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128 articles

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Nov 15, 2025 · Artificial Intelligence

AI Paper Weekly: Scale Pretraining, Game Agents, Attention, Context Engineering

This weekly roundup highlights five recent AI research papers—including CoCa’s contrastive captioning model, the Game‑TARS framework for scalable game agents, Kimi Linear’s efficient attention architecture, the Continuous Autoregressive Language Model (CALM), and a comprehensive survey of Context Engineering—summarizing their core contributions and providing direct links.

AIContext EngineeringLanguage Models

0 likes · 6 min read

AI Paper Weekly: Scale Pretraining, Game Agents, Attention, Context Engineering

AI Tech Publishing

Nov 13, 2025 · Artificial Intelligence

Claude’s Prompt Engineering Best Practices: A Step‑by‑Step Guide

This guide outlines Claude team’s best practices for prompt engineering, covering core techniques such as clear instructions, background context, specificity, examples, and advanced methods like pre‑filled responses, chain‑of‑thought, output formatting, and prompt chaining, with concrete examples and code snippets.

AI promptingClaudeContext Engineering

0 likes · 18 min read

Claude’s Prompt Engineering Best Practices: A Step‑by‑Step Guide

AI Product Manager Community

Nov 8, 2025 · Artificial Intelligence

Why Prompt Engineering Fails: Embracing Context Engineering for Smarter LLMs

The article explains that prompt engineering alone cannot guarantee reliable AI responses because models lack situational awareness, and introduces context engineering as a systematic approach that structures memory, manages context flow, and integrates RAG and evaluation to make large language models truly useful in real‑world applications.

AIContext EngineeringLLM

0 likes · 7 min read

Why Prompt Engineering Fails: Embracing Context Engineering for Smarter LLMs

Tech Minimalism

Nov 2, 2025 · Artificial Intelligence

Claude Code: How a Minimalist Design Turns an AI Tool into a True Programming Partner

Claude Code redefines AI programming assistants by abandoning complex multi‑agent architectures in favor of a single‑loop, single‑file design, leveraging Unix‑style simplicity, LLM‑based search, and sophisticated context engineering to act as a collaborative partner rather than a mere code‑completion tool.

AI programming assistantClaude CodeContext Engineering

0 likes · 12 min read

Claude Code: How a Minimalist Design Turns an AI Tool into a True Programming Partner

Alibaba Cloud Developer

Oct 31, 2025 · Artificial Intelligence

Why AI Agents Fail and 10 Proven Ways to Make Them Reliable

This article shares the practical lessons learned from building Alibaba Cloud’s digital employee "YunXiaoEr Aivis", explaining why large‑language‑model agents often miss expectations and presenting ten concrete strategies—ranging from clear prompt design to memory management—that dramatically improve multi‑agent reliability.

AI agentsAgent OptimizationContext Engineering

0 likes · 29 min read

Why AI Agents Fail and 10 Proven Ways to Make Them Reliable

AI Large Model Application Practice

Oct 27, 2025 · Artificial Intelligence

Why Context Engineering Is the Next Evolution Beyond Prompt Engineering

The article explains how traditional prompt engineering is giving way to Context Engineering and the Agentic Context Engineering (ACE) framework, which lets large language model agents continuously learn and improve through evolving, well‑structured context without fine‑tuning.

AI ArchitectureContext EngineeringLLM

0 likes · 12 min read

Why Context Engineering Is the Next Evolution Beyond Prompt Engineering

Alibaba Cloud Native

Oct 25, 2025 · Artificial Intelligence

How Agent Development Toolchains Evolved: From Basic Frameworks to Model‑Centric AI

This article traces the evolution of agent development toolchains across four stages—basic frameworks, collaboration tools, reinforcement‑learning‑driven context engineering, and model‑centric architectures—while highlighting how stable cloud‑native infrastructure components like gateways, runtimes, observability, and security keep AI applications reliable and scalable.

AIAgentContext Engineering

0 likes · 11 min read

How Agent Development Toolchains Evolved: From Basic Frameworks to Model‑Centric AI

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

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.

Context EngineeringLLM Agentsai-optimization

0 likes · 19 min read

Mastering Context Engineering: Boost LLM Agent Performance

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

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

HyperAI Super Neural

Sep 30, 2025 · Artificial Intelligence

OnePiece: Applying LLM‑Style Reasoning to Item‑ID Sequences for Generative Recommendation

The article presents the OnePiece framework, which injects LLM‑style context engineering and latent reasoning into item‑ID based search‑and‑recommendation models, details the design choices, training tricks, attention analysis, and reports online gains of around 1% GMV and ad revenue, offering a thorough technical dissection of generative recommendation in industrial settings.

