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
Token migration from AI16Z to ElizaOS dominates community discussion while core development continues on enhanced memory systems and two revenue-generating products: Cloud and Babylon.
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

Token Migration Strategy
The migration from AI16Z to ElizaOS has caused significant community confusion and price volatility, with users experiencing various issues related to eligibility, conversion rates, and exchange support.
Q1
How should we address the ongoing migration confusion to minimize community fragmentation and token price volatility?
  • The Light: Marc A requested the name change due to it conflicting with his a16z corp. Plus migration offered opportunity to become cross chain with x402 integration.
  • Multiple users reported problems with the migration portal not recognizing their tokens (OscarN_Music, MATRIX)
1Create a comprehensive migration guide with clear timelines, supported exchanges, and detailed troubleshooting steps.
Would resolve immediate confusion but requires significant documentation effort and may delay other priorities.
2Extend the migration deadline and simplify the process by removing snapshot restrictions.
Would increase token accessibility but potentially dilute value for early supporters and create arbitrage opportunities.
3Accelerate partnership development with major exchanges to handle migration automatically for users.
Would streamline the process for most holders but increases dependency on third parties and may incur listing fees.
4Other / More discussion needed / None of the above.
Q2
Should we prioritize technical stability of the migration portal or focus on expanding exchange/wallet integrations?
  • RAMO: Users confused about existence of snapshot despite contradictory information
  • Will123: Users with tokens on Kraken are uncertain about migration process
1Stabilize the migration portal first, addressing all reported technical issues before expanding to new integrations.
Ensures reliable core infrastructure but delays broader accessibility and may limit migration options for exchange users.
2Prioritize exchange integrations to automate migration for the majority of holders, particularly on Korean exchanges where issues are most severe.
Maximizes accessibility but may perpetuate technical issues with the self-service portal and divide developer attention.
3Balance both priorities by assigning dedicated teams to portal stability and exchange integrations concurrently.
Addresses both issues simultaneously but requires more resources and coordination, potentially slowing progress on other strategic initiatives.
4Other / More discussion needed / None of the above.
Revenue-Driven Development Strategy
With limited treasury funds, the team is developing two revenue-generating products (Cloud and Babylon) to fund further development and token liquidity, with a focus on building a world for agents backed by elizaOS tokens.
Q3
How should we prioritize and sequence the development of Cloud and Babylon to maximize revenue generation?
  • shaw: It's technically complete with documentation, tutorials, and tooling, but needs consumer-facing applications.
  • shaw: Use revenue to buy tokens and seed liquidity.
1Develop Cloud first as it leverages existing infrastructure, then use its revenue to accelerate Babylon development.
Creates sequential revenue streams but delays the potential synergies between both products and may miss market timing for Babylon.
2Develop both products concurrently with minimal viable features to establish multiple revenue streams quickly.
Accelerates initial revenue generation but risks launching two incomplete products that underwhelm users and generate less revenue overall.
3Focus development resources on whichever product has the clearest path to market and highest revenue potential based on user research.
Optimizes for maximum initial revenue but may create imbalanced development and potential technical debt in the neglected product.
4Other / More discussion needed / None of the above.
Q4
What token-economic model should we implement for the agent world to maximize sustainable value creation?
  • shaw: A world for agents backed by a chain where $elizaOS serves as gas, with staking and fee-earning opportunities
1Implement a pure gas fee model where agents pay elizaOS tokens for computational resources and storage.
Creates consistent token demand but may limit adoption due to upfront costs and create volatile usage patterns tied to token price.
2Develop a hybrid model with subsidized basic usage and premium features requiring tokens or staking.
Balances accessibility with value capture but requires more complex economic modeling and may dilute token value without careful design.
3Create a reputation-based system where agents earn tokens through contributions, which can be spent on premium services.
Incentivizes positive ecosystem contributions but potentially creates more complexity in token distribution and may take longer to generate direct revenue.
4Other / More discussion needed / None of the above.
Advanced Agent Memory Architecture
The team is developing a sophisticated long-term memory system for AI agents with nine structured categories, which will significantly enhance agent capabilities and user experience in consumer-facing applications.
Q5
How should we balance memory complexity with onboarding simplicity for new agent creators?
  • 0xbbjoker: Create memory structure for identity, expertise, projects, preferences, data sources, goals, constraints, definitions, and behavioral patterns
  • Odilitime: Create system for 16 pre-built character types based on Jungian psychology
1Prioritize advanced memory features with comprehensive onboarding tutorials to educate users about the system's full capabilities.
Maximizes technical sophistication but risks overwhelming new users with complexity during onboarding.
2Implement a tiered approach with basic templates for beginners and advanced customization options for experienced users.
Balances accessibility with power but creates development overhead to maintain two parallel systems.
3Focus on pre-built templates based on Jungian archetypes with minimal customization options initially, expanding complexity over time.
Simplifies initial user experience but limits the uniqueness of created agents and may disappoint power users.
4Other / More discussion needed / None of the above.
Q6
How should the memory system implementation be prioritized relative to other v2 features to meet our monthly goal?
  • Monthly goal: Stabilize and attract new users to auto.fun by showcasing 24/7 agent activity (streaming, trading, shitposting), ship production ready elizaOS v2.
1Prioritize memory system as a core v2 feature, even if it delays the overall release, as it fundamentally enhances agent capabilities.
Creates more powerful and differentiated agents but risks missing monthly goal timelines for shipping production-ready v2.
2Implement a simplified version of the memory system for v2 release, with plans to enhance it in subsequent updates.
Meets release deadlines but delivers a less impressive initial experience and requires managing user expectations about future enhancements.
3Focus on shipping other v2 features first and delay the memory system to a point release, prioritizing stability over new capabilities.
Ensures timely and stable v2 release but may miss an opportunity to showcase a standout feature that could drive adoption.
4Other / More discussion needed / None of the above.