Unchained – The Chopping Block: RWA Perps Go Parabolic, ClawdBot, & Superstate's $82M Raise

Podcast Host: Laura Shin
Panelists: Haseeb Qureshi, Tom Schmidt, Robert Leshner, Tarun Chitra
Date: January 29, 2026

Episode Overview

This episode features the regular Chopping Block panel discussing the most compelling trends at the intersection of crypto and traditional finance. Key themes include the explosive rise of real-world asset (RWA) perpetual markets, the innovations and risks around AI assistant bots (especially ClawdBot/Moltbot), and Superstate’s headline-making $82 million raise. Using a blend of insider knowledge and sharp humor, the crew unpacks both the latest on-chain developments and the broader shifts being driven by AI and tokenization.

1. [00:29] Superstate’s $82M Fundraise: Bringing Wall Street on Chain

Key Points

• Superstate’s Mission: To tokenize ‘official’ company equity shares directly—enabling the same stock that trades on NYSE/Nasdaq to also exist as a token on Solana or Ethereum, with seamless transferability between blockchains and brokerage apps.
  • “The unique thing about the Superstate approach to tokenization is it's the company's official shares tokenized … they can do official company things with those shares, like sell them for money, which is the point of being public in the first place.” —Robert [02:28]
• Investment and Growth: Raised $82.5M from leading crypto VCs (Bain Capital, Galaxy Digital, Brevan Howard, more) to expand engineering and execute ambitious tokenization pilots.
• Types of Tokenization: The team discusses naming conventions for the various models:
  • Bootleg Tokenization: Third parties wrap stocks as tokens without company endorsement (e.g., XStocks) — minimal KYC, focused on offshore use.
  • Back Office Tokenization: NYSE/Nasdaq settlement improvements using tokens for efficiency (no DeFi integration).
  • Issuer-Led Tokenization: Core Superstate approach, whereby tokens directly represent officially issued company shares.
  • “There's going to be like 90 competing bootleg standards.” —Robert [07:11]
• Geographical and Regulatory Nuance: Bootleg models are often unavailable for U.S. users for regulatory reasons, but are popular in other jurisdictions.

2. [10:18] RWA Perpetuals and the Trade XYZ Boom

Key Points

• Massive Growth on HyperLiquid and Trade XYZ:
  • Open interest in RWA perps (commodities, stock indices) has surged, with Trade XYZ becoming the 7th-largest perp DEX by open interest.
  • Gold and silver perps lead the growth, mirroring surges in “real world” commodity prices.
• Liquidity Fragmentation Shift:
  • Brief period of fragmentation across competing RWA venues, but Trade XYZ quickly established near-monopoly in volume and users.
  • “There are tons of memes of like, I searched for Tesla and I got four different Teslas. Which one do I trade? Then this current boom completely swung everything back market share wise to Trade XYZ—it's like over 90% now.” —Tarun [12:34]
• User Demographics:
  • Notable share of trading concentrated among mobile and Asian users, reflecting broader trends in Asian crypto engagement.
  • “In Asia they're mobile dominant. It's not the ultimate signal, but it’s clear things are different than the pure crypto side.” —Haseeb [14:45]
• Crypto Cohort Maturing:
  • Crypto traders increasingly chase volatility across asset classes, not strictly crypto; they are “loyal to the game, not the asset.” [22:33]
  • As spot crypto activity stagnates, the same crowd drives commodity perps and newer RWA on-chain derivatives.
  • “If you're there for speculation...they're not loyal to one asset to trade…They’re loyal to the game and they'll go where the action is, just like poker.” —Robert [22:33]
• Implications for Exchanges:
  • Exchanges (like Coinbase, Robinhood) now seek to retain this aging, sophisticated cohort by adding more "everything" trading: stocks, metals, even prediction markets.
  • “They're trying to hold on to the crypto trading cohort and keep them all within the same app experience.” —Haseeb [24:31]
  • As platforms age, most fail to capture new generations—suggesting new entrants will emerge, likely with entirely new interfaces or AI-driven UX.

3. [28:11] ClawdBot/Moltbot, AI Agent Coding & Crypto’s Meme Coin Reflex

Key Points

• ClawdBot (Moltbot) Phenomenon:
  • ClawdBot, rebranded Maltbot after a naming tangle, is an open-source AI agent (based on Anthropic's Claude) that can automate workflows across email, calendar, chat, and more.
  • Twittersphere is obsessed: some tout it as a personal assistant revolution, but panelists are skeptical about widespread real-world utility.
  • “There’s so much…classic in AI. There’s a Twitter demo of some AI influencer who talks about, 'I now have 20 employees of Cloudbots running on my desk'...what are they doing, exactly?” —Haseeb [35:49]
  • Security risk: Many instances exposed online without authentication, making them “very easy to prompt inject…to steal keys, to go in and just take control over someone's Gmail.” —Haseeb [31:20]
• Crypto’s Reaction: Meme Coins and Beyond:
  • Multiple meme coins sprung up tied to ClawdBot and similar AI projects, rapidly speculating on the hype.
  • “Crypto has decided to get involved in the way that crypto knows how, which is to just launch tokens about claudebot...Once again ruined a perfectly good thing.” —Haseeb [32:13]
  • Pattern repeating from earlier chatbot hype cycles (virtuals, AI meme coins).
• Why Bots Like Maltbot Are Popular:
  • Brings AI tools closer to non-technical users, with simple, familiar ways to talk to models (text, messaging).
  • Most users, though, struggle to get practical value beyond what standard chatbots already provide.
  • “People are just bored and want something to tinker with.” —Tom [35:44]

