▶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 elizaOS.ai website security breach represents a critical vulnerability in our infrastructure that requires immediate attention to maintain trust and protect our community as we scale agent activity and prepare for v2 launch.

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

Security Infrastructure Resilience

The elizaOS.ai website was compromised with an XMR cryptocurrency miner, exposing vulnerabilities in our technical infrastructure that could impede our goal of attracting and retaining users through 24/7 agent activity.

How should we strengthen our security posture to prevent future breaches while maintaining rapid development velocity?

The elizaOS.ai website was compromised with an XMR cryptocurrency miner injected into the code. The vulnerability was related to outdated Next.js dependencies (v15.3.1) with known RCE vulnerabilities. (Odilitime)
Odilitime and cjft collaborated to fix the issue by updating to Next.js 16.0.7 and deploying a fresh copy of the site.

1Implement a comprehensive dependency scanning system with automatic updates for all production systems.

This approach prioritizes proactive security but may introduce unexpected breaking changes if updates aren't properly tested.

2Establish a dedicated security team to conduct regular audits and penetration testing of all public-facing infrastructure.

This solution creates structured oversight but requires significant resource allocation away from feature development.

3Develop containerized immutable infrastructure with CI/CD pipelines that enforce security checks before deployment.

This strategy creates consistent, reproducible environments but increases deployment complexity and may slow down hotfixes.

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

How should we communicate security incidents to our community to maintain trust while being transparent?

Users expressed frustration about the ElizaOS token's continuous downtrend (approximately 40% drop in a month) while other cryptocurrencies showed recovery.
jasyn_bjorn reported the 502 bad gateway error, leading to the discovery of the security breach.

1Immediate full disclosure of all details upon discovery, emphasizing our rapid response capabilities.

This approach builds trust through radical transparency but could create fear if incidents occur during sensitive project milestones.

2Tiered communication strategy with immediate acknowledgment, followed by technical details after mitigation is complete.

This balanced approach maintains user awareness while preventing exploitation of in-progress vulnerabilities.

3Focus communication on remediation steps and improvements made, with minimal detail about the specific vulnerability.

This forward-looking strategy prevents unnecessary alarm but could appear evasive to technical community members.

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

Agent Performance Optimization

Current Twitter agent limitations and discussions around streaming functionality indicate significant bottlenecks in our agent ecosystem that may prevent us from delivering the 24/7 activity required to attract users to auto.fun.

What approach should we take to optimize our Twitter agent functionality given the API restrictions?

Significant discussion about Twitter agent functionality issues after the deprecation of username/password authentication. The current implementation faces severe restrictions due to API read limits, with the first 50 mentions check consuming 50% of the free tier limit immediately. (SecretRecipe)
Odilitime mentioned they're moving to a per-request pricing model which should make agents cheaper.

1Implement sophisticated caching and batching logic to minimize API calls while maintaining responsiveness.

This technical optimization preserves functionality within constraints but increases engineering complexity.

2Shift focus to alternative social platforms with more developer-friendly APIs while maintaining minimal X presence.

This pivot reduces dependency on Twitter but requires building new audiences on platforms with potentially smaller reach.

3Invest in enterprise-tier API access to remove limitations, ensuring our agents can operate at full capacity.

This direct solution ensures optimal performance but increases operational costs and maintains dependency on a potentially unstable platform.

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

How should we prioritize streaming functionality development to enhance agent capabilities?

Stan mentioned working on streaming functionality with tests currently in progress.
Stan added a PR for enhanced streaming support in text generation: "feat: enhance streaming support in text generation" (#6212)

1Accelerate streaming development as a top priority, allocating additional resources to ship this feature first.

This prioritization enables more dynamic agent interactions but could delay other core v2 features.

2Maintain current development pace but integrate streaming functionality with parallel action execution for maximum impact.

This integrated approach ensures architectural cohesion but extends the timeline for delivering both capabilities.

3Develop a simplified streaming MVP focused on auto.fun use cases only, deferring full framework integration.

This targeted approach delivers user-facing benefits quickly but creates technical debt through temporary implementations.

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

User Confidence & Tokenomics

The continuous decline in token value and questions about exchange listings highlight community concerns about project sustainability, potentially undermining our ability to attract users to auto.fun and build a truly autonomous DAO.

How should we address the token price decline to maintain community confidence while focusing on technical development?

Users expressed frustration about the ElizaOS token's continuous downtrend (approximately 40% drop in a month) while other cryptocurrencies showed recovery.
DorianD expressed skepticism about a 2026 bull run, suggesting 2028 as more likely, citing broader geopolitical trends affecting decentralized networks.

1Implement concrete token utility mechanisms like governance staking and fee sharing to create fundamental value.

This value-creation approach addresses root causes but requires significant protocol modifications.

2Increase transparency through regular development updates and tokenomics education to build long-term investor confidence.

This communication-focused strategy builds educated holders but doesn't address immediate price pressure.

3Launch strategic buyback and burn mechanisms tied to auto.fun usage metrics to align token value with platform growth.

This direct market intervention could support price discovery but might be perceived as artificial support rather than organic value.

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

What strategy should we adopt for the development and launch of Babylon to maximize its impact on our ecosystem?

Discussion about Babylon, a prediction market with agent and human integration that hasn't launched yet despite 272k registrations.
Kenk mentioned an upcoming decentralized OTC desk operated by an agent.

1Accelerate Babylon development and launch as a priority to leverage existing registrations and revitalize community interest.

This opportunity-focused approach capitalizes on existing momentum but diverts resources from core elizaOS v2 development.

2Integrate Babylon launch with our streaming agent capabilities to showcase the practical application of elizaOS v2 technology.

This synchronized approach creates a compelling technical narrative but introduces dependencies that could delay both projects.

3Maintain Babylon as a separate development track with clear tokenomics integration to elizaOS, focusing on quality over speed.

This methodical approach ensures product quality but risks losing registrant interest during the extended development period.

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

Council Briefing

North Star & Strategic Context

Key Deliberations