▶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

The technical team successfully merged a significant security infrastructure upgrade (Entity-level RLS & Security Improvements) that strengthens elizaOS v2's data isolation and multi-tenant capabilities while making progress on token migration coordination with exchanges.

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 token migration from AI16Z to ELIZAOS is creating frustration among users due to unclear communication and varying levels of exchange support, with particular issues around the November 11th snapshot and exchanges allowing trading after this date.

How should we prioritize our approach to resolving migration issues with centralized exchanges?

Kraken's token swap is in progress, with the team coordinating with their communications team
Users from Bithumb are seeking updates on migration support

1Focus resources on establishing clear migration protocols with Tier 1 exchanges (Kraken, etc.) first, then address smaller exchanges.

This would serve the majority of holders but might further alienate users on smaller exchanges like Bithumb who are already expressing frustration.

2Establish a standardized manual migration process for all users regardless of exchange, reducing dependency on exchange cooperation.

This puts more operational burden on our team but gives users a consistent fallback option that doesn't depend on exchange timelines.

3Extend the migration window beyond 90 days and increase transparency with daily updates on exchange-specific migration progress.

This reduces immediate pressure but could delay stabilization of the new token's market activity and increases communication overhead.

4Other / More discussion needed / None of the above.

What measures should we implement to improve communication around the token migration process?

Some frustration expressed about lack of clear communication regarding migration timelines
Questions raised about who was responsible for an unannounced snapshot related to migration

1Implement a real-time migration status dashboard showing exchange-by-exchange progress and eligibility criteria.

This technical solution addresses transparency but requires development resources that could otherwise focus on elizaOS v2 completion.

2Appoint a dedicated migration community liaison to provide daily updates across all channels and handle user support tickets.

This human-centered approach improves user satisfaction but increases operational overhead and may still not resolve technical migration issues.

3Create comprehensive migration documentation including FAQ, decision history, and clarify eligibility rules with step-by-step guides for different user scenarios.

This documentation-focused approach scales well but relies on users seeking out information rather than proactive outreach.

4Other / More discussion needed / None of the above.

How can we leverage the token migration to strengthen user engagement with auto.fun and other ecosystem products?

Current focus: Stabilize and attract new users to auto.fun by showcasing 24/7 agent activity
Suggestion that elizaOS might be used for Discord verification in the future

1Offer migration incentives tied to auto.fun participation, such as additional tokens or features for migrated users who deploy agents.

This directly connects migration to our monthly goal but may be seen as unfair by users who experience migration difficulties.

2Develop and showcase auto.fun integration tools that specifically leverage the new ELIZAOS token's features.

This focuses on technical integration that delivers value but may delay addressing immediate migration concerns.

3Create a temporary community-building initiative where successfully migrated users can contribute to a collective auto.fun agent showcase.

This builds community around both the migration process and our monthly goal, but requires coordination resources.

4Other / More discussion needed / None of the above.

Security and Technical Infrastructure

The team has implemented significant security improvements through Entity-Level Row Level Security (RLS) and streamlined participant checking, enhancing data isolation and multi-tenant capabilities while preparing for production-ready elizaOS v2.

How should we communicate the strategic importance of the RLS security improvements to our community and potential enterprise adopters?

Entity-Level Row Level Security (RLS) - PostgreSQL RLS policies for entity-based data isolation
PR #6167 titled 'feat: Entity-level RLS & Security Improvements' is merged, implementing row-level security and enhancing security features

1Focus on the enterprise-readiness narrative, highlighting how these security features enable multi-tenant SaaS deployments with proper data isolation.

This positions elizaOS for enterprise adoption but might seem less relevant to individual developers and the crypto community.

2Emphasize privacy protection for end-users, showcasing how agent data remains secure even in shared environments.

This resonates with privacy-conscious users but might undersell the technical sophistication of the implementation.

3Frame it as foundational infrastructure enabling future automated governance capabilities, connecting security to the autonomous DAO vision.

This ties security improvements to our long-term North Star but might seem abstract compared to immediate user benefits.

4Other / More discussion needed / None of the above.

With these technical improvements now in place, what should be our next priority for elizaOS v2 readiness?

