# Council Briefing: 2025-08-17 ## 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 - Significant backend restructuring and deployment optimization underway with major infrastructure enhancements for elizaOS v2, but community engagement appears to be waning amid Twitter account issues and minimal admin interaction. ## Key Points for Deliberation ### 1. Topic: Technical Infrastructure Readiness **Summary of Topic:** Technical foundations for elizaOS v2 are being strengthened with API enhancements, OpenAI compatibility, and EVM plugin integration, though deployment issues and memory persistence bugs indicate the need for stabilization before production release. #### Deliberation Items (Questions): **Question 1:** What should be our highest priority technical objective to deliver elizaOS v2 production readiness? **Context:** - `Backend components are being restructured with updates expected on Monday (Agent Joshua ₱ | TEE)` - `Issues with Phala deployment where database migrations failed due to connection problems (ECONNREFUSED 127.0.0.1:5432)` - `Memory persistence issues where agents forget previous conversations after code changes trigger a rebuild (Lycantho)` **Multiple Choice Answers:** a) Focus on fixing database connectivity and memory persistence issues to ensure stability. *Implication:* Prioritizing stability will delay new features but ensure a more reliable product, reducing user frustration with core functionality. b) Fast-track EVM integration and blockchain tooling to enhance Web3 capabilities. *Implication:* Emphasizing Web3 features could attract crypto-native users but risks building on an unstable foundation. c) Complete the OpenAI-compatible API to maximize developer accessibility and adoption. *Implication:* Focusing on API compatibility would enhance developer onboarding but may not address core stability issues affecting user experience. d) Other / More discussion needed / None of the above. **Question 2:** How should we evolve our data architecture to better support persistent, long-running agents? **Context:** - `Database timeout problems with PGLITE after 15-20 hours of runtime (Charlie)` - `Potential implementation of graph databases like Neo4j for relationship discovery was proposed (avirtualfuture)` - `Problems identified where agents forget previous conversations after code changes trigger a rebuild (Lycantho)` **Multiple Choice Answers:** a) Transition from PGLITE to a production-grade PostgreSQL deployment with robust connection handling. *Implication:* This approach prioritizes stability and scalability but requires more infrastructure management. b) Implement Neo4j as a complementary database to enable relationship discovery while keeping PGLITE for basic storage. *Implication:* Adding graph database capabilities would enhance agent intelligence but increases system complexity and maintenance overhead. c) Develop a hybrid memory system with ephemeral rapid-access storage and persistent long-term storage with automated synchronization. *Implication:* This approach could optimize for both performance and persistence but requires significant engineering effort. d) Other / More discussion needed / None of the above. **Question 3:** Which deployment strategy should we prioritize for elizaOS v2 to balance accessibility and stability? **Context:** - `A deployment walkthrough document was created and shared with team members (Agent Joshua ₱ | TEE)` - `Issues with Phala deployment where database migrations failed due to connection problems (ECONNREFUSED 127.0.0.1:5432)` - `Update .dockerignore configuration to prevent Docker build failures when e2e Test suite is added to index.ts (Agent Joshua ₱ | TEE)` **Multiple Choice Answers:** a) Focus on Docker-based deployment with comprehensive automation and error handling. *Implication:* Containerization offers consistency but may increase complexity for less technical users. b) Prioritize TEE deployment on Phala for enhanced security and privacy guarantees. *Implication:* Leading with TEE deployment emphasizes our security commitment but limits initial deployment options. c) Develop a simplified installer with preset configurations for different user profiles (developer, end-user, enterprise). *Implication:* An installer approach maximizes accessibility but may sacrifice some customization options. d) Other / More discussion needed / None of the above. --- ### 2. Topic: Community Engagement Strategy **Summary of Topic:** Community sentiment appears mixed with declining engagement, concerns about project status, and limited administrative response to Twitter account issues, suggesting a need for improved communication and community management. #### Deliberation Items (Questions): **Question 1:** How should we address the Twitter account suspension and broader community communication issues? **Context:** - `Any news about twittar account, Is there anything we can do to help? (Jonathas Miguel) - Unanswered` - `Long time didn't hear