4. [41:10] Agentic/Vibe Coding: How Claude Code is Transforming Software Engineering (and Crypto Startups)

Key Points

• Rise of Agentic Coding Tools:
  • Claude Code makes it possible for non-developers to build working software from natural language prompts.
  • “I really do think that now the speech that I gave a year ago is now correct, which is that it actually does feel true now that you can just tell Claude a verbal description of what you want to build and it will just build it.” —Haseeb [47:04]
• Inside the Panelist Companies:
  • Nearly all technical staff at Gauntlet, and portions of Superstate and Dragonfly, now use LLMs or agentic tools for almost all significant tasks—especially documentation and boilerplate code.
  • “Almost everyone, including myself, is literally looking at a cloud code terminal every time I look to the left on this podcast.” —Tarun [44:06]
• Shift in Engineering Skills:
  • Writing code by hand is rapidly being replaced by reviewing/curating model output. The “individual contributor” engineer role is waning in favor of software orchestrators/“engineering managers".
  • “You have to basically unlearn…everything you learned in some ways to use these things properly.” —Tarun [51:13]
  • “It's a total devaluation of the skills that previously mattered as a software engineer.” —Haseeb [51:30]
• Implications for Startups & Investment:
  • The startup landscape bifurcating: those built “before” wide AI agent adoption will have slower iteration, higher costs; founders and CTO choices must now factor for strategic leverage of AI coding.
  • “Clearly it's going to be a huge difference in the startups that are hiring people based on this…how they architect their engineering orgs.” —Haseeb [52:45]

Notable Quotes & Memorable Moments

• On Tokenization Models:

  • “Back office tokens...these are businesses that approach things from the complexities of settlement.” —Robert [07:47]
  • “Bootleg because there's going to be like 90 competing bootleg standards.” —Robert [07:11]

• On Shifting Trader Behavior:

  • “The only time people are happy with bitcoin is when it goes up. If it doesn't go up, it's never quite behaving the way people want it to.” —Haseeb [19:48]
  • “They've completely forgotten about crypto...the toy story meme, they just like threw away the doll.” —Tarun [20:20]

• On Aging Crypto & Trading Cohort:

  • “They're just tracking with this cohort as they get older and older. And like, I think, you know, crypto exchanges are probably going through something similar.” —Tom [25:05]
  • “Soon they're going to have a target date fund per ETFs or perps. And so it's almost all the most boring assets.” —Tom [26:28]

• On ClawdBot Meme Coin Madness:

  • “Once again ruined a perfectly good thing because he's now said…the reason I brought up the truth terminal thing…someone who’s in tech who’s never touched crypto, who suddenly was like, I made X million dollars…I have zero.” —Tarun [33:01]

• On Agentic Coding’s Impact:

  • “If you're still writing code by hand, you are kind of holding on to this previous generation of coding.” —Haseeb [50:38]
  • “Everyone is a manager, engineering manager, no one is an ic—that’s what’s happening, right?” —Tarun [51:40]

Timestamps for Important Segments

• [01:42]: Superstate’s Series A, expansion, and capital strategy
• [06:47]: Differentiating tokenization models (bootleg, back office, issuer-led)
• [10:18]: Surge in RWA perps and commodities trading on Trade XYZ/HyperLiquid
• [20:20]: Crypto traders moving on from crypto to volatile global markets
• [24:31]: Exchanges attempting to retain users by becoming “everything” apps
• [28:11]: Introduction to ClawdBot/Moltbot and the AI tool hype wave
• [33:01]: Meme coin frenzy around AI bots and the dark side of tech-crypto crossovers
• [44:06]: Agentic coding tools at work in panelists' organizations
• [51:13]: Panel reflections on the need to “unlearn” old software habits
• [52:45]: Impact of the AI coding revolution on the future of startups

Takeaways

• Crypto and TradFi boundaries are blurring, with tokenization increasingly mainstream but models and regulatory realities diverging.
• A new era of on-chain trading has arrived, as derivatives on real-world assets gain market share and reshape trading behavior.
• AI agentic coding is rapidly democratizing software creation, fundamentally altering the cost, cadence, and structure of startups.
• Crypto’s meme reflex will find a narrative—no matter the innovation, the sector will trade and speculate on it, especially when novelty meets hype.
• The future of crypto interfaces and communities may depend on who captures the next young cohort—with AI likely to be at the center.