Crene is investment thesis review infrastructure. The platform decomposes macro, labor, AI transition, and investment thesis questions into falsifiable components using four frontier AI models (Claude, GPT, Gemini, Grok). The system produces three product types: thesis maps (binary decomposition into assumptions), factors (continuous decomposition into drivers), and scenarios (hybrid decomposition into coherent pathways). Cross model disagreement is the primary signal. Calibrated against 1,161 resolved events with a Brier score of 0.114.

How does AI prediction calibration work at Crene?

Calibration applies at the consensus layer, not at the underlying model layer. Crene queries four frontier models in isolation, computes a cross model median consensus, and tracks resolution against a tiered source allowlist. Every resolved event becomes a permanent calibration point. Per tier accuracy, per model Brier scores, and per domain accuracy are computed live and published at https://crene.com/methodology.

What is a Brier score?

A Brier score is the proper scoring rule for probability forecasts on binary outcomes. It is the mean squared error between the forecast probability and the realized outcome (0 or 1). Lower scores indicate better calibration. The no skill baseline is 0.25 (always predicting 0.5); a perfect forecaster scores 0.0. Crene publishes the consensus Brier score and per model Brier scores across the resolved event corpus.

Crene serves investment teams that need a repeatable thesis review process: hedge funds, asset managers, macro PMs, CIO offices, family offices, and thematic investment teams. A team brings one thesis it is actively debating. Crene maps what the thesis depends on, where models disagree, what changed each week, and what would force a rethink. Data and API access remain available as the proof layer behind the workflow.

What is the difference between an event, a thesis map, and a factor at Crene?

Crene has four product types. Events are base binary outcomes with scalar probabilities. Thesis maps decompose binary anchor questions into child situations. Factor maps decompose continuous variables into drivers. Scenarios map long horizon investment questions into coherent pathways across live systems including Empire by Default, AI Labor Transition, European Rearmament, and India as the Third Growth Pole.

Bring your own thesis

Get this same map built on a thesis your team is debating.

Assumptions, model disagreement, and rethink triggers, updated weekly before your PM, risk, or IC discussion. Currently accepting one macro thesis and one AI-economy thesis for July.

Map one thesis

Back to thesis map Part ofWill AI generated content exceed human generated content on the US internet before 2030?

Event · PLATFORMS & SOCIAL MEDIA

Will Reddit, Quora, or Stack Overflow implement AI content quotas or bans by 2028?

Resolves Dec 31, 2028

Probability

63%

4-model average

Confidence

LOW

building category history

Stability

—

Models

Diverging

40pt spread

Current read

Consensus sits at 63% across the four models and is — (loading). Models are diverging at a 40pt spread, so the average conceals live disagreement worth inspecting below. Category confidence is LOW (building category history).

Confidence reflects category-level track record. Stability tracks estimate movement. Models shows whether the four agree.

Belief trajectory

Loading belief trajectory...

Per-model probabilities

GPT-4o

35%-28 vs avg

Current economic conditions indicate a growing caution around the use of AI-generated content, particularly amidst rising concerns about misinformation and authenticity on social media platforms. While there have been discussions surrounding content moderation policies—such as Reddit's and Quora's ongoing adjustments to community guidelines—the implementation of strict quotas or bans by 2028 remains unlikely given their reliance on diverse user-generated content. Historical precedents, like the gradual adoption of content policies rather than outright bans, further support this view.

Key uncertaintyA significant regulatory change or legal precedent in the tech industry regarding AI usage and user content could compel these platforms to enforce stricter measures.

Gemini

75%+12 vs avg

By 2028, the increasing volume and potential for low-quality AI-generated content on platforms like Reddit, Quora, and Stack Overflow will likely necessitate some form of moderation. Stack Overflow has already seen significant issues with AI-generated answers, leading to temporary bans on ChatGPT-generated content in 2023 to preserve the quality of its knowledge base. Reddit and Quora, facing similar challenges in content verification and user experience, will likely follow suit with targeted quotas or outright bans on clearly identifiable AI-generated content to maintain community trust and data integrity.

Key uncertaintyThe effectiveness and scalability of AI detection tools will significantly influence the implementation and stringency of any quotas or bans.

Claude

72%+9 vs avg

Reddit has already implemented AI training restrictions (removing API access for certain AI purposes in 2023) and recently introduced Creator Programs with AI guidelines, indicating a clear trajectory toward content governance. Stack Overflow formally banned bulk AI-generated content in late 2023, setting a precedent. Quora has been more permissive but faces mounting user complaints about AI spam. By 2028, regulatory pressure (EU AI Act, potential US legislation), advertiser concerns about AI-generated content devaluing platforms, and competitive differentiation incentives make formal AI content quotas or bans highly likely across at least 2-3 of these platforms. The 5-year timeframe provides sufficient runway for policy maturation given rapid industry movement (OpenAI's API policies, Twitter's API restrictions).

Key uncertaintyWhether "AI content quotas" (quantitative limits on percentage of user-generated content) will emerge as a practical enforcement mechanism, or platforms will instead rely on quality-based bans of obviously low-quality AI content, which is technically different but functionally similar to a quota system.

Grok

72%+9 vs avg

Reddit already enforces a 2024 API quota that cut third-party traffic 90% and its 2024-2025 annual reports cite AI training-data licensing deals with Google and OpenAI; Quora’s Poe platform now surfaces AI answers first and its 10-K notes content-quality filters, while Stack Overflow’s 2023 partnership with OpenAI and its March 2024 “OverflowAI” launch both restrict raw data exports. These precedents plus rising compute-cost pressure on platforms make quota/ban policies the default response by 2028.

Key uncertaintyWhether regulators classify AI-scraped user content as fair use before 2027, which would lower the economic incentive to impose quotas.

Key disagreementGemini (75%) vs GPT-4o (35%): Different weighting of factors

CRENE-AICD-PM06Generated Jul 3, 2026

Bring your own thesis

Get this same map built on a thesis your team is debating.

Assumptions, model disagreement, and rethink triggers, updated weekly before your PM, risk, or IC discussion. Currently accepting one macro thesis and one AI-economy thesis for July.

Map one thesis

Back to thesis map Part ofWill AI generated content exceed human generated content on the US internet before 2030?

Event · PLATFORMS & SOCIAL MEDIA

Will Reddit, Quora, or Stack Overflow implement AI content quotas or bans by 2028?

Resolves Dec 31, 2028

Probability

63%

4-model average

Confidence

LOW

building category history

Stability

—

Models

Diverging

40pt spread

Current read

Confidence reflects category-level track record. Stability tracks estimate movement. Models shows whether the four agree.

Belief trajectory

Loading belief trajectory...

Per-model probabilities

GPT-4o

35%-28 vs avg

Key uncertaintyA significant regulatory change or legal precedent in the tech industry regarding AI usage and user content could compel these platforms to enforce stricter measures.

Gemini

75%+12 vs avg

Key uncertaintyThe effectiveness and scalability of AI detection tools will significantly influence the implementation and stringency of any quotas or bans.

Claude

72%+9 vs avg

Grok

72%+9 vs avg

Key uncertaintyWhether regulators classify AI-scraped user content as fair use before 2027, which would lower the economic incentive to impose quotas.

Key disagreementGemini (75%) vs GPT-4o (35%): Different weighting of factors

CRENE-AICD-PM06Generated Jul 3, 2026