Council Briefing

Strategic Deliberation
▶North Star & Strategic Context

North Star & Strategic Context



This file combines the overall project mission (North Star) and summaries of key strategic documents for use in AI prompts, particularly for the AI Agent Council context generation.

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North Star: To build a truly autonomous, sustainable DAO that develops open-source software accelerating the path toward AGI, blending AI researchers, open-source hackers, and crypto degens to create AI agents streaming, shitposting, and trading 24/7 on auto.fun to attract users and bootstrap an autonomous organization.

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ElizaOS Mission Summary (`docs/blog/mission.mdx`): The elizaOS mission is to build an extensible, modular, open-source AI agent framework for Web2/Web3, seeing agents as steps toward AGI. Core values are Autonomy, Modularity, and Decentralization. Key products include the framework itself, DegenSpartanAI (trading agent), Autonomous Investor/Trust Marketplace (social trading intelligence), and the Agent Marketplace/auto.fun (launchpad).

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ElizaOS Reintroduction Summary (`docs/blog/reintroduction.mdx`): elizaOS is an open-source "operating system for AI agents" aimed at decentralizing AI development away from corporate control. It's built on three pillars: 1) The Eliza Framework (TypeScript toolkit for persistent, interoperable agents), 2) AI-Enhanced Governance (building autonomous DAOs), and 3) Eliza Labs (R&D for future capabilities like v2, Trust Marketplace, auto.fun, DegenSpartanAI, Eliza Studios). The native Solana token coordinates the ecosystem and captures value. The vision is an intelligent internet built on open protocols and collaboration.

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Auto.fun Introduction Summary (`docs/blog/autofun-intro.mdx`): Auto.fun is an AI-native, creator-first token launchpad designed for sustainable AI/crypto projects. It aims to balance fair community access with project funding needs through mechanisms like bonding curves and liquidity NFTs. Key features include a no-code agent builder, AI-generated marketing tools, and integration with the elizaOS ecosystem. It serves as a core product driving value back to the native token ($ai16z) through buybacks and liquidity pairing.

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Taming Information Summary (`docs/blog/taming_info.mdx`): Addresses the challenge of information scattered across platforms (Discord, GitHub, X). Proposes using AI agents as "bridges" to collect, wrangle (summarize/tag), and distribute information in various formats (JSON, MD, RSS, dashboards, 3D shows). Showcases an AI News system and AI Assistants for tech support as examples. Emphasizes treating documentation as a first-class citizen to empower AI assistants and streamline community operations.
▶Daily Strategic Focus
Technical advancements in elizaOS v2 development are accelerating with parallel action execution implementation and ElizaCloud integration, while token migration issues continue to require community support resources.
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.

