#distributed tracing
210 related articles
·6 min
Andrew Ng × Anthropic: A Hands-On Claude Code Tutorial and Core Methodology
Andrew Ng partners with Anthropic to launch a hands-on Claude Code course, revealing its simple architecture, local security edge, and core context methodology across three cases: RAG chatbot, Jupyter analysis, and Figma-to-frontend.
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·4 min
Complete Guide: Connecting Claude Code to DeepSeek — Local Setup + VS Code Integration
A step-by-step guide to installing Claude Code locally on Windows and swapping its underlying model for the DeepSeek API—enabling low-cost AI coding with no VPN required. Covers Node.js setup, Claude Code config, and getting a DeepSeek API Key.
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·6 min
Connecting SQL Projects to Azure DevOps Pipelines: A Hands-On Guide to Automated Builds and Secure Deployment
Learn how to connect SSMS SQL projects to an Azure DevOps CI/CD pipeline—covering YAML build config, SQL code quality analysis, managed identity authentication, and dynamic firewall rules for secure Azure SQL deployment.
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·7 min
1X Unveils NEO Robotic Hand: 25 DoF Tendon-Driven Design Ushers Dexterous Hands into the Mass-Production Era
1X unveils a new robotic hand for its NEO humanoid: 25 DoF, tendon-driven quasi-direct-drive architecture, full-joint force control, tactile skin, IP68 waterproofing, and compliant safety design, with capacity for 10,000 units a year.
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·7 min
Turning Any AI Agent into an Orchestration Hub: A Deep Dive into Multi-Agent Collaboration Architecture
An in-depth analysis of the "any Agent as an orchestrator" design philosophy, exploring the technical implementation of multi-Agent collaboration, context management, and workflow automation.
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·4 min
The Age of AI Agents: How Version Control Must Adapt to a Paradigm Shift
AI agents are breaking Git's core assumptions. Explore the three key challenges—concurrent conflicts, history readability, and code review—and where version control is headed next.
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·4 min
AI Agent Development Deep Dive: Opportunities, Real Entry Barriers, and Learning Paths
A deep dive into AI Agent development: real architecture, entry barriers, and learning paths. From ReAct to multi-agent systems and LangChain — cut through the hype.
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·5 min
Google Doubles Down on Virginia: The Energy and Employment Dynamics Behind Data Center Expansion
Google launches new community investment in Virginia focused on energy affordability and tech workforce. Analysis of how data center expansion reshapes local energy and employment dynamics.
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·5 min
Agentic MapReduce: The Key Architecture for AI Agents to Achieve Distributed Reasoning Across Entire Codebases
Cognition's Agentic MapReduce architecture combines classic distributed computing with autonomous agents to break LLM context window limits, enabling multi-Agent parallel reasoning across entire codebases.
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·5 min
5 Things You Must Do Before Deploying AI Agents to Production (With a Banking POC Case Study)
Over 60% of AI Agent projects die between demo and production. This article breaks down Databricks lead Sandy's five-pillar methodology and a bank POC case study to help you avoid the most common deployment pitfalls.
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·6 min
Databricks Agent Framework in Practice: A Guide to ChatAgent Wrapping and Production Deployment
A deep dive into Databricks Agent Framework (Mosaic AI): unify LangGraph/OpenAI agents via ChatAgent, log & evaluate with MLflow, version with Unity Catalog, and deploy Model Serving Endpoints for production AI agents.
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·7 min
The Five Pillars of Production-Grade AI Agents: A Battle-Tested Guide from Demo to Deployment
Databricks tech lead Sandy shares a five-pillar framework for production-grade AI Agents—evaluation, observability, data foundation, orchestration, and governance—with a £85K retail banking failure case to bridge the demo-to-production gap.
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·6 min
Deploying Enterprise AI Agents to Production: The Five Pillars from Demo to Launch
A Databricks expert breaks down the complete methodology for taking AI Agents from demo to production, covering the five pillars of evaluation, observability, data foundation, multi-Agent orchestration, and AI governance, with a real eight-week banking chatbot POC case.
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·4 min
Reinforcement Learning for AI Agents: A Deep Dive into RLHF and Agentic RL
A deep dive into RL for AI agents: from RLHF to Agentic RL, covering PPO vs. GRPO, sparse rewards, tool-calling optimization, and verifiable rewards.
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·6 min
Dify Local Deployment in Practice: A Complete Guide to Building an AI Application Platform with Docker
A complete guide to Dify local deployment: from Docker environment setup, source code pulling, and container startup to first access. Build a private AI app development platform across Linux, Windows, and Mac for fast enterprise AI deployment.
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·7 min
From Vibe Coding to Engineered AI Programming: A Practical Guide to Enterprise Development
AI coding tools are changing development, but Vibe Coding hides risks in code quality and maintenance. This article explores Engineered AI Programming, compares Codex and Claude Code, and reveals real enterprise development paths.
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·2 min
Microsoft Open-Sources Flint: A Deep Dive into the AI Agent Behavior Visualization Language
Microsoft open-sources Flint, a visualization language for AI agents that helps developers understand decision paths, multi-step reasoning, and collaboration flows to improve debugging and observability.
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·7 min
The Prompt is the Platform: How AI Agents Deeply Participate in System Design and Specification
Resonate's founder proposes "The Prompt is the Platform": as AI agents generate production-grade implementations from abstract specs, engineers' value shifts to specification. A deep dive into deterministic simulation and forbidden-fruit debugging.
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·7 min
The Agent Engineer Transition Roadmap: A Deep Dive into Three Core Skill Systems
Want to become an Agent engineer? This article systematically covers three core skill tracks—LLM fundamentals, LangChain architecture development, and enterprise deployment—to help you avoid detours.
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·7 min
Getting Started with Dify: A Complete Guide from Local Deployment to Building Enterprise-Grade AI Applications
A detailed guide to Dify, the open-source LLM app development platform, covering its core features and full local deployment via VMware + Ubuntu + aaPanel + Docker. Supports 100+ models like DeepSeek and ChatGPT to build enterprise AI apps fast.
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