LLM
# Context Engineering *Part of the “Machine Learning for Engineers” series*  **Previous recap:** *Vector Distance Metrics* --- ## Introduction: From Chatbot to Decision Engine Large Language Models (LLMs) have shifted from being **casual chatbots** to **core decision-making components** in complex
AI agents
# Building Better Agents: Lessons from Yunxiaoer Aivis ## Introduction This year, our team has invested heavily in **Yunxiaoer Aivis** — a digital employee in the Alibaba Cloud services domain. It represents our evolution from traditional intelligent customer service assistance to a new **end-to-end Multi-Agent** capability. 
context engineering
# 2025-10-24 · Zhejiang   --- ## Introduction With the rapid growth of AI Agents, a new term — **Context Engineering** — has emerged. Many are asking: - How does it differ
AI coding
Alibaba Qoder — Architecture Philosophy, Technical Trade-offs, and Positioning / Pricing Overview AI programming tools are undergoing explosive growth. Overseas solutions like Claude Code and Cursor have gained momentum through architectural and interaction innovations, while platforms such as Cline, Replit, and AmpCode push forward new experimentation. Domestic vendors are entering this competitive
ACE framework
Agentic Context Engineering (ACE): A New Path for Self-Improving LLMs Researchers from Stanford University, SambaNova Systems, and UC Berkeley have introduced Agentic Context Engineering (ACE) — a novel framework designed to enhance Large Language Models (LLMs) using evolving, structured context instead of traditional weight retraining. The goal is simple yet powerful:
AI agents
AI Agents and the Art of Context Engineering Source of Inspiration: Lance (LangChain) & Pete (Manus) Original Video: Watch on YouTube --- We are entering a new era where AI Agents can autonomously execute long, complex tasks. Yet an unexpected paradox arises: > The more we rely on them, the
AI agents
Datawhale Insights: Why 95% of AI Agents Fail in Production At a recent Silicon Valley industry event, Oana Olteanu—a renowned venture capitalist—joined engineers and ML leads from Uber, WisdomAI, EvenUp, and Datastrato to discuss how AI Agents can succeed in production environments. Key statistic: 95% of AI Agents
AI research
Farewell to Traditional Fine-Tuning: Introducing ACE A groundbreaking study from Stanford University, SambaNova Systems, and the University of California, Berkeley has demonstrated a transformative approach to improving AI models — without adjusting a single weight. The method, called Agent Contextual Engineering (ACE), relies on context engineering rather than retraining. It autonomously