money around and some tokens and everything goes up automatically."

"We're in a very different world now. We're in a regime where there's not that many players that are really institutional quality, and that can really add value to a lot of these projects."

"Most of the easy money in crypto is gone now."

@hosseeb on @BloombergTV at Token2049