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AI & Automation

Explore the topics and references in this collection.

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.

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Modern AI Chips & Data Center Compute Architectures Cheat Sheet: CPU, GPU, TPU, LPU, NPU, DPU & Global Silicon Selection

A high-density reference guide to modern AI data center and edge compute silicon: covering CPU, GPU, TPU, LPU, NPU, DPU architectures, global silicon ecosystems (Huawei Ascend, Cambricon, Hygon, AWS Trainium, Meta MTIA, Microsoft Maia), Prefill/Decode disaggregation topologies, LLM VRAM/bandwidth sizing formulas, and nvidia-smi/npu-smi cluster operations.

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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.

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Technological Revolutions & Artificial Intelligence Evolution Master Cheat Sheet

A comprehensive comparative reference guide examining humanity's four industrial and technological revolutions (Steam, Electricity, Computing/Internet, and AI): analyzing core drivers, diffusion cycles, factor substitution, AGI/ASI evolutionary roadmaps, and social-organizational transformations.

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Neural Networks Evolution History & Landmark AI Papers Cheat Sheet

A comprehensive reference guide charting the evolution of neural networks and deep learning (1850s to present): covering 8 historical eras, 18 seminal landmark papers, architectural transitions, core bottlenecks solved, and an analysis of the 4 foundational unsolved challenges in modern AI.

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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.

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AI Image Generation Models Tier List & Evaluation Cheat Sheet

A comprehensive tier list and production evaluation cheat sheet for frontier AI image generation models: benchmarking SSS-tier flagships, Tier 1 powerhouses, and specialized models across photorealism, typography precision, multi-turn consistency, inpainting, and vector export.

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Claude Code CLI Commands & Slash Commands Cheat Sheet

A compact reference guide for Anthropic's official terminal AI coding agent Claude Code: covering CLI startup flags, interactive slash commands (context management, permissions, code review, MCP extensions), keyboard shortcuts, and CLAUDE.md configuration patterns.

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Core AI Algorithms Cheat Sheet: From Classical ML to Foundation Models & Vector Search

A production-tested reference guide distilling the 27 most essential algorithms used in modern AI engineering: covering classical supervised learning, gradient-boosted trees, clustering and vector search (HNSW), deep architectures and optimizers (AdamW), and LLM alignment (DPO, PPO).

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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.

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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.

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