The Chopping Block: Do Aragon Association Members Get 'Fat Salaries' With 'Zero Accountability'? - Ep. 492
Welcome to “The Chopping Block” – where crypto insiders Haseeb Qureshi, Robert Leshner, Tom Schmidt, and Tarun Chitra chop it up about the latest news. In this episode, they talk about the recent issues surrounding the Aragon Foundation, the likelihood of Montenegro becoming an ETH hub, the BRC-20s mania, and much more!
Listen to the episode on Apple Podcasts, Spotify, Overcast, Podcast Addict, Pocket Casts, Stitcher, Castbox, Google Podcasts, TuneIn, Amazon Music, or on your favorite podcast platform.
Show highlights:
- why Zuzalu is “Burning Man in the daytime”
- whether Montenegro could become the “ETH El Salvador doppelganger”
- why the Aragon Foundation alleged that they were under attack
- why Aragon has “missed the boat on a lot of everything that’s happened in DAOs”
- whether the Aragon Foundation is “suckling on the teat of the DAO for a fat salary”
- whether Arca was right about wanting the Aragon treasury to be part of the on-chain governance
- how on-chain governance can do even more than many of the investment banking functions that exist currently
- why some Bitcoin developers want to censor BRC-20 transactions
- why the way XEN works gives Haseeb a headache
- whether Binance CEO CZ invented the memecoin PEPE
- what the impact of Jump and Jane Street decreasing their market making activity is
- where the next market makers will come from
- Haseeb Qureshi, managing partner at Dragonfly
- Robert Leshner, founder of Compound
- Tarun Chitra, managing partner at Robot Ventures
- Tom Schmidt, general partner at Dragonfly
- Unchained:
- Coinbase Apologizes After Calling PEPE a ‘Hate Symbol’
- Market Makers Jump and Jane Street Withdraw From U.S. Crypto Trading: Report
- CoinDesk: Aragon Cancels Planned Community Control of $200M Treasury Amid Battle With Activist Investors
- The Block: Coinbase cuddles up to UAE policymakers as US outlook sours
Learn more about your ad choices. Visit megaphone.fm/adchoices
Available Results
Generated results are saved to your library for reuse and search.
Choose Template
Pick the result you want. You can review provider and model before generating.
A concise first-pass summary for understanding the episode quickly.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Repeatable methods, frameworks, mental models, processes, and systems.
A dedicated inventory of concrete resources named in the episode.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Investment theses, assets, catalysts, valuation reasoning, time horizons, and risks.
Chronologies, actors, causes, consequences, turning points, and competing historical interpretations.
Policies, proposals, stakeholders, arguments, implementation constraints, and predicted effects.
Career paths, skills, hiring signals, workplace decisions, transitions, and limitations of the advice.
Behavioral mechanisms, biases, motivation, habits, emotions, interventions, and evidence limitations.
Economic mechanisms, incentives, indicators, market structure, forecasts, and uncertainty.
Leadership principles, team systems, organizational design, culture, feedback, and failure modes.
Audience, positioning, messaging, acquisition, retention, experiments, metrics, and failed approaches.
Teaching methods, learning strategies, practice, feedback, assessment, and effectiveness evidence.
Theses, premises, arguments, objections, values, thought experiments, and unresolved questions.
Communication patterns, conflict, boundaries, expectations, repair methods, and contextual limitations.
Books, papers, authors, courses, and other learning resources mentioned in the episode.
Repeatable methods, frameworks, mental models, processes, and systems.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Memorable statements and important claims with attribution and source context.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.