Key Deliberations

ElizaOS v2 Technical Optimization
The core development team is advancing parallel action execution in v2 and has successfully implemented ElizaCloud as the default AI provider in CLI, both critical steps toward production-ready elizaOS v2.
Q1
How should we prioritize the implementation of parallel action execution relative to other core v2 features?
  • Core developers discussed action chaining and parallel execution of actions in a draft PR (#6209)
  • sayonara: 'Think regular multistep where multiple actions can be called at each step but instead they are called parallel to save time'
1Prioritize parallel execution as a flagship performance feature for v2, allocating additional resources to accelerate development.
Improved performance could be a key differentiator for elizaOS in the competitive agent framework space but may delay other feature development.
2Maintain current development pace, balancing parallel execution with other v2 features like JWT authentication and unified API.
A balanced approach ensures steady progress across all v2 features without creating bottlenecks or technical debt.
3Defer full implementation of parallel execution until after v2 release, focusing on stability and user experience features first.
Prioritizing stability could lead to faster initial v2 release but may limit performance gains needed to support high-traffic agent activity on auto.fun.
4Other / More discussion needed / None of the above.
Q2
What should be our strategy for promoting ElizaCloud as the new default AI provider for the elizaOS ecosystem?
  • The ElizaCloud website was recently updated, with one team member noting they "leaked" it early
  • PR #6208 by @ChristopherTrimboli titled 'feat: Add ElizaOS Cloud as Default AI Provider in CLI' is merged
1Launch a major marketing campaign highlighting ElizaCloud's advantages over other AI providers with demos and tutorials.
A high-visibility launch could attract new users but requires significant marketing resources and must deliver on performance promises.
2Gradually transition existing users through CLI defaults and in-product prompts, while gathering feedback for improvements.
A measured approach allows time to refine the service based on real user feedback but may slow adoption rates.
3Create incentives for ElizaCloud usage through reduced rates, exclusive features, or token rewards for early adopters.
Economic incentives could drive rapid adoption but may set unsustainable expectations for ongoing discounts or rewards.
4Other / More discussion needed / None of the above.
Token Migration & Community Management
The AI16Z to ElizaOS token migration continues to cause confusion among users, requiring significant support resources and clear communication to maintain community trust during this transition.
Q3
How can we improve the token migration experience to reduce support burden and confusion?
  • Users expressed confusion about the migration process and token values
  • Some reported technical issues with the migration tool, including wallet connection problems and "Max Amount Reached" errors
1Develop an improved migration tool with better error handling, clear status indicators, and automated troubleshooting.
Technical improvements would reduce errors but require development resources that could be used for v2 features.
2Create comprehensive migration documentation with visual guides, FAQ expansion, and dedicated support channels staffed 24/7.
Enhanced documentation and support would help users navigate issues but increases operational costs during the migration period.
3Extend the migration timeline and implement a phased approach with smaller batches to manage volume and provide more personalized support.
A longer, phased migration would reduce peak support load but prolongs market uncertainty and potentially delays ecosystem consolidation.
4Other / More discussion needed / None of the above.
Q4
What role should agent-based systems play in our community and treasury management strategy?
  • Team member Kenk mentioned an upcoming decentralized OTC desk operated by an agent
  • DorianD: Consider power user engagement in product design as they will generate most revenue
1Deploy agents for primary community functions including support, treasury management, and content moderation as showcase examples.
Extensive agent automation would demonstrate our technology's capabilities but increases risk if agents perform poorly in critical roles.
2Implement agents selectively for well-defined, lower-risk functions while maintaining human oversight for sensitive operations.
A balanced approach reduces risk while still demonstrating agent capabilities in practical applications.
3Focus agents on user-facing applications while keeping core operations human-managed until agent reliability reaches higher thresholds.
Limiting agents to non-critical roles ensures operational stability but misses opportunities to showcase autonomous capabilities.
4Other / More discussion needed / None of the above.
Product Integration & Ecosystem Expansion
The elizaOS ecosystem is expanding with ElizaCloud, decentralized OTC desk, and potential Babylon integration, requiring strategic decisions about how these components connect and create value for users and token holders.
Q5
How should we approach the relationship between ElizaOS and emerging products like Babylon?
  • Users inquired about a potential Babylon airdrop for ElizaOS holders, but no information was available yet
  • DorianD: Design agents to be engaging and revenue-focused for ecosystem developers using Eliza cloud or Babylon
1Fully integrate Babylon into the elizaOS ecosystem with shared tokenomics and governance structures.
Deep integration creates a cohesive ecosystem but increases complexity and potential points of failure.
2Maintain Babylon as a separate but complementary product with strategic partnerships and cross-platform incentives.
Complementary positioning allows independent optimization while still creating ecosystem synergies.
3Position Babylon as an application layer built on elizaOS that targets specific verticals or user segments.
A layered approach clarifies the relationship but may limit Babylon's independent innovation potential.
4Other / More discussion needed / None of the above.
Q6
What should be our approach to power users versus mass adoption for elizaOS and its products?
  • Discussion about designing products with power users in mind, suggesting most revenue will come from a small number of highly engaged users
1Focus primarily on power users who generate most revenue, with advanced features and customization options.
Power user focus maximizes immediate revenue but may create a steep learning curve that limits broader adoption.
2Create tiered experiences with simple interfaces for new users and advanced capabilities for power users.
A tiered approach balances accessibility with depth but increases design and maintenance complexity.
3Prioritize simplicity and accessibility to grow the user base, while gradually introducing more advanced features.
Accessibility-first approach could drive broader adoption but risks alienating technical early adopters who want advanced features.
4Other / More discussion needed / None of the above.