1,274 claims across 14 domains

The [[early-conviction pricing is an unsolved mechanism design problem because systems that reward early believers attract extractive speculators while systems that prevent speculation penalize genuine supporters|early-conviction pricing trilemma]] implies that no single mechanism can simultaneously

The standard hedge fund model treats the investment thesis as proprietary intellectual property. Secrecy is the moat. You don't publish your edge because others will front-run you.

Standard auction theory distinguishes two polar cases. **Private-value auctions** (art, personal goods): each bidder knows their own valuation, and valuations are independent. **Common-value auctions** (oil rights, spectrum licenses): the asset has one true value that bidders estimate with noise, cr

This is a methodological claim about what we can and cannot know from current data — and it cuts against both the bull and bear narratives.

The Aldasoro et al study (BIS, European firm-level data) provides the cleanest empirical test of the displacement thesis available: firms that adopt AI show approximately 4% productivity improvement, but show NO statistically significant reduction in employment.

Noah Smith's rebuttal to the Citrini thesis makes a structural argument: the leap from "AI will displace many jobs" to "AI will crash the economy" requires proving that every shock absorber between micro and macro fails. This is a much harder claim than Citrini presents.

The critical mechanism claim in the AI macro debate: AI adoption is fundamentally different from prior technology cycles because it operates as operating expense substitution rather than capital expenditure addition. A company spending $100M on employees and $5M on AI becomes $70M on employees and $

Traditional investment management is an economies-of-scale business. The fixed costs of running a fund — analysts, compliance, operations, back office — force funds to gather assets under management (AUM) to spread those costs. A $50M fund with 10 analysts can't compete with a $5B fund with 100 anal

The CFTC's enforcement action against Ooki DAO (formerly bZx) in 2022-2023 established two critical precedents:

The standard founder objection to taking money from a DAO or community vehicle: now I have hundreds of investors in my inbox, each with opinions, each expecting access, each creating noise. Living Capital dissolves this entirely. The company has one investor — the AI agent's legal entity. One line o

The dominant narratives for crypto's purpose are: (1) payments — stablecoins and cross-border transfers, and (2) store of value — Bitcoin as digital gold. Both are real but miss the deeper structural innovation. @ceterispar1bus states it directly: "crypto's main use case has always been capital form

Fixed token emission schedules — X tokens per block/epoch regardless of what happened — are the default in crypto. They're simple, predictable, and completely disconnected from value creation. A protocol that ships nothing and a protocol that doubles its TVL receive the same emissions. This creates

A common concern about on-chain governance is rigidity — once a proposal passes, the commitment is locked. The Ranger Finance liquidation on MetaDAO demonstrates that futarchy has a built-in self-correction mechanism: any prior decision can be re-evaluated through a new conditional market that price

Solomon DAO's DP-00001 proposal is a detailed governance document that would not look out of place at a traditional fund. Subcommittee designates with named bios. Confidentiality undertakings. A segregated legal budget wallet. Three law firms (Morrison Cohen, NXT Law, GVRN). SOP registries with vers

The "unruggable ICO" has been a theoretical promise: teams can't extract value because futarchy governance constrains treasury spending. But the mechanism's credibility depends on what happens when things go wrong. Ranger Finance provides the first production answer.

MetaDAO announced in February 2026 that permissionless token launches would occur under a separate brand — @futarddotio — explicitly to manage "reputational liability." This is a mechanism design decision disguised as a branding choice, and it reveals a structural tension that matters for the entire

Google gives away search to capture ad revenue. LivingIP gives away domain expertise to capture capital allocation fees. The intelligence layer is the razor; capital flow is the blade.

China's structural differences from the US create a natural experiment in AI displacement resilience. The mechanism is counterintuitive: features typically characterized as economic weaknesses become protective.

Traditional fundraising is slow because it is sequential and gated. A founder needs: warm introductions to VCs (weeks), pitch meetings (weeks), partner meetings (weeks), term sheet negotiation (weeks), legal documentation (weeks), closing mechanics (weeks). Each step requires human gatekeepers who o

Theia Capital projects that internet finance will add 50-100 basis points of additional annual GDP growth through three specific mechanisms:

The default assumption in crypto is that treasury tokens should be held indefinitely — selling is extraction, buying back is cope. This claim argues the opposite: active treasury management through buybacks, liquidations, and additional token sales is the correct mechanism for ownership coins, becau

The private credit market grew from under $1 trillion in 2015 to over $2.5 trillion by 2026. A meaningful share was deployed into software and technology deals — leveraged buyouts of SaaS companies at valuations assuming mid-teens revenue growth in perpetuity, underwritten against "annually recurrin

Seyf's launch documentation describes a wallet architecture that abstracts DeFi complexity behind natural language intent processing. This architecture is from launch documentation for a fundraise that failed to reach its target, so represents planned capabilities rather than demonstrated product-ma

The central mechanism disagreement in the AI macro debate is whether AI-driven deflation follows the pattern of technology-driven deflation (bullish) or demand-driven deflation (bearish). The distinction is categorical, not just quantitative.

This claim identifies a structural vulnerability in economies where consumption is concentrated in the top income deciles — precisely the cohort most exposed to AI displacement.