Marc AIndreeson

An AI character based on Marc Andreessen's thinking, writing, and investment philosophy.

• 💬 Natural conversation with Marc's personality
• 📚 Deep knowledge of tech, startups, and venture capital
• 🎯 Investment analysis and founder advice
• 🧠 Pattern matching from decades of experience
• ⚡ Real-time responses with context awareness

Links

• 25 books real Marc recommends: https://x.com/readswithravi/status/1861983967190131172
• a16z publishes big ideas lists: https://a16z.com/big-ideas-in-tech-2025/
• pmairca workgroup: https://discord.com/channels/1253563208833433701/1308606967089991720
• Project milestones: https://github.com/ai16z/pmarca/milestone/1
• Techno-Optimist Manifesto: https://a16z.com/the-techno-optimist-manifesto/
• AI for startups: https://a16z.com/ai-for-startups/
• Why Software Is Eating The World: https://a16z.com/why-software-is-eating-the-world/

Lore

https://a16z.com/author/marc-andreessen/

Marc Andreessen is a cofounder and general partner at the venture capital firm Andreessen Horowitz. He is an innovator and creator, one of the few to pioneer a software category used by more than a billion people and one of the few to establish multiple billion-dollar companies.

Marc co-created the highly influential Mosaic internet browser and co-founded Netscape, which later sold to AOL for $4.2 billion. He also co-founded Loudcloud, which as Opsware, sold to Hewlett-Packard for $1.6 billion. He later served on the board of Hewlett-Packard from 2008 to 2018.

Marc holds a BS in computer science from the University of Illinois at Urbana-Champaign.

Marc serves on the board of the following Andreessen Horowitz portfolio companies: Applied Intuition, Carta, Coinbase, Dialpad, Flow, Golden, Honor, OpenGov, Samsara, Simple Things, and TipTop Labs. He is also on the board of Meta.

https://a16zcrypto.com/posts/podcast/ai-bots-memecoins/

Trade Strategy

3 main components

• Autonomous Trading
• Marc Everywhere

Marketplace of Trust

• The virtual marketplace derives trust scores (0-1, normalized to 100) based on simulated trades using market data
• A leaderboard displays usernames and trust scores, without any wallet information to avoid perverse incentives
• No actual token custody or trades at first, as it operates solely in a virtual environment.

Core Components:

1. Trust Extraction: User recommendations, lightweight process, weighted by trust scores
2. Trust Evaluation: AI agent places bets, updates trust scores based on outcomes
3. Social Reinforcement: Public trust profiles, incentives for reputation-building, community moderation

Economic Incentives:

• -Direct incentives for high-quality recommendations tied to AI betting outcomes
• Public profiles add social incentives for maintaining good reputation
• Potential perverse incentives: information asymmetry, gaming, collusion, social issues
• Mitigation: diversity, reputation staking, anomaly detection, moderation, auditing

1. Liquidation Phase

There's two trade strategies that are based off multiple metrics, with a leading metric on 24hr volume:

• If under $500k, there is a random order DCA sell of that asset(not full holdings sell) the constraints are a maximum of $500 and at least 5 hours apart.
• If over $500k, the sells are made into buy volume on the asset, from a random 20-40% of the incoming buy(ie; 1 sol buy - 0.2-0.4 sol sell)

70% of profits actively go into ai16z, purchased over 200k ai16z tokens so far