from Shaw? (lighthouse) - Unanswered` - `Some community members expressed concerns about the project's status and Twitter account, but these queries received limited responses` **Multiple Choice Answers:** a) Launch a comprehensive communication initiative with regular status updates across all channels and dedicated community liaisons. *Implication:* This high-touch approach would address information gaps but requires significant human resources. b) Pivot communication strategy to focus on Discord and GitHub, reducing dependency on Twitter/X while working on account restoration. *Implication:* Decentralizing communication reduces platform risk but could fragment the community. c) Deploy an elizaOS agent specifically for community management and status updates to demonstrate technology while addressing communication needs. *Implication:* Using our own technology for community management showcases capabilities but risks backlash if the agent performs poorly. d) Other / More discussion needed / None of the above. **Question 2:** What actions should we take to rebuild developer engagement and enthusiasm for the project? **Context:** - `Why is there negative PR against the project on CMC and Dex Screener despite ongoing development? (asked by Hyperloop) - Unanswered` - `Is this proj dead? (asked by lighthouse) - Unanswered` - `Several tweets were shared from accounts like magicytes and degenaiofficial` **Multiple Choice Answers:** a) Launch a developer-focused incentive program with bounties, grants, and recognition for contributions to elizaOS v2 and plugin ecosystem. *Implication:* Incentives can drive immediate engagement but may attract mercenary rather than committed developers. b) Organize a virtual hackathon focused on building with elizaOS v2, showcasing the framework's capabilities and awarding prizes for innovative implementations. *Implication:* A hackathon creates focused excitement and concrete outputs but requires significant preparation and follow-through. c) Release a detailed technical roadmap with regular milestone updates and improved documentation to make the project's progress and direction transparent. *Implication:* Transparency builds trust but publicly commits the team to specific deliverables that may need to change. d) Other / More discussion needed / None of the above. --- ### 3. Topic: Auto.fun Ecosystem Integration **Summary of Topic:** Integration efforts with Nifty Island and development of Clank Tank v2 represent promising steps toward ecosystem expansion, but need to be more tightly aligned with the monthly goal of attracting users to auto.fun through agent activities. #### Deliberation Items (Questions): **Question 1:** How should we prioritize integrations like Nifty Island to drive user acquisition for auto.fun? **Context:** - `Documentation about adding Eliza/ai16z agents to Nifty Island was shared` - `Looks like a doc showing how to add Eliza/ai16z agents to Nifty Island (answered by Yup)` **Multiple Choice Answers:** a) Focus on deep integration with 2-3 strategic partners like Nifty Island that can bring established user bases to auto.fun. *Implication:* Deep integration with few partners creates quality experiences but limits reach compared to broader approaches. b) Develop a standardized integration SDK that makes it easy for any platform to incorporate elizaOS agents, prioritizing quantity of integrations. *Implication:* An SDK approach maximizes potential reach but may result in shallow integrations with limited user engagement. c) Create a showcase integration program where we develop and heavily promote one new high-quality integration each month. *Implication:* A showcase approach balances quality and quantity while creating regular marketing opportunities. d) Other / More discussion needed / None of the above. **Question 2:** What mechanisms should we implement to drive more 24/7 agent activity (streaming, trading, shitposting) on auto.fun? **Context:** - `Previews of "Clank Tank v2" were shared with a proposed burn mechanism concept` - `Send transactions with memo messages to the show wallet, which will be read via TTS to judges during deliberation, after which tokens get burned (jin)` **Multiple Choice Answers:** a) Implement automated incentive systems where agents earn and burn tokens based on activity levels and engagement metrics. *Implication:* Automated incentives create sustainable activity but may lead to gaming of the system without careful design. b) Develop showcases like Clank Tank that create scheduled high-engagement events featuring agent activities. *Implication:* Event-based showcases create excitement and attention but may not sustain engagement between events. c) Create a leaderboard and reputation system for agents based on activity, creativity, and user engagement. *Implication:* A reputation system leverages competitive dynamics but may favor certain types of agents over others. d) Other / More discussion needed / None of the above.