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Prompt Engineering

1599 articles · Page 12 of 16
Alibaba Cloud Developer
Alibaba Cloud Developer
Oct 30, 2025 · Artificial Intelligence

Why AI Agents Aren’t As Simple As They Appear: Engineering Challenges and Solutions

Building AI agents may seem straightforward with frameworks like LangChain, but hidden complexities in orchestration, memory management, reproducibility, and scalability turn simple demos into fragile systems, requiring systematic engineering, observability, and robust design to achieve reliable, production‑grade intelligent agents.

AI AgentsAgent designLangChain
0 likes · 21 min read
Why AI Agents Aren’t As Simple As They Appear: Engineering Challenges and Solutions
Xiaolong Cloud Tech Team
Xiaolong Cloud Tech Team
Oct 28, 2025 · Artificial Intelligence

How Claude Skills Redefine AI Agent Architecture: A Deep Dive

This article explains the design, three‑layer architecture, registration process, intent routing, security model, and practical comparisons of Anthropic's Claude Skills, showing how they extend LLM capabilities beyond prompts and function calling.

AI AgentsAnthropicClaude Skills
0 likes · 15 min read
How Claude Skills Redefine AI Agent Architecture: A Deep Dive
Code Mala Tang
Code Mala Tang
Oct 28, 2025 · Artificial Intelligence

Unlocking AI Creativity with Just Eight Words: The Verbalized Sampling Breakthrough

A recent Stanford and West Virginia University study reveals that a simple eight‑word prompt technique, called Verbalized Sampling, can double the creative output of large language models without costly retraining, by exposing hidden diversity suppressed by conventional alignment methods.

AI creativityLLM sampling techniquesLarge Language Models
0 likes · 9 min read
Unlocking AI Creativity with Just Eight Words: The Verbalized Sampling Breakthrough
Tencent Technical Engineering
Tencent Technical Engineering
Oct 27, 2025 · Artificial Intelligence

How AI Programming Is Transforming Software Development – A Practical Guide

This article explores the strategic impact of AI‑assisted coding, outlines a comprehensive AI × SDLC methodology, showcases three real‑world scenarios—from end‑to‑end development pipelines to Figma‑to‑code automation and backend system evolution—while highlighting practical tips, pitfalls, and organizational changes needed to fully harness AI programming.

DevOpsPrompt Engineeringquality assurance
0 likes · 71 min read
How AI Programming Is Transforming Software Development – A Practical Guide
大转转FE
大转转FE
Oct 27, 2025 · Frontend Development

5 Essential Tech Articles This Week: Frontend Innovations, AI Agents, and Testing Breakthroughs

This weekly roundup curates five insightful articles covering the evolution of a frontend collaboration tool, the rise of context engineering in AI, the design of an AI‑assisted coding plugin, the debate over AI versus human task planning, and AI‑driven test case generation at scale.

Artificial IntelligencePrompt EngineeringTesting automation
0 likes · 4 min read
5 Essential Tech Articles This Week: Frontend Innovations, AI Agents, and Testing Breakthroughs
KooFE Frontend Team
KooFE Frontend Team
Oct 26, 2025 · Artificial Intelligence

Master Zero-Shot Prompting: Advanced Techniques to Boost LLM Performance

Zero-shot prompting lets large language models perform tasks without examples, and by following principles of clarity and structured instructions, advanced strategies such as emotion prompting, zero-shot chain-of-thought, RE2 re-reading, Rephrase-and-Respond, role-play, and System-2 Attention can significantly improve accuracy and response quality across translation, reasoning, and QA tasks.

AI reasoningLLMLarge Language Models
0 likes · 13 min read
Master Zero-Shot Prompting: Advanced Techniques to Boost LLM Performance
Wuming AI
Wuming AI
Oct 23, 2025 · Artificial Intelligence

How I Built a Hand‑Counting Calculator in 5 Minutes with WeaveFox AI

In just five minutes, I used the WeaveFox AI coding platform to recreate a quirky "hand‑counting" calculator by prompting natural language, iterating through form‑based tech‑stack selection, and letting multiple AI agents generate, refine, and deploy the full front‑end application.

AI codingPrompt EngineeringWeaveFox
0 likes · 7 min read
How I Built a Hand‑Counting Calculator in 5 Minutes with WeaveFox AI
DaTaobao Tech
DaTaobao Tech
Oct 22, 2025 · Artificial Intelligence

How AI Coding Transforms Complex Client Development: Methods, Challenges, and Efficiency Gains

This article reveals the core methodology of applying AI coding to complex client-side development, discusses practical challenges, prompt design, task decomposition, efficiency improvements, and provides actionable guidelines and architectural rules for integrating AI into UI and service layers.

AI codingPrompt EngineeringSoftware Architecture
0 likes · 15 min read
How AI Coding Transforms Complex Client Development: Methods, Challenges, and Efficiency Gains
DataFunTalk
DataFunTalk
Oct 22, 2025 · Artificial Intelligence

How Large Language Models Power Xiaomi’s Xiao AI Assistant

This article explains how Xiaomi’s Xiao AI assistant leverages large language models for intent routing, domain‑specific intent understanding, and response generation, detailing the system architecture, challenges such as knowledge requirements and latency constraints, and the shift from prompt engineering to model fine‑tuning.

AI assistantIntent RoutingLarge Language Models
0 likes · 5 min read
How Large Language Models Power Xiaomi’s Xiao AI Assistant
Instant Consumer Technology Team
Instant Consumer Technology Team
Oct 21, 2025 · Artificial Intelligence

Master Claude Code with GLM‑4.6: Install, Configure, and Boost Your Coding Productivity

This guide explains why the Claude Code + GLM‑4.6 combo outperforms other AI coding tools, details how to overcome access hurdles, walks through installing Node.js and Claude Code, configuring GLM‑4.6 via environment variables, and demonstrates using natural‑language prompts for tasks ranging from simple web games to complex web‑scraping scripts.

AI coding assistantClaude CodeGLM 4.6
0 likes · 11 min read
Master Claude Code with GLM‑4.6: Install, Configure, and Boost Your Coding Productivity
Wuming AI
Wuming AI
Oct 20, 2025 · Artificial Intelligence

How to Let AI Instantly Draw Professional UML Diagrams with Mermaid

This article walks through using large language models such as Claude, Gemini, DeepSeek, and Kimi to generate accurate, colorful UML diagrams via Mermaid syntax, covering model selection, prompt engineering, step‑by‑step demonstrations, and practical tips for reliable AI‑driven diagram creation.

