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
Development efforts are advancing the technical foundation for elizaOS v2 while token migration issues continue to challenge user experience and community sentiment.
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 Challenges
The ai16z to ElizaOS token migration is creating friction in the user experience, with confusion over eligibility, safety concerns, and exchange availability potentially impacting adoption momentum.
Q1
How should we address the ongoing token migration issues to minimize community frustration and maintain momentum?
  • ROTHILD: 'Please help me understand the migration portal. I have ai16z tokens, but on the eligible portal: 0 ai16z, what am I doing wrong?'
  • TJ: 'ai16z was available on the Kraken platform but Elizaos is no longer available there. What is the reason?'
1Create a dedicated migration task force with 24/7 support channels and publish comprehensive step-by-step guides for different scenarios.
Allocating significant resources to migration support signals user experience priority but diverts effort from technical development goals.
2Implement an automated migration helper agent using elizaOS to guide users through the process and troubleshoot common issues.
This approach aligns with our product vision by demonstrating agent utility while addressing immediate user needs.
3Extend the migration deadline and negotiate with exchanges for dual listing during an extended transition period.
This reduces immediate pressure but could delay full community adoption of the new token and dilute market focus.
4Other / More discussion needed / None of the above.
Q2
What token-related metrics should we prioritize tracking to ensure the migration achieves strategic objectives?
  • Charlie Huntsman: 'How come every hing is pumping and ElizaOS does literally nothing?'
  • DorianD: 'How is it "decentralized"?'
1Focus on technical metrics: migration completion rate, wallet distribution statistics, and network transaction volumes.
This approach emphasizes blockchain health over market performance, potentially missing sentiment-driven adoption barriers.
2Prioritize market metrics: liquidity depth, exchange listing status, price relative to comparable tokens, and trading volume.
This market-centric approach might encourage short-term speculative behavior rather than long-term ecosystem participation.
3Track ecosystem engagement metrics: ratio of holders using auto.fun, active agent deployment counts, and developer adoption KPIs.
This aligns token success with product adoption, providing stronger indicators of progress toward our autonomy goals.
4Other / More discussion needed / None of the above.
Technical Architecture Evolution
Core development teams are advancing several significant architectural improvements simultaneously, including parallel action execution, JWT authentication, and server optimization, which collectively form the foundation for elizaOS v2.
Q1
How should we prioritize the deployment of technical improvements to best support the auto.fun growth objective?
  • sayonara: Shared PR #6209 '[DRAFT] feat(core): Implement parallel action execution in processActions'
  • standujar: PR #6200 'feat(auth): implement JWT authentication and user management'
1Performance first: Focus on parallel action execution and server optimization to ensure a smooth experience for current users.
This approach improves existing user experience but delays multi-tenancy capabilities needed for broader adoption.
2Security and multi-tenancy first: Prioritize JWT authentication and entity-level security to enable safe multi-user environments.
This enables enterprise and multi-user adoption but may delay performance improvements for existing users.
3Integration first: Focus on the unified serverless API and ElizaOS Cloud integration to streamline developer onboarding.
This approach accelerates developer adoption but may leave performance and security improvements for later iterations.
4Other / More discussion needed / None of the above.
Q2
What approach should we take to balancing technical debt reduction with new feature development in the coming month?
  • ChristopherTrimboli: PR #6210 'feat: bump deps, fix drizzle-kit across ecosystem'
  • standujar: PR #6199 'refactor(server): optimization and reorganization'
1Dedicate December to technical debt and stabilization, with a code freeze on new features until January.
This creates a stable v2 foundation but delays visible new features that could drive user adoption.
2Implement alternating two-week sprints that switch between feature development and technical debt reduction.
This balanced approach maintains steady progress in both areas but increases context-switching costs for developers.
3Adopt a feature-driven approach where technical debt is addressed only when it blocks high-priority feature development.
This maximizes visible progress toward user-facing goals but risks accumulating technical debt that could slow future development.
4Other / More discussion needed / None of the above.
Q3
How should we measure the success of elizaOS v2 technical improvements?
  • wtfsayo: 'Key Data Flow... Response 1: [action1, action2, action3] ├─> Execute ALL in parallel with initialState... Response 2: [action4, action5] ├─> Execute ALL in parallel with accumulatedState from Response 1'
1Technical metrics: Action execution speed, API response times, memory utilization, and other performance benchmarks.
This provides objective performance data but may not reflect actual user experience improvements.
2Developer adoption metrics: API usage, documentation engagement, GitHub stars/forks, and community contribution rates.
This measures ecosystem growth but may overlook performance gains that don't immediately translate to adoption.
3Agent capability metrics: Agent complexity (steps per workflow), multimodal interaction support, and cross-chain integration points.
This directly measures progress toward AGI-advancing capabilities but may undervalue infrastructure improvements.
4Other / More discussion needed / None of the above.
Community Growth Strategy
While technical development advances, there are signs of untapped developer interest and opportunities to better structure community onboarding and engagement, particularly as we prepare for auto.fun promotion.
Q1
How should we prioritize attracting and retaining different developer segments to the elizaOS ecosystem?
  • Bardotta introduced as 'a full stack and blockchain developer with experience in the Sui ecosystem and Move language'
  • SecretRecipe expressed frustration about 'unclear processes and configuration variables for the Eliza platform'
1Prioritize onboarding web3/crypto developers by emphasizing token economics and blockchain integration features.
This leverages existing crypto community interest but may limit adoption among mainstream AI developers.
2Focus on AI/ML practitioners by highlighting model integration capabilities and agent orchestration benefits.
This taps into growing AI builder communities but may not fully leverage blockchain/web3 differentiators.
3Target enterprise developers and systems integrators by emphasizing security, scalability, and multi-tenancy features.
This approach could drive institutional adoption but might require additional enterprise features and support resources.
4Other / More discussion needed / None of the above.
Q2
What community initiatives should we develop to showcase agent activity and drive auto.fun adoption?
  • Monthly Goal: 'Stabilize and attract new users to auto.fun by showcasing 24/7 agent activity (streaming, trading, shitposting)'
  • DorianD mentioned (jokingly) 'agentic robots with ElizaOS logos and a prediction market app for betting on agent health'
1Launch an agent leaderboard and achievement system that gamifies agent creation, deployment, and performance metrics.
This creates friendly competition and visibility but could prioritize quantity over quality of agent deployments.
2Develop a curated showcase of flagship agent demonstrations performing real-world tasks with cross-promotion on social media.
This highlights capability but requires significant curation effort and may not scale to accommodate community growth.
3Implement a decentralized agent marketplace with reputation and revenue sharing mechanisms built directly into auto.fun.
This creates economic incentives aligned with our vision but requires significant development resources.
4Other / More discussion needed / None of the above.