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Data Thinking Notes

Sharing insights on data architecture, governance, and middle platforms, exploring AI in data, and linking data with business scenarios.

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Latest from Data Thinking Notes

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Data Thinking Notes

Feb 8, 2026 · Artificial Intelligence

How OpenClaw Turns AI into a Hands‑On Digital Assistant (Local‑First, Open‑Source)

OpenClaw is an open‑source, local‑first AI agent platform that acts as a digital employee capable of autonomously executing tasks on your computer, offering multi‑channel interaction, persistent memory, and a modular architecture that bridges the gap between conversational AI and real‑world operations.

AI AgentAutomationDocker deployment

0 likes · 13 min read

How OpenClaw Turns AI into a Hands‑On Digital Assistant (Local‑First, Open‑Source)

Data Thinking Notes

Jan 25, 2026 · Artificial Intelligence

Why Anthropic Switched from Specialized Agents to Skills—and What It Means for AI Development

Anthropic’s technical blog explains the shift from building domain‑specific agents to creating reusable Agent Skills, detailing the new code‑centric paradigm, progressive disclosure, skill ecosystem, real‑world examples in finance and healthcare, and the emerging architecture that unifies agents, runtimes, MCP servers, and skill libraries.

AI agentsAgent SkillsClaude

0 likes · 14 min read

Why Anthropic Switched from Specialized Agents to Skills—and What It Means for AI Development

Data Thinking Notes

Jan 11, 2026 · Artificial Intelligence

How Anthropic’s Agent Skills Turn Claude into a Customizable Expert Assistant

Anthropic’s Agent Skills, introduced in October 2025, package procedural knowledge into structured SKILL.md files that the Claude model can discover and load on demand, dramatically improving token efficiency, workflow automation, and domain‑specific expertise without requiring extensive prompt engineering.

AI pluginsAgent SkillsClaude

0 likes · 15 min read

How Anthropic’s Agent Skills Turn Claude into a Customizable Expert Assistant

Data Thinking Notes

Nov 16, 2025 · Artificial Intelligence

How AI Agents Transform Automation: Architecture, Challenges & Future Trends

This comprehensive overview examines AI agents powered by large language models, detailing their definition, core components, architectural patterns, key technologies such as prompt engineering and retrieval‑augmented generation, diverse application domains, current challenges, security solutions, and emerging research directions.

ArchitectureRetrieval-Augmented Generationlarge language models

0 likes · 81 min read

How AI Agents Transform Automation: Architecture, Challenges & Future Trends

Data Thinking Notes

Nov 9, 2025 · Artificial Intelligence

From Hype to Reality: How Enterprise AI Agents Are Gaining Real‑World Impact

Tencent Cloud and Tencent Research Institute, together with Gartner, released a comprehensive report that outlines evaluation methods, challenges, and practical solutions for deploying enterprise AI agents, introducing an innovative "AI Agent Scenario Compass" to help companies assess maturity and plan implementation roadmaps.

AI agentsAI roadmapEnterprise AI

0 likes · 5 min read

From Hype to Reality: How Enterprise AI Agents Are Gaining Real‑World Impact

Data Thinking Notes

Nov 2, 2025 · Artificial Intelligence

Why Data Governance Is the Key to Trustworthy AI in the Large Model Era

The article explains how the rapid rise of large‑model AI has shifted the focus from models to data, outlines the concept and stages of AI‑specific data governance, identifies challenges such as low‑quality data, privacy leaks, bias, and proposes a comprehensive framework of principles, processes, and technologies to ensure high‑quality, secure, and ethical AI deployment.

AIData qualityEthics

0 likes · 40 min read

Why Data Governance Is the Key to Trustworthy AI in the Large Model Era

Data Thinking Notes

Oct 19, 2025 · Artificial Intelligence

How GSPO Improves Stability in Large Language Model Training

GSPO (Group Sequence Policy Optimization) is a reinforcement‑learning algorithm for LLMs that replaces token‑level GRPO with sequence‑level optimization, addressing instability in ultra‑large model training, especially for long‑sequence and MoE architectures, by aligning reward granularity and reducing variance.

GRPOGSPOlarge language models

0 likes · 11 min read

How GSPO Improves Stability in Large Language Model Training

Data Thinking Notes

Oct 12, 2025 · Artificial Intelligence

Mastering AI Agent Planning: Architectures, Strategies, and Real-World Implementations

This article provides a comprehensive guide to AI Agent planning modules, covering their core responsibilities, architectural designs, major planning paradigms such as ReAct, Plan‑and‑Execute, Hierarchical Planning and Reflexion, detailed prompt engineering, execution frameworks, and practical case studies in data analysis and intelligent customer service.

AI PlanningAgent architectureReAct

0 likes · 25 min read

Mastering AI Agent Planning: Architectures, Strategies, and Real-World Implementations

Data Thinking Notes

Oct 9, 2025 · Artificial Intelligence

Mastering Context Engineering: Boost LLM Agent Performance

Context Engineering, the evolution beyond Prompt Engineering, optimizes the selection and management of tokens within large language model windows, enabling high‑performance, autonomous AI agents through efficient system prompts, tool design, example selection, dynamic retrieval, compression, structured memory, and multi‑agent architectures.

AI OptimizationContext EngineeringLLM agents

0 likes · 19 min read

Mastering Context Engineering: Boost LLM Agent Performance

Data Thinking Notes

Sep 24, 2025 · Artificial Intelligence

How AI Agents Are Transforming Smart Logistics at SF Express

This article explains how SF Express leverages AI agents and large language models to create a full‑process intelligent management framework that optimizes order forecasting, dynamic scheduling, resource allocation, and operational decision‑making across the entire logistics chain.

AIIntelligent AgentsLogistics

0 likes · 21 min read

How AI Agents Are Transforming Smart Logistics at SF Express