5 guides
AI Agents
Designing a Second Brain for AI Agents: The Vault-as-Database Pattern
How to architect a local knowledge base that AI agents can reason over — starting from Karpathy's three-folder reference architecture, through the three-layer memory stack, MCP bridges, quality maintenance, and the scaling path from flat files to SQLite.
The Social Nature of AI Intelligence: From Societies of Thought to Agent Governance
Why intelligence is inherently social — how reasoning models spontaneously generate internal debates, why the singularity vision is wrong, the human-AI centaur era, and the constitutional design principles for governing billions of interacting agents.
Building Multi-Agent Orchestration Systems: From Single Agents to Coordinated Teams
A practical guide to designing agent coordination systems — covering orchestrator patterns, sub-agent delegation, cost optimization strategies, MCP tool integration, and the memory/self-improvement loops that make agent teams compound over time.
What Is Autoresearch and How to Use It
Autoresearch is Karpathy's hill-climbing optimization loop — make one change, test against a binary checklist, keep or revert, repeat. This guide covers the core method, practical implementation with Claude skills, scaling to parallel GPU clusters and distributed agent swarms, and the emerging pattern of full-stack AI research agents.
Claude & Claude Code for Marketing Agencies: A Detailed Guide
A comprehensive guide covering agency workspace setup, content strategy, competitive intelligence, outbound automation, brand design workflows, and agency-specific Claude Code skills — grounded in 77+ sources.