AI‑generated diagramsLarge Language ModelsMermaid
0 likes · 5 min read
How to Let AI Instantly Draw Professional UML Diagrams with Mermaid
DataFunTalk
DataFunTalk
Oct 18, 2025 · Artificial Intelligence

Why Users Call Gemini ‘HakiMi’: The Rise of AI Personas and Community‑Driven Tuning

The article explores how Chinese netizens affectionately nickname Google’s Gemini model ‘HakiMi’, examining the cultural phenomenon, the model’s distinctive conversational quirks, the community’s deep‑level prompt engineering, and the broader debate over AI personality definition, user ownership, and regulatory implications.

AI ethicsAI personasGemini
0 likes · 12 min read
Why Users Call Gemini ‘HakiMi’: The Rise of AI Personas and Community‑Driven Tuning
Instant Consumer Technology Team
Instant Consumer Technology Team
Oct 17, 2025 · Artificial Intelligence

Mastering Context Engineering for AI Agents: Overcome Overload with Smart Strategies

This article distills Anthropic’s “Effective Context Engineering for AI Agents” into key insights, explaining why context engineering matters, how it differs from prompt engineering, what constitutes good practice, and practical techniques—system prompts, tool design, few‑shot prompting, compaction, structured note‑taking, and sub‑agent architectures—to mitigate context overload in large language model agents.

AI AgentsAgent designContext Engineering
0 likes · 10 min read
Mastering Context Engineering for AI Agents: Overcome Overload with Smart Strategies
Xiaolong Cloud Tech Team
Xiaolong Cloud Tech Team
Oct 17, 2025 · Artificial Intelligence

How Six Agents Tackle Complex Commands and Tool Bloat in AI Data Generation

The article analyzes the evolution from a single‑agent LLM pipeline to a six‑agent architecture that separates intent recognition, tool filtering, reasoning, and summarization, enabling precise handling of complex user queries, efficient tool selection from thousands, and faster, more reliable AI‑driven data generation.

AI AgentsLLM IntegrationPrompt Engineering
0 likes · 25 min read
How Six Agents Tackle Complex Commands and Tool Bloat in AI Data Generation
BirdNest Tech Talk
BirdNest Tech Talk
Oct 17, 2025 · Artificial Intelligence

How to Extend Claude with Custom Agent Skills Using SKILL.md

Claude’s new Agent Skills let developers package domain expertise into organized SKILL.md files and resource folders, enabling progressive disclosure, code execution, and scalable context loading, with detailed guidance on structure, bundling, evaluation, and security considerations for building robust, reusable AI agents.

AI AgentsAgent SkillsClaude
0 likes · 11 min read
How to Extend Claude with Custom Agent Skills Using SKILL.md
Alibaba Cloud Native
Alibaba Cloud Native
Oct 16, 2025 · Artificial Intelligence

How Spring AI Alibaba Admin Powers Data‑Centric AI Agent Development and Ops

This article outlines the industry shift toward large‑scale AI Agent deployment, identifies key engineering challenges such as prompt management, quality assessment, and observability, and presents Spring AI Alibaba Admin—a cloud‑native platform that offers prompt, dataset, evaluator, and tracing capabilities, complete with setup instructions and future roadmap.

AI AgentJavaNacos
0 likes · 15 min read
How Spring AI Alibaba Admin Powers Data‑Centric AI Agent Development and Ops
Java Tech Enthusiast
Java Tech Enthusiast
Oct 16, 2025 · Artificial Intelligence

When AI Becomes Your Boss: A Content Expert’s Rise and Layoff

The article examines how AI's rapid adoption in 2025 workplaces, illustrated by Kevin Cantera’s experience of boosting productivity only to be replaced during layoffs, reveals a deeper power shift where tools dictate processes, employees must master AI fundamentals, and organizations face mixed efficiency outcomes.

AI adoptionAI governanceAI layoffs
0 likes · 7 min read
When AI Becomes Your Boss: A Content Expert’s Rise and Layoff
Tencent Cloud Developer
Tencent Cloud Developer
Oct 15, 2025 · Artificial Intelligence

Why LLMs Are Unreliable: The pⁿ Dilemma and Building Trustworthy AI‑Human Collaboration

The article explains that large language models are fundamentally probabilistic predictors, causing their success rate to drop exponentially with task complexity (the pⁿ dilemma), and proposes a systematic, human‑centered approach—using deterministic tools, narrowing prompt scope, and delivering incremental results—to create reliable AI‑human collaborative systems.

AI-human collaborationLLM reliabilityPrompt Engineering
0 likes · 66 min read
Why LLMs Are Unreliable: The pⁿ Dilemma and Building Trustworthy AI‑Human Collaboration
Alibaba Cloud Developer
Alibaba Cloud Developer
Oct 15, 2025 · Artificial Intelligence

Mastering Structured Output in Large Language Models: Techniques, Challenges, and Future Trends

Large language models are evolving from free‑form text generators to reliable data providers by mastering structured output through prompt engineering, validation frameworks, constrained decoding, supervised fine‑tuning, reinforcement learning, and API‑level capabilities, enabling seamless integration with software systems while addressing hallucinations and format reliability.

APIEvaluationLLM
0 likes · 28 min read
Mastering Structured Output in Large Language Models: Techniques, Challenges, and Future Trends
Huawei Cloud Developer Alliance
Huawei Cloud Developer Alliance
Oct 15, 2025 · Artificial Intelligence

Unlocking AI Agents: From Fundamentals to Cutting‑Edge Applications

This article provides a comprehensive overview of AI agents, explaining their core concepts, architecture, memory and planning mechanisms, tool integration, key prompting techniques such as Chain‑of‑Thought and Tree‑of‑Thought, and showcases real‑world case studies and future trends that illustrate how AI agents extend large language models to automate complex tasks.

AI AgentPrompt Engineering
0 likes · 40 min read
Unlocking AI Agents: From Fundamentals to Cutting‑Edge Applications
Xiaolong Cloud Tech Team
Xiaolong Cloud Tech Team
Oct 13, 2025 · Artificial Intelligence

Building Reliable AI Agents: A Practical Guide from Prompt Engineering to Workflows and Knowledge Bases

This article systematically explains how to build a reliable, production‑ready AI agent by covering its core architecture—LLM, prompts, workflow, RAG, and tools—detailing prompt‑engineering techniques, DSL‑based workflow design, knowledge‑base construction, security considerations, and project planning methods.

