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ai-agent
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AI Agent Harness Engineering Architecture & Runtime Cheat Sheet
A comprehensive reference guide to AI Agent Harness engineering and runtime scaffolds: comparing bare LLMs against harnessed agents, exploring the 6 core pillars of harness architecture, detailing a 10-step closed-loop bug-fixing workflow, and comparing top industrial harnesses (Claude Code, Devin, SWE-agent, OpenHands) with 5 golden engineering rules.
AI Agent Skill Architecture & Development Cheat Sheet
A comprehensive cheat sheet for AI Agent Skill architecture: comparing casual chat vs skill-based execution, detailing the 4 core components of a production skill, analyzing the 5-tier Prompt/Tool/Skill/Workflow/Agent hierarchy, and providing a standardized SKILL.md template with 5 golden engineering rules.
Four Leading Always-on Autonomous Agents Comparison Cheat Sheet: Meta Muse, Grok Bot, OpenAI dots, and Manus Cue
A comprehensive comparative cheat sheet analyzing 4 leading Always-on persistent AI agents (Meta Muse, Grok Bot, OpenAI dots, Manus Cue): evaluating product positioning, persistent cloud environments, real-world execution, digital identity, multi-agent swarms, and decision selection matrices.
Modern Authentication & Authorization Architecture 12-Layer Panoramic Cheat Sheet
A comprehensive reference guide to modern authentication (AuthN) and authorization (AuthZ) across a 12-layer architecture: from password hashing (Argon2id/bcrypt), server sessions, JWT lifecycle, OAuth 2.0+PKCE, and FIDO2 Passkeys, to RBAC/ABAC/ReBAC models, OPA/Cedar policy engines, enterprise SSO/SCIM, workload mTLS/SPIFFE, and autonomous AI Agent delegation.
Cross-Border E-Commerce AI Agent Architecture & Multi-Agent Collaboration Cheat Sheet
A 5-tier reference sheet for cross-border e-commerce AI Agent system architecture: touchpoints, 6 multi-role collaborative agents and orchestrator, tool & capability integration, data governance lakehouse and vector DB, and cloud infrastructure.
LLM & AI Agent Technical Concepts Master Cheat Sheet
A comprehensive reference taxonomy of modern Large Language Models (LLMs) and Autonomous AI Agents across 8 technical tiers: Foundations, Model Architecture, Intelligence, Knowledge Augmentation, Agent Core, Engineering, Governance, and Applications, featuring deep dives on RoPE, Tool vs Skill, and MCP vs A2A.