#DevOps and machine learning
141 related articles
Deep Dives·3 min
Deep Dive into How Claude Code Works: A New Programming Paradigm Driven by the Agent Loop
Deep dive into how Claude Code works, including the Agentic Loop, automatic context compaction, tool calling, and permission modes that power autonomous AI programming.
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Tutorials·4 min
Four Core Rules Anthropic Engineers Use to Prompt Claude Code
Anthropic engineers share how to properly use Claude Code at AI Code Summit: build composable Skills systems instead of one-off prompts. Master four core rules for skills that get smarter over time.
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Tutorials·3 min
In-Depth Review of a 628-Episode Python Full-Stack Tutorial: Can a Free Course Launch Your Career?
In-depth review of a 628-episode free Python full-stack tutorial on Bilibili, analyzing its strengths, limitations, and providing learning strategy advice for Python beginners.
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Tutorials·3 min
In-Depth Review of a 628-Episode Python Full-Stack Tutorial: Can a Free Course Launch Your Career?
In-depth review of a 628-episode free Python full-stack tutorial on Bilibili, analyzing its strengths, limitations, and providing learning strategy advice for Python beginners.
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Deep Dives
The Complete Guide to OpenTelemetry: T…
·4 min
The Complete Guide to OpenTelemetry: The Three Pillars of Observability & DevOps in Practice
Deep dive into OpenTelemetry's core architecture, the three pillars of observability (logs, metrics, traces), with a real-world food delivery app crash debugging case showing how distributed tracing locates microservice bottlenecks and how AI is revolutionizing DevOps monitoring.
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Expert Opinions·3 min
The Hotter AI Gets, the More We Need Tech-Savvy People: Embrace the Tool, Don't Fear the Replacement
Jensen Huang advises everyone to embrace AI rather than fear it. As AI advances, demand for tech talent grows. Those who get displaced are people who refuse to use new tools. Learn strategies for thriving in the AI era.
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Tutorials·4 min
Deep Dive into Claude Code's Agent Architecture: From Principles to Minimal Implementation
Deep analysis of Claude Code's four core agent modules: Agent Loop, Tool System, Skills, and Memory, with a TypeScript minimal implementation guide for frontend engineers transitioning to AI development.
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Tutorials·3 min
Deep Dive into a 198-Hour Python Zero-to-Hero Course: Is This Learning Path Worth Following?
In-depth analysis of a 198-hour Python+AI beginner course: breaking down its structure, learning path, and projects with honest pros, cons, and study tips.
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Product Reviews·3 min
Ruflo: A Multi-Agent Orchestration Solution That Turns Claude Code into a 100-Person AI Team
Ruflo is an open-source multi-agent orchestration platform that upgrades single-threaded Claude Code into a distributed AI dev team with 100+ specialized Agents and a SANA self-learning engine.
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Industry Insights·3 min
AI Is Getting More Expensive: The Industry Truth Behind Rising Prices for Premium Models
From $1.3M monthly token bills to rising premium AI model prices, AI isn't becoming accessible. A deep dive into the industry's two price lists, centralization trends, and what it means for everyone.
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Product Reviews·2 min
Warp Terminal Deep Dive: A Smart Command-Line Tool with Built-in AI Agent
Deep dive into Warp intelligent terminal, a high-performance CLI tool built with Rust. Explore Agent Mode for natural language commands, smart debugging, Warp Drive team collaboration, and how it differs from Cursor and other AI coding tools.
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Product Reviews·3 min
Claude 4.5 vs Gemini 3 Pro: A Comprehensive Coding Showdown
In-depth comparison of Claude 4.5 vs Gemini 3 Pro across five benchmarks including ARC-AGI-V2, SWE-Bench, and Terminal Bench 2.0, revealing their real coding and reasoning strengths.
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Product Reviews·2 min
OpenClaw Hands-On Review: An AI Agent That Controls Your Computer — A New Benchmark for Office Automation
In-depth review of OpenClaw AI Agent: it takes over your keyboard and mouse to operate your computer directly. Covers environment setup, data scraping, file management, security, and cross-platform support.
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Tutorials·2 min
Python for Absolute Beginners: A Complete Guide to Language Features and Applications
A beginner's guide to Python covering its core features—readability, simplicity, and extensibility—plus key applications in AI, web development, data analysis, and web scraping, with version selection advice.
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Tutorials·1 min
MLflow Hands-On Tutorial: A Full-Stack MLOps Guide for GenAI Tracing + Classic ML Tuning
Learn MLflow's core features for GenAI and classic ML: auto tracing, model evaluation, Prompt versioning, hyperparameter tuning, and model deployment in just a few lines of code.
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Tech Frontiers·2 min
2024 Go Developer Survey Now Open: How to Participate and How Past Surveys Have Shaped Go's Evolution
The Go team launches a new developer community survey to collect usage feedback and improvement suggestions. Learn about the survey's purpose, how to participate, and how past surveys drove features like generics and Go Modules.
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Tutorials·3 min
Full-Stack Development for Beginners in the AI Era: Don't Write Code — Learn to Manage It
AI coding tools make code generation easy, but a huge gap remains between code and product. This article breaks down frontend, backend, and DevOps stacks, exploring how beginners can manage code with AI.
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Expert Opinions·2 min
A Critical Look at AI Coding: Copilot Is Not a Developer's Replacement
An in-depth look at how to properly use AI coding tools like GitHub Copilot, exploring hybrid development, prompt evolution, and the risk of eroding developer learning abilities.
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Tutorials·3 min
What Are Python Literals? A Detailed Guide to int, float, and str Data Types
Learn Python literals and the three core data types: int, float, and str. Includes type() function examples, common pitfalls like confusing "123" with 123, and a beginner learning roadmap.
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Deep Dives·3 min
AI Model Deployment Pipeline Friction: How TensorRT Systematically Eliminates Inference Optimization Bottlenecks
Deep dive into pipeline friction in AI model deployment from training to production, covering TensorRT automated optimization, ONNX export, and Triton Inference Server best practices.
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