# Council Briefing: 2025-09-08 ## 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 elizaOS team is executing a comprehensive architectural refactor of the CLI while enhancing user experience through real-time action visualization and implementing dynamic prompting for multi-turn agent conversations. ## Key Points for Deliberation ### 1. Topic: Token Value & Community Confidence **Summary of Topic:** Community members have expressed significant concerns about AI16z token value losses (-60% to -63%) and are requesting clearer explanations about token utility and rebranding implications. #### Deliberation Items (Questions): **Question 1:** How should we address the community's concerns about token value while maintaining focus on technical development? **Context:** - `Community members expressed significant concerns about token value losses (ranging from -60% to -63%).` - `Q: Can you please comment explicitly on the plans for token utility if any? A (Odilitime): We have articles coming out on the topic, stay tuned.` **Multiple Choice Answers:** a) Accelerate the planned articles on token utility and provide a detailed roadmap connecting utility to value accrual. *Implication:* This approach prioritizes transparency but may divert resources from technical development temporarily. b) Maintain current communication strategy with articles in development, while implementing small token utility features to demonstrate progress. *Implication:* This balanced approach shows commitment to both value and development, but may not satisfy those seeking immediate explanations. c) Focus primarily on delivering the core technical roadmap and auto.fun agent functionality, letting utility emerge naturally from product adoption. *Implication:* This development-first approach may improve long-term value but risks further short-term community dissatisfaction. d) Other / More discussion needed / None of the above. **Question 2:** What specific token utility mechanisms should we prioritize implementing in the next 30 days to address community concerns? **Context:** - `Community members requested clarification on token utility plans, with Odilitime indicating that articles addressing these concerns are forthcoming.` - `Brief references to "agentic payments" and "A2A permanent economy" with a note that "elizaos is currently working on this."` **Multiple Choice Answers:** a) Auto.fun buybacks and liquidity pairing tied to agent marketplace activity metrics. *Implication:* Directly connects token value to the success of the agent ecosystem, providing immediate utility but requiring market infrastructure. b) Implement agent-to-agent (A2A) payment rails with AI16z as the native currency for agent services and API access. *Implication:* Creates organic demand for tokens through system utility, but requires significant technical development. c) Launch a staking program that provides governance rights and revenue sharing from auto.fun agent activities. *Implication:* Offers immediate passive utility to holders while building community governance, but may not drive as much active token velocity. d) Other / More discussion needed / None of the above. --- ### 2. Topic: Framework Architecture Refactor **Summary of Topic:** A major architectural refactor is underway to centralize business logic in the server package, improve CLI simplicity, and create a more maintainable codebase structure while enhancing user experiences with real-time feedback. #### Deliberation Items (Questions): **Question 1:** Given the scope of the architectural changes, how should we balance the refactoring efforts with delivering new user-facing features? **Context:** - `A major architectural discussion began around a comprehensive refactor of the Eliza CLI (#5860), proposing to centralize business logic into a new `@eliza/server` package.` - `This PR refactors the ElizaOS architecture by moving all business logic from the CLI package to the server package. The CLI becomes a thin orchestration layer that delegates to the server package, eliminating code duplication and creating a cleaner separation of concerns.` **Multiple Choice Answers:** a) Prioritize completing the architectural refactor before adding significant new features to ensure a stable foundation. *Implication:* This creates a more maintainable codebase but delays delivery of user-visible improvements that could drive adoption. b) Implement a phased approach where refactoring and new features are developed in parallel streams with careful integration points. *Implication:* This balanced approach maintains momentum on both fronts but increases complexity in release management and testing. c) Focus on user-facing features that support auto.fun agent activities, while making only targeted architectural improvements where blocking. *Implication:* This prioritizes short-term user adoption goals but accumulates technical debt that may slow development later. d) Other / More discussion needed / None of the above. **Question 2:** How should we leverage the new real-time action visualization capabilities to enhance auto.fun agent activity and user engagement? **Context:** - `The web chat UI received a significant upgrade to display real-time action calls (#5865).` - `This PR introduces a comprehensive Real-time Action Execution UI System that provides transparency and visibility into agent action execution. Users can now see actions as they happen, with detailed input/output data, status tracking, and error handling - all updated in real-time.` **Multiple Choice Answers:** a) Create a public dashboard showcasing live agent trading, streaming, and content creation activities with visualization of real-time actions. *Implication:* This provides compelling social proof of the platform's capabilities but requires additional frontend development. b) Implement specialized action visualizations for trading agents that show market analysis steps and decision reasoning. *Implication:* This focused approach improves specific high-value use cases but doesn't address the full range of agent activities. c) Develop a user-configurable action display system where community members can create custom visualizations for specific agent behaviors. *Implication:* This leverages community creativity but requires more sophisticated infrastructure and developer tooling. d) Other / More discussion needed / None of the above. --- ### 3. Topic: Advanced Agent Capabilities **Summary of Topic:** Recent development introduces significant new agent capabilities including dynamic prompting for multi-turn conversations, enhanced image generation, and new model integrations, expanding possibilities for agent deployment and interaction. #### Deliberation Items (Questions): **Question 1:** How should we position the new multi-turn conversation capabilities to drive adoption of auto.fun agents? **Context:** - `A major feature was added to enable dynamic prompting for multi-turn conversations in ElizaOS scenarios, significantly enhancing agent testing capabilities (#5824).` - `This PR implements Dynamic Prompting (multi-turn conversations) in ElizaOS scenarios, enabling sophisticated testing of agent behavior through extended conversations where an LLM simulates realistic user responses.` **Multiple Choice Answers:** a) Showcase agent personalities with memory and conversational depth through interactive demos on auto.fun. *Implication:* This highlights the human-like quality of interactions but may set high expectations for all agents on the platform. b) Focus on practical use cases where conversation memory creates value, such as customer support and educational agents. *Implication:* This targets specific high-value verticals but may not capture the imagination of the broader crypto community. c) Develop a 'conversation marketplace' where users can deploy pre-trained conversation flows for common scenarios. *Implication:* This productizes the capability for non-technical users but requires additional infrastructure development. d) Other / More discussion needed / None of the above. **Question 2:** With the fix for Discord image generation and new model capabilities, what visual content strategy should we prioritize for auto.fun agents? **Context:** - `A key fix enabled image generation in Discord channels (#5861).` - `OpenRouter Updates: New Sonoma AI models with 2M context windows are now available through OpenRouter. A PR was created for OpenRouter image generation model integration.` - `User requested image generation action generating agent images instead of user-requested images` **Multiple Choice Answers:** a) Implement automated meme generation and visual commentary from trading agents tied to market events. *Implication:* This creates viral, shareable content but requires sophisticated prompt engineering and moderation systems. b) Develop agent avatars and visual identities that evolve based on agent activities and performance. *Implication:* This creates stronger emotional connections to agents but increases complexity in identity management. c) Focus on data visualization capabilities that transform complex information into intuitive graphics and charts. *Implication:* This enhances utility for serious users but may miss opportunities for broader social engagement. d) Other / More discussion needed / None of the above.