AI AgentLLMPrompt Engineering
0 likes · 17 min read
Building Reliable AI Agents: A Practical Guide from Prompt Engineering to Workflows and Knowledge Bases
AI Large Model Application Practice
AI Large Model Application Practice
Oct 13, 2025 · Artificial Intelligence

How to Tame LLM Agents: Proven Strategies to Reduce Uncertainty and Boost Reliability

This article outlines practical techniques—including prompt engineering, domain fine‑tuning, retrieval‑augmented generation, structured outputs, workflow constraints, model parameter control, behavior rules, risk‑based AI participation, and comprehensive governance—to curb the unpredictability of large language model agents in enterprise settings.

AI AgentAI governanceLLM
0 likes · 18 min read
How to Tame LLM Agents: Proven Strategies to Reduce Uncertainty and Boost Reliability
Data Thinking Notes
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 planningPrompt EngineeringReAct
0 likes · 25 min read
Mastering AI Agent Planning: Architectures, Strategies, and Real-World Implementations
Architect
Architect
Oct 10, 2025 · Artificial Intelligence

How AI Pair Programming Reinvents the Full Development Lifecycle with PDCA

This article systematically explores how AI‑augmented pair programming can be applied across the entire software development process, using the PDCA (Plan‑Do‑Check‑Act) loop, and provides practical guidance on prompt engineering, context engineering, and three typical scenarios—production delivery, rapid validation, and experimental exploration—while sharing personal insights and future outlooks.

AIPDCAPrompt Engineering
0 likes · 17 min read
How AI Pair Programming Reinvents the Full Development Lifecycle with PDCA
Baidu Tech Salon
Baidu Tech Salon
Oct 10, 2025 · Artificial Intelligence

Navigating the 2025 AI Model Boom: Practical Evaluation Strategies

This article examines the rapid surge of large AI models in 2024‑2025, critiques the reliability of public leaderboards, and presents a business‑focused evaluation framework—including dataset construction, metric selection, automation, and LLM‑as‑judge techniques—to help developers choose the right model for real‑world applications.

AI benchmarksAI performanceDataset Construction
0 likes · 17 min read
Navigating the 2025 AI Model Boom: Practical Evaluation Strategies
DataFunTalk
DataFunTalk
Oct 10, 2025 · Artificial Intelligence

How Large Language Models Power Xiaomi’s Xiao AI Assistant

This article explains how large language models are integrated into Xiaomi’s Xiao AI assistant, covering intent distribution, domain‑specific intent understanding, response generation, architectural design, challenges such as knowledge requirements and latency, and the shift from prompt engineering to model fine‑tuning.

AI assistantIntent RoutingLarge Language Models
0 likes · 5 min read
How Large Language Models Power Xiaomi’s Xiao AI Assistant
DaTaobao Tech
DaTaobao Tech
Oct 9, 2025 · Artificial Intelligence

From Prompt to Context Engineering: How Language Formalization Boosts AI Reliability

The article explains how AI is shifting from low‑formal Prompt Engineering to medium‑formal Context Engineering by applying language formalization concepts such as the Chomsky hierarchy, improving traceability, reliability, and system verification while sacrificing some unrestricted LLM expressiveness.

AI reliabilityContext EngineeringLanguage Formalization
0 likes · 14 min read
From Prompt to Context Engineering: How Language Formalization Boosts AI Reliability
Xiaolong Cloud Tech Team
Xiaolong Cloud Tech Team
Oct 9, 2025 · Artificial Intelligence

Stop Collecting ‘God‑Level’ Prompts – Master Prompt Engineering Through Practice

The article argues that hoarding countless prompt examples is futile and instead teaches a three‑step, practice‑driven method—drafting a raw prompt, using AI to refine it, and iteratively polishing through real‑world testing—while emphasizing top‑down planning and the importance of personal experience.

AIIterative DevelopmentPractical Guide
0 likes · 5 min read
Stop Collecting ‘God‑Level’ Prompts – Master Prompt Engineering Through Practice
DataFunTalk
DataFunTalk
Oct 6, 2025 · Artificial Intelligence

Mastering Context Engineering: 5 Proven Strategies to Boost AI Agent Performance

This article explores the emerging concept of context engineering for AI agents, explains why managing long‑range context is critical, and details five practical strategies—Offload, Reduce, Retrieve, Isolate, and Cache—backed by insights from leading industry teams and the "Bitter Lesson" philosophy.

AI AgentsContext EngineeringLLM Optimization
0 likes · 30 min read
Mastering Context Engineering: 5 Proven Strategies to Boost AI Agent Performance
DataFunSummit
DataFunSummit
Oct 5, 2025 · Artificial Intelligence

How Baidu’s AI‑Powered Code Assistant Is Revolutionizing Software Development

In this detailed presentation, Baidu’s engineering manager Yang Jingwei explains the current landscape, emerging trends, key challenges, data pipelines, model training, prompt engineering, multi‑platform support, and future outlook of Baidu’s intelligent code assistant and AI IDE, illustrating practical solutions and real‑world impact.

AI code assistantData PipelinePrompt Engineering
0 likes · 26 min read
How Baidu’s AI‑Powered Code Assistant Is Revolutionizing Software Development
DataFunSummit
DataFunSummit
Oct 5, 2025 · Artificial Intelligence

How Xiaomi’s XiaoAI Harnesses Large Models for Intent Routing and Response Generation

This article explains how Xiaomi’s XiaoAI assistant integrates large language models for intent distribution, vertical intent understanding, and response generation, detailing the architecture, challenges such as knowledge requirements and sub‑200 ms latency, and the shift from prompt engineering to model fine‑tuning that boosted user retention by 10% and query satisfaction by 8%.

AI assistantArtificial IntelligenceIntent Routing
0 likes · 4 min read
How Xiaomi’s XiaoAI Harnesses Large Models for Intent Routing and Response Generation
Ubiquitous Tech
Ubiquitous Tech
Oct 1, 2025 · Artificial Intelligence

Designing Context for AI Code Review (Part 18)

This article explains how to construct and manage various context data—such as historical review feedback, code diffs, file types, developer experience, commit messages, business scenarios, framework knowledge, and Git logs—to improve the quality of AI‑driven code reviews, and provides a concrete TypeScript implementation with modular context providers, prompt engineering, and integration with GitLab and OpenAI APIs.