Context EngineeringGenerative RecommendationLLM reasoning

0 likes · 31 min read

OnePiece: Applying LLM‑Style Reasoning to Item‑ID Sequences for Generative Recommendation

Tencent Cloud Developer

Sep 29, 2025 · Artificial Intelligence

Boost Your Development with AI Pair Programming: PDCA, Prompt & Context Engineering

This article explores how AI‑assisted pair programming can transform the entire software development lifecycle—from planning to production—by applying the PDCA cycle, prompt engineering, and context engineering, offering practical tips, real‑world scenarios, and future outlooks for developers.

AI pair programmingContext EngineeringPDCA

0 likes · 17 min read

Boost Your Development with AI Pair Programming: PDCA, Prompt & Context Engineering

Wuming AI

Sep 29, 2025 · Artificial Intelligence

How I Quickly Uncovered Cherry Studio’s New API Server Using AI

In this walkthrough I show how, within minutes, I used AI‑driven code search and simple curl commands to locate, enable, and test the newly added API server feature in the open‑source Cherry Studio project, illustrating the power of an AI‑first workflow.

AIAI-firstAPI Server

0 likes · 6 min read

How I Quickly Uncovered Cherry Studio’s New API Server Using AI

DataFunTalk

Sep 20, 2025 · Artificial Intelligence

Why Chroma’s Context Engineering Is Redefining AI Search Infrastructure

Jeff Huber, founder of Chroma, discusses the startup’s mission to turn AI demos into production‑grade applications, critiques the hype around RAG, emphasizes the importance of Context Engineering, and explains how Chroma’s open‑source vector database and cloud service aim to simplify AI search for developers.

AIChromaContext Engineering

0 likes · 32 min read

Why Chroma’s Context Engineering Is Redefining AI Search Infrastructure

AI Cyberspace

Sep 18, 2025 · Artificial Intelligence

LangChain vs LangGraph vs LangSmith: Which AI Framework Fits Your Needs?

This article compares LangChain, LangGraph, and LangSmith—three complementary frameworks for building LLM-powered applications—explaining their distinct architectures, use cases, and features, and also introduces related concepts such as RAG, MCP, A2A protocols, hierarchical memory systems, context engineering, and knowledge graphs to guide developers in selecting and integrating the appropriate tools.

AgentContext EngineeringLLM

0 likes · 21 min read

LangChain vs LangGraph vs LangSmith: Which AI Framework Fits Your Needs?

Fighter's World

Sep 12, 2025 · Artificial Intelligence

Why Are Production‑Grade AI Agents So Hard to Build?

The article analyses why production‑grade AI agents remain unreliable, pinpointing the scarcity of high‑quality task‑action data, the limits of static benchmarks, and the need for massive data‑generation engines, simulation sandboxes, sophisticated RL reward design, and efficient context engineering.

AI AgentContext EngineeringData Generation

0 likes · 21 min read

Why Are Production‑Grade AI Agents So Hard to Build?

Instant Consumer Technology Team

Sep 5, 2025 · Artificial Intelligence

Why Context Engineering Is the Next Frontier for Large Language Models

This article surveys over 1,400 papers to define context engineering as a systematic discipline that structures retrieval, memory, tools, and multi‑agent coordination for LLMs, highlighting the critical asymmetry between understanding long contexts and generating equally complex outputs.

Context EngineeringLLM evaluationLarge Language Models

0 likes · 8 min read

Why Context Engineering Is the Next Frontier for Large Language Models

Instant Consumer Technology Team

Sep 2, 2025 · Artificial Intelligence

Why RAG Is Dead: Jeff Huber’s 5 Retrieval Secrets and Context Engineering

Jeff Huber, founder of Chroma, argues that traditional RAG is obsolete, introduces context engineering as the new paradigm, and shares five practical retrieval strategies, a complete pipeline, and insights on handling context rot, memory, and generative benchmarking to build production‑grade AI applications.

AIContext EngineeringGenerative Benchmarking

0 likes · 11 min read

Why RAG Is Dead: Jeff Huber’s 5 Retrieval Secrets and Context Engineering

Volcano Engine Developer Services

Aug 26, 2025 · Artificial Intelligence

From Single LLM to Multi‑Agent: How Context Engineering Drives the Next AI Architecture

This article examines the evolution of LangChain's Open Deep Research project from a monolithic LLM pipeline to a multi‑agent system, highlighting the role of context engineering, architectural trade‑offs, practical code examples, and best‑practice guidelines for building scalable, token‑efficient AI solutions.

