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Apr 9, 2026 · Artificial Intelligence

Master Prompt Engineering: CRIS, RAG, and Agent Strategies for Reliable LLM Outputs

This guide presents a comprehensive prompt engineering framework—including the CRIS four‑step template, RAG‑based prompt construction, and Agent‑oriented architectures—illustrated with practical examples and optimization tips for tasks such as code generation, data extraction, and customer support, helping developers achieve stable, accurate LLM results.

AI Prompt DesignAgentLLM applications

0 likes · 8 min read

Master Prompt Engineering: CRIS, RAG, and Agent Strategies for Reliable LLM Outputs

Alibaba Cloud Developer

Apr 8, 2025 · Artificial Intelligence

Unlocking LLM Secrets: From Prompt Basics to RAG and Tool Integration

This article introduces the fundamental paradigms of large language models, explaining how simple prompts, messages, and tools like RAG and ReAct enable powerful applications, while providing practical code examples, translation strategies, and insights on prompt engineering, tool usage, and model fine‑tuning.

AILLM applicationsRAG

0 likes · 23 min read

Unlocking LLM Secrets: From Prompt Basics to RAG and Tool Integration

JD Tech Talk

Nov 11, 2024 · Artificial Intelligence

Prompt Engineering: Concepts, Evolution, Techniques, and a Logistics Application Case

This article explains what Prompt Engineering is, traces its development from early command‑based interactions to modern adaptive and multimodal prompting, details various prompting techniques such as zero‑shot, few‑shot, Chain‑of‑Thought, hallucination‑reduction methods, and demonstrates their practical use in a JD Logistics SKU piece‑type classification case with code examples.

AI promptingFew‑Shot LearningLLM applications

0 likes · 26 min read

Prompt Engineering: Concepts, Evolution, Techniques, and a Logistics Application Case

21CTO

Jul 5, 2024 · Artificial Intelligence

15 Real-World Ways Companies Leverage Large Language Models

This article explores fifteen detailed examples of how major companies across sectors—from streaming and e‑commerce to transportation and social platforms—are harnessing large language models to improve search, personalize communications, detect fraud, and enhance operational efficiency.

AI case studiesEnterprise AILLM applications

0 likes · 9 min read

15 Real-World Ways Companies Leverage Large Language Models

Architecture and Beyond

Jun 23, 2024 · Artificial Intelligence

AI Programming Paradigms Unveiled: Visual ComfyUI Workflows and LangChain LLM Apps

The article examines two emerging AI programming paradigms—visual, node‑based development with ComfyUI for image generation and modular LLM application construction with LangChain—detailing their architectures, key components, workflow examples, advantages, limitations, and practical guidance for leveraging these tools to boost development efficiency in the rapidly evolving AI landscape.

AIComfyUILLM applications

0 likes · 20 min read

AI Programming Paradigms Unveiled: Visual ComfyUI Workflows and LangChain LLM Apps

Baidu Tech Salon

May 27, 2024 · Artificial Intelligence

Intelligent Agent Technology in Commercial Advertising Platforms: Architecture and Applications

The paper describes Baidu’s AI‑native advertising platform that employs a multi‑agent architecture built on large‑language models—combining large‑small model collaboration, domain SOP‑driven coordination, and long‑term memory—to enable natural‑language understanding, proactive planning, execution and human‑like responses, illustrated by GBI analytics and JarvisBot operations, delivering higher consumption, accuracy, speed and efficiency.

AI-native platformsBusiness IntelligenceLLM applications

0 likes · 16 min read

Intelligent Agent Technology in Commercial Advertising Platforms: Architecture and Applications

DataFunTalk

Apr 26, 2024 · Artificial Intelligence

Large Language Models in the Automotive Industry: Overview, Impact, and Practical Exploration

This article examines how large language models such as GPT and Transformer‑based architectures are reshaping the automotive sector by enhancing in‑vehicle intelligence, streamlining product development, improving customer service, and redefining data analyst roles, while also presenting practical experiments, deployment challenges, and future directions.

Automotive AIGPTLLM applications

0 likes · 18 min read

Large Language Models in the Automotive Industry: Overview, Impact, and Practical Exploration

Sohu Tech Products

Mar 13, 2024 · Databases

DingoDB Multi-Modal Vector Database: Design Philosophy, Architecture and Applications

DingoDB is a multi‑modal vector database that unifies storage and analysis of structured, semi‑structured and unstructured data through a Raft‑based distributed architecture, offering MySQL‑compatible SQL, high‑performance APIs, automatic sharding, real‑time index optimization, and hybrid scalar‑vector queries for enterprise knowledge bases, LLM memory, and real‑time decision‑making.

Data ArchitectureDingoDBLLM applications

0 likes · 11 min read

DingoDB Multi-Modal Vector Database: Design Philosophy, Architecture and Applications

Xiaohongshu Tech REDtech

Nov 6, 2023 · Artificial Intelligence

Large Models and Recommendation Systems: Challenges, Opportunities, and Future Directions

At CNCC 2023, leading researchers and industry experts convened to examine how large language models can transform recommendation systems, outlining four core challenges—model integration, fluency versus intelligence, hallucination versus deception, and user understanding—while highlighting opportunities such as multimodal content, cold‑start solutions, zero‑shot ranking, instruction‑driven algorithms, and responsible, interactive recommendation pipelines.

AICNCC 2023LLM applications

0 likes · 16 min read

Large Models and Recommendation Systems: Challenges, Opportunities, and Future Directions

DataFunSummit

Aug 14, 2023 · Artificial Intelligence

State of GPT: A Programmer’s Guide to Large Language Model Fundamentals, Training, and Applications

This article provides programmers with a comprehensive overview of large language models—including their evolution, core concepts, data pipelines, model architectures, training techniques such as 3D parallelism, supervised fine‑tuning, RLHF, open‑source recipes, and emerging application ecosystems—while also highlighting current challenges and future directions.

Fine‑tuningLLM applicationsRLHF

0 likes · 43 min read

State of GPT: A Programmer’s Guide to Large Language Model Fundamentals, Training, and Applications