AI Code ReviewGitLabPrompt Engineering
0 likes · 21 min read
Designing Context for AI Code Review (Part 18)
BirdNest Tech Talk
BirdNest Tech Talk
Sep 30, 2025 · Artificial Intelligence

LLM vs. ChatModel in LangChain: Choosing the Right Interface

This article explains LangChain's two core abstractions—LLM for simple text completion and ChatModel for multi‑turn conversational AI—detailing their input/output formats, practical code examples, and why ChatModel is generally preferred for modern dialogue applications.

AIChatModelLLM
0 likes · 6 min read
LLM vs. ChatModel in LangChain: Choosing the Right Interface
Architect
Architect
Sep 30, 2025 · Artificial Intelligence

Transform Your Coding Workflow: A Structured AI Collaboration Framework for Developers

Discover a four‑stage, structured AI‑coding workflow—Explore, Plan, Code, Commit—that turns developers from occasional users into architectural partners, boosting efficiency, reducing bugs, and enabling smarter decision‑making across tasks from quick scripts to complex system design.

AIProductivityPrompt Engineering
0 likes · 21 min read
Transform Your Coding Workflow: A Structured AI Collaboration Framework for Developers
Ubiquitous Tech
Ubiquitous Tech
Sep 30, 2025 · Artificial Intelligence

16 Practical Ways to Elevate AI Code Review Quality

The article tells of a developer whose code caused a CPU spike, shows how an AI code review tool caught an unnecessary database query, and then outlines sixteen practical ideas—including multi‑turn dialogue, diff analysis, domain fine‑tuning, CI/CD integration, template feedback, intent inference, automated test generation, security scanning, auto‑fix suggestions, performance analysis, readability scoring, and visual reporting—to improve AI‑assisted code review quality.

AI Code ReviewCI/CDPrompt Engineering
0 likes · 20 min read
16 Practical Ways to Elevate AI Code Review Quality
Software Engineering 3.0 Era
Software Engineering 3.0 Era
Sep 28, 2025 · Artificial Intelligence

Why Large Language Models Appear So Smart: The Science of Emergence

The article explains how massive language models achieve seemingly intelligent behavior through emergence at a critical scale, hierarchical planning, attention-driven global coherence, multimodal understanding, and progressive training techniques that turn simple token prediction into sophisticated reasoning and creativity.

Attention MechanismLarge Language ModelsMultimodal AI
0 likes · 15 min read
Why Large Language Models Appear So Smart: The Science of Emergence
Tencent Advertising Technology
Tencent Advertising Technology
Sep 27, 2025 · Artificial Intelligence

How AI‑Generated Test Cases Transformed Tencent Ads R&D Workflow

This article details how Tencent's advertising R&D team tackled lengthy, experience‑driven test case creation by deploying AIGC‑powered demand analysis, Prompt + RAG knowledge retrieval, and multi‑stage automated validation, ultimately boosting test case adoption from under 20% to nearly 60% while reducing manual effort and iteration time.

AI testingAIGCPrompt Engineering
0 likes · 14 min read
How AI‑Generated Test Cases Transformed Tencent Ads R&D Workflow
BirdNest Tech Talk
BirdNest Tech Talk
Sep 25, 2025 · Artificial Intelligence

Mastering LangChain: A Hands‑On Guide to Building LLM Applications

This repository offers a comprehensive, step‑by‑step LangChain tutorial series that walks developers through installation, the LangChain Expression Language, streaming, parallel execution, callbacks, serialization, model customization, prompt templates, memory, multimodal support, and advanced tools like LangGraph and LangSmith, enabling the creation of sophisticated AI applications.

AI developmentLLMLangChain
0 likes · 9 min read
Mastering LangChain: A Hands‑On Guide to Building LLM Applications
Alibaba Cloud Developer
Alibaba Cloud Developer
Sep 25, 2025 · Artificial Intelligence

Why AI Code Generation Fails and How Structured Docs Can Boost Adoption

The article analyzes the low adoption rate of AI‑generated code, identifies root causes such as information asymmetry, oversized tasks, missing feedback loops and unclear role boundaries, and proposes a systematic solution based on structured documentation, issue‑driven workflows, prompt engineering and incremental quality control to make AI coding reliable.

Prompt Engineeringdocumentationissue management
0 likes · 18 min read
Why AI Code Generation Fails and How Structured Docs Can Boost Adoption
Raymond Ops
Raymond Ops
Sep 21, 2025 · Artificial Intelligence

What is AIGC? A Complete Guide to AI-Generated Content and Its Real-World Uses

This article provides a comprehensive overview of Artificial Intelligence Generated Content (AIGC), explaining its definition, core technologies, relationship with large models, diverse application scenarios, industry impact, career implications, popular tools, prompt engineering, and practical step‑by‑step tutorials across text, image, voice, video, and coding domains.

AI Content GenerationAI toolsAIGC
0 likes · 43 min read
What is AIGC? A Complete Guide to AI-Generated Content and Its Real-World Uses
Wuming AI
Wuming AI
Sep 20, 2025 · Artificial Intelligence

How to Use Cherry Studio for Simultaneous Multi‑Model AI Calls

This guide shows how to install Cherry Studio, configure multiple AI model providers, and send a single prompt that triggers several models at once, with step‑by‑step screenshots, layout tips, and cost considerations for free and paid services.

AI toolsArtificial IntelligenceCherry Studio
0 likes · 5 min read
How to Use Cherry Studio for Simultaneous Multi‑Model AI Calls
JD Tech
JD Tech
Sep 18, 2025 · Artificial Intelligence

How I Turned a General LLM into a Precise E‑commerce Risk Detector

The article recounts how a risk‑control algorithm engineer progressively refined a generic large language model through four stages of prompt engineering—role‑playing, business knowledge injection, deeper analysis, and a double‑hypothesis decision framework—to transform it into a precise e‑commerce fraud detection expert.

AILLMMachine Learning
0 likes · 12 min read
How I Turned a General LLM into a Precise E‑commerce Risk Detector
Instant Consumer Technology Team
Instant Consumer Technology Team
Sep 17, 2025 · Artificial Intelligence

Uncovering the Secret System Prompts Behind ChatGPT, Claude, and Gemini

The article examines the open‑source "system_prompts_leaks" project, which collects leaked system prompts from major AI models and reveals recurring design patterns such as modular layering, strict boundary control, dynamic strategy adjustment, emotional persona injection, and multi‑layer safety mechanisms.