AI researchContext EngineeringLLM architecture

0 likes · 16 min read

From Single LLM to Multi‑Agent: How Context Engineering Drives the Next AI Architecture

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

Architecture and Beyond

Jul 27, 2025 · Artificial Intelligence

Why Context Engineering Is the Secret to Powerful AI Agents

This article explains how AI agents work through perception, planning, and action, describes the four supporting systems—memory, tools, safety, and evaluation—and shows how the evolution from prompt engineering to context engineering, with strategies like selective saving, retrieval, compression, and modularization, addresses the core challenges of managing large‑scale context for reliable, efficient agent performance.

AI agentsContext EngineeringLLM

0 likes · 17 min read

Why Context Engineering Is the Secret to Powerful AI Agents

Alibaba Cloud Developer

Jul 21, 2025 · Artificial Intelligence

Unlocking LLM Power: How Context Engineering Transforms AI Assistants

Context engineering, the emerging discipline of structuring and managing input information for large language models, goes beyond simple prompt design by addressing issues such as context poisoning, overload, and conflict, offering strategies like intelligent retrieval, isolation, pruning, and compression to build reliable, high‑performing AI agents.

AI productivityAgent DesignContext Engineering

0 likes · 19 min read

Unlocking LLM Power: How Context Engineering Transforms AI Assistants

DataFunTalk

Jul 19, 2025 · Artificial Intelligence

Mastering Context Engineering for AI Agents: KV-Cache, Tool Management, and Error Handling

Peak, co‑founder of Manus, shares practical lessons on building AI agents through context engineering, emphasizing KV‑cache optimization, stable prompt prefixes, controlled tool selection, file‑system memory, attention‑directed todo lists, and preserving error traces to improve robustness and scalability.

AI agentsContext EngineeringError Handling

0 likes · 14 min read

Mastering Context Engineering for AI Agents: KV-Cache, Tool Management, and Error Handling

Continuous Delivery 2.0

Jul 17, 2025 · Artificial Intelligence

Why AI Coding Tools May Slow You Down: Uncovering the Efficiency Illusion

This article examines why AI‑assisted coding tools often create an illusion of speed, revealing research that shows senior developers may spend up to 19% more time, and outlines three key insights: the efficiency illusion, the supremacy of context, and a roadmap for building a human‑AI quality flywheel.

AI programmingContext Engineeringefficiency illusion

0 likes · 11 min read

Why AI Coding Tools May Slow You Down: Uncovering the Efficiency Illusion

DataFunTalk

Jul 7, 2025 · Artificial Intelligence

Bacterial Programming Meets Context Engineering: Insights for AI Agents

Karpathy’s “bacterial programming” metaphor—favoring small, modular, self‑contained code—offers a blueprint for building robust AI agents, while the emerging discipline of context engineering expands on this by systematically assembling prompts, tools, memories, and retrieval mechanisms to supply large language models with precisely the right information.

AIBacterial ProgrammingContext Engineering

0 likes · 19 min read

Bacterial Programming Meets Context Engineering: Insights for AI Agents

Fighter's World

Jun 21, 2025 · Artificial Intelligence

Speculating Devin’s Context Engineering Architecture: How Long‑Horizon Agents Preserve Complete Context

The article analyzes why context engineering is crucial for multi‑agent AI systems, illustrates the fragility caused by fragmented context with a Flappy Bird analogy, and proposes three detailed speculative components—a compression‑to‑structure pipeline, a hybrid layered memory architecture, and a context‑aware coordination mechanism—culminating in a unified reference design for long‑horizon agents.

Agent CoordinationCompression PipelineContext Engineering

0 likes · 22 min read

Speculating Devin’s Context Engineering Architecture: How Long‑Horizon Agents Preserve Complete Context

phodal

Jun 2, 2023 · Artificial Intelligence

Mastering LLMs: A Programmer’s Guide to Prompt Engineering, Architecture, and Contextual AI

This comprehensive guide walks programmers through the fundamentals of large language model capabilities, prompt writing and management, new interaction and workflow designs, advanced scenario‑specific applications, and context engineering, offering practical strategies and architectural insights for AI‑native development.

AI ArchitectureContext EngineeringLLM

0 likes · 14 min read

Mastering LLMs: A Programmer’s Guide to Prompt Engineering, Architecture, and Contextual AI