# Council Briefing: 2025-09-29 ## Monthly Goal Current focus: Stabilize and attract new users to auto.fun by showcasing 24/7 agent activity (streaming, trading, shitposting), ship production ready elizaOS v2. ## Daily Focus - The AI16z to ElizaOS token migration is imminent (October 6th), with technical progress on elizaOS v2 continuing through significant core refactoring and stabilization efforts. ## Key Points for Deliberation ### 1. Topic: Token Migration Preparation **Summary of Topic:** The migration from AI16z to ElizaOS token is scheduled for October 6th, but community members are seeking clearer communication about the process, especially for tokens held on centralized exchanges. #### Deliberation Items (Questions): **Question 1:** How should we prioritize communication about the token migration to maximize both user confidence and technical readiness? **Context:** - `Migration of AI16z to ElizaOS is scheduled for October 6th` - `Community members are seeking clarification about the migration process, especially for tokens held on centralized exchanges` - `More detailed information about the migration is expected to be released in October` - `Some users expressed concerns about the lack of social media exposure and updates from the team` **Multiple Choice Answers:** a) Comprehensive technical documentation first, followed by social media announcements. *Implication:* Ensures migration integrity but may leave users anxious about the process until closer to the date. b) Immediate high-level announcements across all channels with a promise of technical details to follow. *Implication:* Builds awareness and confidence quickly but risks creating expectations that may shift as technical details are finalized. c) Coordinated release of both technical details and user-friendly guides simultaneously with exchange partners. *Implication:* Provides the most complete user experience but requires delaying communication until all pieces are finalized. d) Other / More discussion needed / None of the above. **Question 2:** What level of exchange integration should we prioritize for the token migration to ensure the best user experience? **Context:** - `joe_: Is 'October 6th' the migration day?` - `rubysan: seems like it from the post` - `godlike1987: What to do when Ai16z migrates to ElizaOS? I have my token on CEX. Do I need to transfer for later migration?` - `rubysan: In October there will be more info you'll be okay brother ❤️` **Multiple Choice Answers:** a) Focus on self-custody wallets first, with exchange support as a secondary priority. *Implication:* Empowers technically-savvy users immediately but may alienate mainstream holders who prefer exchanges. b) Prioritize tier-1 exchange integrations before launch, delaying if necessary to ensure broad CEX support. *Implication:* Maximizes accessibility for average users but creates dependency on exchange timelines and cooperation. c) Launch with parallel support for both self-custody and a select group of committed exchanges. *Implication:* Balances accessibility with execution speed but requires managing multiple integration processes simultaneously. d) Other / More discussion needed / None of the above. --- ### 2. Topic: V2 Technical Stability **Summary of Topic:** The core development team is making significant progress on elizaOS v2 with focus on refactoring type definitions, fixing build processes, and improving plugin compatibility, but several technical challenges remain to be addressed. #### Deliberation Items (Questions): **Question 1:** How should we prioritize remaining technical issues to ensure a stable, production-ready v2 release? **Context:** - `PR #5998 by @tcm390 titled 'refactor type definitions across runtime.' is merged` - `PR #6004 titled 'refactor(core): make runtime initialization idempotent and improve service registration coordination' is merged` - `PR #6010 by @wtfsayo titled 'fix(server): downgrade plugin import failure from error to warn' is merged` - `A user encountered an OpenAI plugin error while following the quick start guide, resolved by updating to a specific alpha version of the CLI (`@elizaos/cli@1.5.13-alpha.3`)` **Multiple Choice Answers:** a) Focus on developer experience: solve CLI errors, plugin compatibility, and documentation first. *Implication:* Improves adoption and reduces support burden but may delay core architectural improvements. b) Prioritize core architectural stability: complete runtime refactoring and service coordination before addressing peripheral issues. *Implication:* Creates a more robust foundation but might frustrate early adopters dealing with surface-level issues. c) Balance bug fixes with feature completion: alternate between resolving critical bugs and implementing remaining v2 features. *Implication:* Provides continuous visible progress but risks spreading engineering resources thin across multiple priorities. d) Other / More discussion needed / None of the above. **Question 2:** What level of backward compatibility should we maintain between v1 and v2 releases? **Context:** - `Eliza v1.5.14 was released on GitHub, though there's an issue with the npm release possibly related to a token problem` - `A user encountered an OpenAI plugin error while following the quick start guide, resolved by updating to a specific alpha version of the CLI` - `cjft shared a link to an Eliza waifu quest application deployed on Vercel, which uses runtime.useModel rather than the Eliza agent pipeline` **Multiple Choice Answers:** a) Strict compatibility: Ensure all v1 agents and plugins work with v2 without modification. *Implication:* Minimizes migration pain but constrains architectural improvements and innovation. b) Compatibility with migration path: Allow breaking changes but provide clear migration guides and tooling. *Implication:* Balances innovation with user experience but requires significant documentation and support resources. c) Fresh start with parallel support: Make v2 a clean redesign while maintaining v1 as a separate supported branch. *Implication:* Enables maximum technical improvement but splits resources and may confuse the ecosystem. d) Other / More discussion needed / None of the above. --- ### 3. Topic: Auto.fun Agent Ecosystem Growth **Summary of Topic:** While development progresses on technical foundations, there's growing interest in practical AI agent use cases including DegenAI (Spartan), moderation teams, and marketplace intermediaries that could showcase auto.fun's capabilities. #### Deliberation Items (Questions): **Question 1:** Which agent use cases should we prioritize to best showcase auto.fun's capabilities and attract new users? **Context:** - `Significant interest in DegenAI (also referred to as "Spartan")` - `Shaw is reportedly purchasing DegenAI tokens and considering a livestream` - `Several potential use cases for AI agents were proposed, including: Moderation teams for online communities, Payday loan processing services, Decentralized marketplaces with AI intermediaries` **Multiple Choice Answers:** a) Focus on financial agents: Double down on DegenAI's trading capabilities and financial analysis tools. *Implication:* Leverages existing momentum but narrows the ecosystem to finance-focused applications. b) Prioritize content/community management: Develop moderation, curation, and community management agents. *Implication:* Addresses a clear market need but requires sophisticated understanding of social dynamics and policy enforcement. c) Create a diverse showcase: Develop multiple agent types across different domains to demonstrate versatility. *Implication:* Demonstrates platform flexibility but risks spreading resources thin and delivering less refined examples. d) Other / More discussion needed / None of the above. **Question 2:** How should we approach the technical challenges of training more sophisticated agents like moderation AIs? **Context:** - `DorianD: Why hasn't anyone made a good moderation team agent AI yet?` - `Odilitime: Model sucks at rule following and moderation, I did some experiments but maybe I suck at this idk, someone will crack it` - `DorianD: Access to chat logs of good moderation teams, including team member interactions, community interactions, and decisions made - especially from channels that grow and have "happier" users` **Multiple Choice Answers:** a) Partner with existing communities to access high-quality moderation training data. *Implication:* Provides real-world data but requires careful privacy management and partner relationship building. b) Develop specialized fine-tuning techniques specifically for rule-following and moderation tasks. *Implication:* Creates technical IP and differentiation but requires significant AI research investment. c) Build a hybrid system combining LLM capabilities with rule-based guardrails and human oversight. *Implication:* Delivers practical results faster but may not push the boundaries of full agent autonomy. d) Other / More discussion needed / None of the above.