AI safetyPrompt Engineeringsecurity
0 likes · 7 min read
Uncovering the Secret System Prompts Behind ChatGPT, Claude, and Gemini
Wuming AI
Wuming AI
Sep 16, 2025 · Artificial Intelligence

How I Restored Faded Childhood Photos Using Nano Banana AI in Google AI Studio

After years of failed attempts with various image‑enhancement tools, I used the Nano Banana model in Google AI Studio, crafted a simple prompt, uploaded my damaged photos, and within minutes achieved surprisingly high‑quality restorations that revived old memories.

AI photo restorationGoogle AI StudioNano Banana
0 likes · 4 min read
How I Restored Faded Childhood Photos Using Nano Banana AI in Google AI Studio
Architects Research Society
Architects Research Society
Sep 12, 2025 · Artificial Intelligence

Master Generative AI: From Core Concepts to Advanced Techniques

This comprehensive guide walks you through generative AI fundamentals—including transformers, diffusion models, large language models, and multimodal systems—then explores practical API usage with OpenAI, Hugging Face, and Vertex AI, followed by model fine‑tuning, LoRA, knowledge injection, and advanced topics such as model distillation, prompt chaining, AutoML, tool integration, and retrieval‑augmented generation.

AutoMLPrompt Engineeringmodel fine‑tuning
0 likes · 3 min read
Master Generative AI: From Core Concepts to Advanced Techniques
Amazon Cloud Developers
Amazon Cloud Developers
Sep 11, 2025 · Artificial Intelligence

Achieving Consistent Characters and Cohesive Styles in AI Storyboards with Amazon Nova – Part 1

The article explains how to maintain character consistency and visual style across AI‑generated storyboard scenes by using structured prompt engineering, seed and cfgScale parameters, and a workflow that combines Amazon Nova Lite, Canvas, and Reel, while also showing concrete examples and limitations.

AI storyboardAmazon NovaPrompt Engineering
0 likes · 14 min read
Achieving Consistent Characters and Cohesive Styles in AI Storyboards with Amazon Nova – Part 1
Full-Stack Cultivation Path
Full-Stack Cultivation Path
Sep 10, 2025 · Frontend Development

Boost Development Efficiency with Vibe Coding: Practical Tips and Real‑World Examples

The article examines Vibe Coding—a high‑frequency AI‑driven coding workflow—detailing when it fits personal or enterprise projects, how to choose strong models, craft effective prompts, manage context, use Agent mode, enforce standards, and review AI‑generated code to turn potential technical debt into a productivity asset.

AI code generationNext.jsPrompt Engineering
0 likes · 12 min read
Boost Development Efficiency with Vibe Coding: Practical Tips and Real‑World Examples
Wuming AI
Wuming AI
Sep 10, 2025 · Industry Insights

Will Half of Developers Be Forced to Switch to AI Roles in the Next 5 Years?

The article analyzes how massive AI investment and government policy are reshaping China’s tech hiring landscape, highlighting that over 60% of Alibaba’s 2026 recruitment targets AI roles, detailing the skills employers now demand, and warning that half of today’s developers may need to transition to AI within the next few years.

AIPrompt Engineeringcareer transition
0 likes · 8 min read
Will Half of Developers Be Forced to Switch to AI Roles in the Next 5 Years?
Architect
Architect
Sep 9, 2025 · Artificial Intelligence

Why Do Language Models Hallucinate? Insights from OpenAI’s New Study

This article explains why large language models often produce confident but incorrect answers, detailing statistical inevitability, data scarcity, and model capacity limits, and proposes concrete solutions such as confidence thresholds and allowing abstention to reduce hallucinations.

AI safetyEvaluationPrompt Engineering
0 likes · 8 min read
Why Do Language Models Hallucinate? Insights from OpenAI’s New Study
Architect's Journey
Architect's Journey
Sep 9, 2025 · Artificial Intelligence

Build an AI Agent Mini‑Game in 30 Minutes

This step‑by‑step tutorial shows how to create a simple AI‑driven mini‑game on the Coze platform in half an hour, covering account setup, agent creation, prompt design, debugging, publishing, advanced prompt techniques, and common pitfalls.

AI AgentAI developmentCoze
0 likes · 11 min read
Build an AI Agent Mini‑Game in 30 Minutes
Zhuanzhuan Tech
Zhuanzhuan Tech
Sep 8, 2025 · Artificial Intelligence

Mastering Cursor AI: Prompt Engineering and Rule Management for Efficient Coding

This guide explains how to communicate effectively with the Cursor AI coding assistant by crafting high‑quality prompts, using context cues, managing multi‑turn dialogues, and configuring persistent rules, offering practical principles, examples, and actionable recommendations to boost development productivity.

AIPrompt Engineeringcursor
0 likes · 15 min read
Mastering Cursor AI: Prompt Engineering and Rule Management for Efficient Coding
JD Tech Talk
JD Tech Talk
Sep 8, 2025 · Artificial Intelligence

How I Turned a Generic LLM into a Precise E‑Commerce Risk Detector

The article recounts how a risk‑control algorithm engineer progressively refined a generic large language model through four stages of prompt engineering—defining roles, dimensions, structured I/O, business rules, behavior fingerprints, and a dual‑hypothesis decision framework—to transform it into a precise e‑commerce fraud detection expert.

AILLMPrompt Engineering
0 likes · 10 min read
How I Turned a Generic LLM into a Precise E‑Commerce Risk Detector
Architecture Breakthrough
Architecture Breakthrough
Sep 7, 2025 · Industry Insights

Why Arrogance Blocks You From Riding the AI Wave—and How to Overcome It

The article argues that arrogance, not lack of knowledge, hinders individuals from seizing AI opportunities, outlines four psychological barriers—unseen, undervalued, incomprehensible, and too late—and provides practical steps such as prompt engineering, RAG, fine‑tuning, and AI agents to actively engage with the AI wave.

AIPrompt EngineeringRAG
0 likes · 11 min read
Why Arrogance Blocks You From Riding the AI Wave—and How to Overcome It
DaTaobao Tech
DaTaobao Tech
Sep 3, 2025 · Artificial Intelligence

Why a Simple Workflow Beats Complex Agents in AI‑Powered Insurance Audits

A retrospective of an AI‑based insurance claim audit project shows that a well‑designed workflow, precise prompt engineering, and rule‑based pre‑filtering can achieve stable, high‑accuracy results, while overly complex agent architectures often become fragile patchwork solutions.