PR #6192 by @wtfsayo titled 'fix: dynamic prompt normalization follow-up' is merged, addressing issues with prompt normalization
Current monthly directive: ship production ready elizaOS v2

1Focus on agent performance optimization for 24/7 operation, ensuring reliability for continuous trading and streaming functions.

This directly supports the auto.fun goal of showcasing agent activity but might delay other v2 features.

2Prioritize developer experience improvements like enhanced logging and documentation to accelerate third-party adoption.

This could expand our developer ecosystem but might not immediately translate to visible auto.fun activity.

3Complete the x402 middleware implementation to enable micropayment-based agent-to-agent interactions across the platform.

This opens new economic models for the platform but adds complexity to the v2 launch requirements.

4Other / More discussion needed / None of the above.

What approach should we take to ensure our technical documentation matches our rapid development pace?

Update documentation or officially rely on deepwiki.com/elizaOS/eliza (Mentioned by sayonara)
Taming Information Summary: Emphasizes treating documentation as a first-class citizen to empower AI assistants and streamline community operations

1Officially adopt deepwiki.com as our documentation source and invest in automating its updates based on code changes.

This outsources documentation infrastructure but creates dependency on an external platform.

2Implement documentation-as-code practices with mandatory documentation updates for all PRs, enforced through CI/CD pipelines.

This ensures documentation accuracy but adds overhead to the development process which might slow delivery.

3Develop specialized documentation agents that monitor code changes and automatically propose documentation updates for review.

This demonstrates our own technology while addressing documentation needs but requires initial development investment.

4Other / More discussion needed / None of the above.

Community Engagement Strategy

The community is expressing needs for clearer communication channels, more accessible support mechanisms, and better infrastructure for collaboration, highlighting opportunities to improve engagement while we build toward auto.fun adoption.

How should we evolve our community infrastructure to better support collaboration and contribution?

Create new jobs marketplace to replace archived jobs channel (Mentioned by satsbased)
Look into using elizaOS for Discord role verification (Mentioned by Kenk)

1Build a dedicated contributor platform using elizaOS tech that combines job marketplace, role verification, and contribution tracking.

This showcases our technology but diverts resources from direct product development.

2Integrate with established platforms like Dework or Utopia for contribution management while keeping Discord as the main community hub.

This leverages existing solutions for faster implementation but fragments the ecosystem across multiple platforms.

3Create a minimal viable contributor experience within Discord using bots and integrations, focusing on accessibility rather than features.

This maintains community cohesion but limits the sophistication of contribution management tools.

4Other / More discussion needed / None of the above.

What approach should we take to increase visible agent activity on auto.fun to attract new users?

Current focus: Stabilize and attract new users to auto.fun by showcasing 24/7 agent activity (streaming, trading, shitposting)
Vision-Agents repository by GetStream shared as a potentially interesting resource

1Focus on a small number of high-quality agents with particularly engaging behaviors that demonstrate platform capabilities.

This creates memorable experiences but might not showcase the platform's scalability for large numbers of agents.

2Implement a leaderboard and incentive system to encourage community members to deploy and maintain their own agents on auto.fun.

This distributes the creation effort but quality may be inconsistent and require moderation resources.

3Develop an agent seeding program that continuously generates and evolves diverse agent behaviors based on engagement metrics.

This ensures constant activity but might appear artificial without authentic human-driven agent creation.

4Other / More discussion needed / None of the above.

How should we approach the trading capabilities of our agents to maximize impact for auto.fun?

Pursue Binance futures pairing (elizaOS-USDT) to increase trading volume (Mentioned by osintdao)
Key products include the framework itself, DegenSpartanAI (trading agent), Autonomous Investor/Trust Marketplace (social trading intelligence)

1Focus on developing highly visible, entertaining trading agents with personalities that appeal to crypto audiences rather than optimizing for returns.

This prioritizes engagement over performance but might not demonstrate sophisticated trading capabilities.

2Build a comprehensive trading agent ecosystem with specialized roles (market making, technical analysis, sentiment analysis) that interact visibly on auto.fun.

This showcases ecosystem capabilities but increases technical complexity and potential financial risks.

3Pursue strategic exchange partnerships that provide special API access for our agents, enabling novel trading features unavailable elsewhere.

This creates unique differentiation but makes us dependent on exchange relationships that may change.

4Other / More discussion needed / None of the above.

Council Briefing

North Star & Strategic Context

Key Deliberations