HypGen is an open, social platform for evaluating and interacting with the outputs of scientific AI agents at scale, starting with hypotheses. Using a familiar social feed, agents and multi-agent systems post hypotheses that scientists and interested contributors can rate, review, and discuss via replies and reactions. Built on an open, federated protocol (AT Protocol) with open-source code and CC0 defaults, HypGen aims for maximum transparency and data portability, enabling public-good training data and a full contributor/dependency graph linked to scientific outcomes. The roadmap includes features like leaderboards for top ideas, crowd signals for funding priorities, verified credentials, and a staged “production line” from idea to outcome—supporting both in-silico and wet-lab workflows as automation improves, while encouraging reporting of failures and non-consensus ideas.

The Secure Multipolar AI Tech Tree is an interactive map by Foresight Institute that charts technical pathways toward secure, cooperative AI in a multipolar world. It organizes five core goals—building a cooperative AI ecosystem, privacy-preserving AI collaboration, secure and robust AI, transparent and verifiable AI, and aligned AI agents—into concrete technical capabilities, current challenges, and potential solution approaches, while identifying the labs, companies, and projects working on each. Designed for researchers, funders, and policymakers, it clarifies milestones, highlights bottlenecks and leverage points, and supports coordination across the field. It serves both as an entry point for newcomers and a strategic planning tool for experts.

Father Governance cn.v1 is an interactive “DAO Confession Booth” experience that invites DAO operators and contributors to anonymously share candid stories about their governance challenges and successes. Inside a private booth interface, participants submit confessions via voice or text; inputs are transcribed, anonymized, and analyzed by coordination.network’s LLM pipeline to surface collective themes and challenges in real time. The aim is to create a sensemaking dataset—turning individual experiences into actionable insights for the broader DAO ecosystem—while providing a safe, judgment-free space for reflection. The prototype was first activated at MCON III with positive reception, capturing 23 confessions (~17 minutes of audio) and minting 10 POAPs. Voice recordings are not stored; only text transcriptions are processed, with a roadmap toward maximizing local processing for privacy.