AI auditPrompt EngineeringWorkflow Design
0 likes · 24 min read
Why a Simple Workflow Beats Complex Agents in AI‑Powered Insurance Audits
Cognitive Technology Team
Cognitive Technology Team
Sep 3, 2025 · Artificial Intelligence

How to Build AI Agents that Auto‑Generate Helm Charts: Strategies, Pitfalls, and Best Practices

This article chronicles the author's hands‑on journey of designing AI agents to automatically generate Helm charts for open‑source applications, exploring agent role definition, behavior paradigms like ReAct and plan‑and‑execute, prompt engineering challenges, structured workflows, multi‑agent collaboration, and practical lessons for reliable, production‑grade automation.

AI AgentsHelm chart automationKubernetes
0 likes · 29 min read
How to Build AI Agents that Auto‑Generate Helm Charts: Strategies, Pitfalls, and Best Practices
Open Source Tech Hub
Open Source Tech Hub
Sep 1, 2025 · Artificial Intelligence

Master Claude Code: 33 Essential Tips and Commands for AI‑Powered Development

Learn how to harness Claude Code’s full potential with 33 practical techniques—from keyboard shortcuts and IDE integration to custom slash commands, cost tracking, multimodal image handling, and essential MCP extensions—providing a step‑by‑step guide that boosts productivity for AI‑assisted coding.

AI coding assistantClaude CodeIDE integration
0 likes · 9 min read
Master Claude Code: 33 Essential Tips and Commands for AI‑Powered Development
ShiZhen AI
ShiZhen AI
Sep 1, 2025 · Artificial Intelligence

Nano Banana: A Next‑Gen AI Image Creation and Editing Guide

Nano Banana, Google’s internal code name for Gemini 2.5 Flash Image, reshapes AI image creation with ten‑fold speed gains over Photoshop, consistent multi‑step editing, dialogue‑driven image manipulation, style‑transfer capabilities, and a community‑validated reputation earned through blind tests on LMArena, while also exposing typical generative‑AI limits such as text rendering glitches and occasional anatomical errors.

AI image generationGemini 2.5 Flash ImageLMArena
0 likes · 20 min read
Nano Banana: A Next‑Gen AI Image Creation and Editing Guide
Data Party THU
Data Party THU
Sep 1, 2025 · Artificial Intelligence

Why Intermediate Tokens Make LLMs Reason Better: Insights from Denny Zhou

The article analyzes Denny Zhou's Stanford CS25 lecture on large language model reasoning, explaining how intermediate token generation, chain‑of‑thought prompting, self‑consistency, reinforcement‑learning fine‑tuning, and answer aggregation together unlock powerful reasoning capabilities beyond traditional greedy decoding.

AI researchChain-of-ThoughtLLM
0 likes · 17 min read
Why Intermediate Tokens Make LLMs Reason Better: Insights from Denny Zhou
DaTaobao Tech
DaTaobao Tech
Sep 1, 2025 · Artificial Intelligence

Boost Business Automation with AI Agents and MCP: Real-World Insights

This article explores how integrating AI agents with the Model Context Protocol (MCP) and tools like Playwright can automate reporting and batch task creation, detailing practical implementations, challenges, performance comparisons with traditional solutions, and best practices for combining AI and engineering to achieve efficient, reliable business workflows.

AI AgentMCPPrompt Engineering
0 likes · 19 min read
Boost Business Automation with AI Agents and MCP: Real-World Insights
Smart Sea Tide
Smart Sea Tide
Sep 1, 2025 · Artificial Intelligence

All-in-One AI Agent Development, Optimization, and Management with Coze Loop & Studio

This article introduces Byte's open‑source Coze Loop and Coze Studio platforms, detailing their Apache‑2.0‑licensed architectures, full lifecycle management for AI agents, core features such as prompt engineering, evaluation, observation, and a low‑code visual development environment built with Golang, React, and TypeScript.

AI AgentCoze LoopCoze Studio
0 likes · 6 min read
All-in-One AI Agent Development, Optimization, and Management with Coze Loop & Studio
DataFunSummit
DataFunSummit
Aug 30, 2025 · Artificial Intelligence

How Tencent’s DEA‑SQL Revolutionizes Text‑to‑SQL for Intelligent BI

This article systematically presents Tencent PGC's Text‑to‑SQL research, detailing the DEA‑SQL framework, its agent‑based architecture, extensive experiments on benchmark datasets, and real‑world deployment in the OlaChat intelligent BI product, highlighting performance gains and practical capabilities.

DEA-SQLPrompt EngineeringText-to-SQL
0 likes · 20 min read
How Tencent’s DEA‑SQL Revolutionizes Text‑to‑SQL for Intelligent BI
JD Retail Technology
JD Retail Technology
Aug 29, 2025 · Artificial Intelligence

Turning a General LLM into an E‑commerce Risk‑Detection Expert: A Step‑by‑Step Prompt Engineering Guide

The article recounts how a risk‑control algorithm engineer transformed a generic large language model into a specialized e‑commerce fraud detector by iteratively designing prompts, injecting business rules, structuring I/O, and introducing a dual‑hypothesis decision framework to achieve accurate, automated risk analysis.

Artificial IntelligenceLLMMachine Learning
0 likes · 11 min read
Turning a General LLM into an E‑commerce Risk‑Detection Expert: A Step‑by‑Step Prompt Engineering Guide
Alibaba Cloud Developer
Alibaba Cloud Developer
Aug 28, 2025 · Artificial Intelligence

How AI Agents and MCP Revolutionize Smart Reporting and Batch Task Automation

This article explores the practical integration of AI agents with Model Context Protocol (MCP) to build a smart reporting assistant and automate batch task creation, detailing the technical workflow, tool‑calling capabilities, implementation steps, challenges faced, and the benefits of combining agents with traditional engineering systems.

AI AgentMCPPrompt Engineering
0 likes · 18 min read
How AI Agents and MCP Revolutionize Smart Reporting and Batch Task Automation
ShiZhen AI
ShiZhen AI
Aug 27, 2025 · Artificial Intelligence

How to Craft Text Prompts for Stunning Images with Google Gemini

This guide explains how to write precise text prompts for Google Gemini’s image‑generation model, covering six essential prompt elements, feature overviews, and concrete examples that demonstrate character consistency, targeted edits, creative composition, style transfer, and logical reasoning, while also noting current limitations.

AI image generationGoogle GeminiPrompt Engineering
0 likes · 10 min read
How to Craft Text Prompts for Stunning Images with Google Gemini
Data Thinking Notes
Data Thinking Notes
Aug 26, 2025 · Artificial Intelligence

From Prompt to Context: How AI Agents Evolve into Proactive Intelligence

This article explores the rapid growth of large language models and explains how AI agents transform passive, single‑turn responses into proactive, continuous intelligence by leveraging a core “Prompt→Context→Action” loop, detailing their architecture, key components, challenges, and future directions.

AI AgentLLM ArchitecturePrompt Engineering
0 likes · 20 min read
From Prompt to Context: How AI Agents Evolve into Proactive Intelligence
Tech Freedom Circle
Tech Freedom Circle
Aug 26, 2025 · Artificial Intelligence

How to Optimize RAG for Alibaba Interviews? 7 Golden Rules Explained

This article provides a step‑by‑step technical guide to optimizing Retrieval‑Augmented Generation (RAG) for interview scenarios, covering query rewriting, HyDE, fallback strategies, routing and prompt routing, multi‑representation indexing, hybrid retrieval, re‑ranking, self‑RAG, generation control, performance benchmarking, and a practical checklist with concrete code examples and metrics.

AI InterviewHybrid RetrievalLangChain
0 likes · 30 min read
How to Optimize RAG for Alibaba Interviews? 7 Golden Rules Explained
Wuming AI
Wuming AI
Aug 26, 2025 · Artificial Intelligence

A Layered Overview of Agentic AI: From LLM Foundations to Multi‑Agent Systems

This article presents a hierarchical breakdown of Agentic AI, detailing the foundational large language models, the capabilities of AI agents, the coordination mechanisms of multi‑agent systems, and the supporting infrastructure needed for reliability, scalability, and security.

AI AgentsLLMObservability
0 likes · 5 min read
A Layered Overview of Agentic AI: From LLM Foundations to Multi‑Agent Systems
Ops Development & AI Practice
Ops Development & AI Practice
Aug 25, 2025 · Artificial Intelligence

Beyond Prompt Engineering: Mastering Context Engineering for Powerful AI Agents

Prompt engineering focuses on crafting single-shot inputs for LLMs, while context engineering builds a dynamic, information-rich environment that supplies history, tools, and external knowledge, enabling agents to act reliably over time; this article compares the two, outlines their differences, and shows how they complement each other.

Artificial IntelligenceContext EngineeringPrompt Engineering
0 likes · 9 min read
Beyond Prompt Engineering: Mastering Context Engineering for Powerful AI Agents
Data Party THU
Data Party THU
Aug 24, 2025 · Artificial Intelligence

How to Build a Multi‑Agent AI Research Assistant with LangGraph

This article demonstrates how to construct a multi‑agent AI research assistant using the LangGraph framework, detailing the system’s shared state design, individual agent implementations for research, fact‑checking, and report generation, workflow orchestration, advanced patterns like dynamic routing and parallel execution, and performance considerations.

AI research assistantLangGraphPrompt Engineering
0 likes · 14 min read
How to Build a Multi‑Agent AI Research Assistant with LangGraph
DataFunSummit
DataFunSummit
Aug 23, 2025 · Artificial Intelligence

Mastering Role‑Playing AI Agents: Challenges, Techniques, and Future Directions

This article surveys the latest research on role‑playing AI agents, covering their definition, core components, application scenarios, three main challenges—role fidelity, long‑term memory, and evaluation—and presents four technical approaches for each challenge along with future research directions and references.

AI AgentsEvaluationLarge Language Models
0 likes · 22 min read
Mastering Role‑Playing AI Agents: Challenges, Techniques, and Future Directions
21CTO
21CTO
Aug 21, 2025 · Artificial Intelligence

Why Most AI Agent Projects Fail and How to Benchmark Their Capabilities

The article analyzes why AI agent initiatives often flop compared to traditional software, explains the fundamental differences in development approaches, and introduces a three‑step Agent Capability Benchmark Testing framework with concrete evaluation criteria and a practical weekly‑report agent example.

AI AgentsLLMPrompt Engineering
0 likes · 12 min read
Why Most AI Agent Projects Fail and How to Benchmark Their Capabilities
Volcano Engine Developer Services
Volcano Engine Developer Services
Aug 21, 2025 · Artificial Intelligence

Why Prompt Engineering Isn’t Enough: The Rise of Context Engineering and RAG

Since last year, the debate over “Prompt Engineering” has split between practitioners who favor “Context Engineering” for building scalable agent systems and scholars who treat Prompt Engineering as a broad umbrella term, highlighting the need to dynamically construct and manage context for reliable, extensible AI applications.

AI AgentsLLMPrompt Engineering
0 likes · 33 min read
Why Prompt Engineering Isn’t Enough: The Rise of Context Engineering and RAG
Alibaba Cloud Developer
Alibaba Cloud Developer
Aug 21, 2025 · Artificial Intelligence

Why Your AI Defect Deduplication Returns Mixed Data and How to Fix It

This article details the challenges of building an AI‑powered defect deduplication system using Retrieval‑Augmented Generation, explains why LLMs produce composite (spliced) results, diagnoses the root cause as information loss in the RAG pipeline, and presents a step‑by‑step solution that restores atomicity of records for reliable duplicate detection.

AI debuggingLLMPrompt Engineering
0 likes · 14 min read
Why Your AI Defect Deduplication Returns Mixed Data and How to Fix It
AndroidPub
AndroidPub
Aug 19, 2025 · Artificial Intelligence

Demystifying AI Jargon: From Prompts to Agents, Tools, and MCP Protocol

This article breaks down the confusing AI buzzwords—user prompts, system prompts, agents, tool registration, function calling, and the MCP protocol—explaining how they work together to enable AI assistants that can perform real tasks beyond simple chat.

AI AgentsAI promptsFunction Calling
0 likes · 8 min read
Demystifying AI Jargon: From Prompts to Agents, Tools, and MCP Protocol
Alibaba Cloud Developer
Alibaba Cloud Developer
Aug 18, 2025 · Artificial Intelligence

Mastering Claude Prompt Engineering: 9 Proven Strategies to Boost LLM Performance

This guide systematically breaks down Anthropic's official prompt‑engineering recommendations—clear instructions, multishot examples, chain‑of‑thought prompting, XML structuring, response pre‑filling, prompt chaining, long‑context handling, extended thinking, and practical code snippets—showing how to unlock Claude's full potential across complex tasks.

AIChain-of-ThoughtClaude
0 likes · 15 min read
Mastering Claude Prompt Engineering: 9 Proven Strategies to Boost LLM Performance
Data Thinking Notes
Data Thinking Notes
Aug 17, 2025 · Artificial Intelligence

Unlocking AI Agents: From Basics to Real-World Development

This article provides a comprehensive overview of AI Agents, covering their fundamental concepts, core features, technical evolution, work cycle, architectural modules, key technologies such as prompt engineering and RAG, practical development steps, a data‑analysis agent case study, and typical industry applications.

AI AgentArtificial IntelligencePrompt Engineering
0 likes · 13 min read
Unlocking AI Agents: From Basics to Real-World Development
Qborfy AI
Qborfy AI
Aug 16, 2025 · Artificial Intelligence

Mastering LLM Tokens: How They Work, Cost, and Choose the Right Model

This article explains what tokens are in large language models, how they are counted and priced, compares tokenization methods across major models, and provides practical guidelines and code examples for optimizing token usage and selecting the appropriate model for different scenarios.

AILLMModel Selection
0 likes · 8 min read
Mastering LLM Tokens: How They Work, Cost, and Choose the Right Model
Ops Development & AI Practice
Ops Development & AI Practice
Aug 15, 2025 · Artificial Intelligence

How Google’s Imagen 4 Redefines AI Image Generation: Breakthroughs & Prompt Tips

Google’s Imagen 4 family—Ultra, Standard, and Fast—introduces unprecedented realism, reliable text rendering, multilingual prompts, and higher instruction fidelity, while the article explains each model’s trade‑offs and offers concrete prompt‑engineering techniques to help creators harness this next‑generation AI image generator.

AIArtificial IntelligenceGoogle
0 likes · 8 min read
How Google’s Imagen 4 Redefines AI Image Generation: Breakthroughs & Prompt Tips
Tencent Technical Engineering
Tencent Technical Engineering
Aug 14, 2025 · Artificial Intelligence

Why Do Large Language Models Hallucinate? Causes, Risks, and Multi‑Dimensional Solutions

This article systematically examines the root causes of hallucinations in large language models, evaluates their pros and cons, and presents a comprehensive set of optimization techniques—including prompt engineering, RAG, sampling tweaks, supervised fine‑tuning, LoRA, RLHF, chain‑of‑thought reasoning, and agent/workflow designs—to build more reliable and trustworthy AI applications.

AILLMLoRA
0 likes · 29 min read
Why Do Large Language Models Hallucinate? Causes, Risks, and Multi‑Dimensional Solutions
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Aug 8, 2025 · Artificial Intelligence

What Von Neumann’s Brain Theory Reveals About Prompt Engineering for LLMs

The article explores how Von Neumann’s insights on the brain‑computer analogy illuminate modern large‑language‑model prompt engineering, comparing logical reasoning chains, memory mechanisms, and DSL‑driven computation to improve accuracy, reduce hallucinations, and balance reasoning depth with precise calculation.

DSLLarge Language ModelsPrompt Engineering
0 likes · 14 min read
What Von Neumann’s Brain Theory Reveals About Prompt Engineering for LLMs
Volcano Engine Developer Services
Volcano Engine Developer Services
Aug 8, 2025 · Artificial Intelligence

Master PromptPilot: Step‑by‑Step Guide to Build, Optimize, and Debug AI Prompts

This comprehensive tutorial walks you through the entire PromptPilot workflow—from initial setup and prompt generation to iterative optimization, visual debugging, batch testing, and intelligent refinement—showcasing how to create high‑quality, production‑ready prompts for AI agents and applications.

AI toolsMultimodal AIPrompt Engineering
0 likes · 10 min read
Master PromptPilot: Step‑by‑Step Guide to Build, Optimize, and Debug AI Prompts
Tencent Cloud Developer
Tencent Cloud Developer
Aug 8, 2025 · Artificial Intelligence

Mastering AI Agents: A Practical Guide to Building Effective Workflows and Tools

This comprehensive guide explains when to use AI agents, presents core design patterns such as prompt chains, routing, parallelization, orchestrator‑worker and eval‑optimize loops, and offers concrete implementation advice and tool‑prompt engineering techniques for building reliable, high‑quality agent systems.

LLMPrompt EngineeringWorkflow Design
0 likes · 24 min read
Mastering AI Agents: A Practical Guide to Building Effective Workflows and Tools
Alibaba Cloud Developer
Alibaba Cloud Developer
Aug 5, 2025 · Artificial Intelligence

Mastering Intent Detection & Slot Filling: Proven Strategies and Code Samples

This article shares reusable AI development techniques for intent detection and slot filling, comparing four solution tiers—from simple prompt engineering to advanced RAG‑enhanced architectures—complete with practical code snippets, performance trade‑offs, and guidance on selecting the optimal approach for reliable conversational agents.

Intent DetectionNLUPrompt Engineering
0 likes · 27 min read
Mastering Intent Detection & Slot Filling: Proven Strategies and Code Samples
Wuming AI
Wuming AI
Aug 4, 2025 · Artificial Intelligence

Why OpenAI’s Study Mode Prompt Is a Masterclass in Prompt Engineering

OpenAI’s new Study Mode prompt exemplifies advanced prompt engineering by combining structured, defensive design, cognitive‑load theory, Vygotsky’s zone of proximal development, and Socratic interaction patterns, offering a step‑by‑step framework that transforms user tutoring into a disciplined, multi‑layered conversational system.

AI interactionCognitive LoadPrompt Engineering
0 likes · 15 min read
Why OpenAI’s Study Mode Prompt Is a Masterclass in Prompt Engineering
Hailey Says
Hailey Says
Aug 3, 2025 · Artificial Intelligence

The 5W1H of Context Engineering: A Method for Agentic AI

This article defines Context Engineering (CE), contrasts it with traditional Prompt Engineering, explains its components and benefits for Agentic AI, outlines practical steps and best‑practice techniques—including KV‑cache design, masking, file‑system context, and attention manipulation—while also discussing evaluation challenges and future outlook.

Context EngineeringKV cacheLLM
0 likes · 18 min read
The 5W1H of Context Engineering: A Method for Agentic AI
Ubiquitous Tech
Ubiquitous Tech
Aug 2, 2025 · Artificial Intelligence

Exploring JoyAgent‑JDGenie: Core Workflow and Prompt Engineering (Part 2)

This article walks through the JoyAgent‑JDGenie open‑source AI agent framework, detailing its multi‑agent architecture, backend and frontend components, deployment steps, configuration files, and the comprehensive prompt templates that drive planning, execution, and ReAct‑style reasoning.

AI AgentsJoyAgent-JDGenieMCP integration
0 likes · 27 min read
Exploring JoyAgent‑JDGenie: Core Workflow and Prompt Engineering (Part 2)