#AI engineer
5438 related articles
·1 min
A Practical Guide to Vibe Coding: How AI Is Reshaping the Frontend Engineer's Skill Model
An in-depth look at the Vibe Coding paradigm: how AI tools shift engineers from 'writing code' to 'directing AI,' exploring frontend skill tiers, polarization trends, and building irreplaceable value.
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·3 min
Pinterest Medic: Engineering an AI Agent for Automated Spark Failure Diagnosis
How Pinterest engineers built Medic for Apache Spark — a multi-agent auto-diagnosis tool — covering the evolution from a single ReAct agent, observability, log denoising, and end-to-end testing.
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·6 min
AI Application Engineer Interview Guide: Core Topics in Model Quantization and Inference Deployment
A systematic review of must-know topics for AI Application Engineer interviews: PTQ/QAT quantization, operator fusion, inference pipelines, latency/throughput analysis, and edge deployment of detection/segmentation/BEV models.
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·6 min
AI Application Engineer Interview Guide: Core Topics on Model Quantization and Inference Deployment
A systematic guide to must-know AI application engineer interview topics: PTQ/QAT quantization, operator fusion, inference pipelines, latency/throughput analysis, and edge deployment of detection/segmentation/BEV models.
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·5 min
From Vibe Coding to AI Engineering: A Complete Guide to Enterprise-Grade Development
In the AI programming era, Vibe Coding alone can only build toys. This article deeply analyzes the complete engineering path from Vibe Coding to SDD spec-driven development, covering Claude Code and Codex tool selection, the SuperPower plugin, and domestic LLM comparisons.
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·3 min
Vibe Coding vs. AI Engineering: A Practical Guide to Enterprise-Level AI Programming
From Vibe Coding to AI Engineering, explore Claude Code vs Codex tool selection, real enterprise boundaries of AI programming, and how to build maintainable AI-assisted development workflows.
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·4 min
Beyond Vibe Coding: A Complete Guide to Enterprise-Grade AI Engineering
Hit the Vibe Coding ceiling? This guide covers the three-stage AI coding progression path, Claude Code vs. Codex, SuperPower SDD, and how to go from vibe coding to enterprise-grade AI engineering.
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·7 min
Context Engineering: A Systematic Approach to Stop AI Agents from 'Talking Nonsense'
Context engineering is the core methodology for building efficient AI Agents, covering query enhancement, RAG retrieval, prompt design, memory management, and tool invocation. Master Write, Select, Compress, and Isolate to solve LLM hallucination at its root.
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·3 min
AI-Assisted GeeTest Four-Image CAPTCHA Reverse Engineering: A Complete Efficiency Guide
A complete walkthrough of AI-assisted GeeTest four-image CAPTCHA reverse engineering: from capturing the w parameter to AI analyzing obfuscated code and generating runnable scripts in minutes.
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·7 min
The Complete Guide to LLM Application Engineer Interviews: Six High-Frequency Topics in the Agent Domain
A focused guide to the core interview topics for LLM application engineers, covering agent architecture, Multi-Agent, Langfuse evaluation & tracing, security, and RAG optimization.
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·2 min
Full-Stack Developer to AI Engineer: Which Certifications Actually Matter?
Full-stack developer transitioning to AI/ML? Compare Google, AWS, and Microsoft AI certifications, understand the two career paths, and learn what actually matters.
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·7 min
From Chat to Agent Platform: A Practical Guide to Engineering AI Applications
A deep dive into engineering AI applications: from a simple chat page to a multi-layer Agent platform, covering RAG knowledge bases, Workflow scheduling, multi-model management, and run tracing.
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·4 min
Vibe Coding vs. AI-Assisted Engineering: An In-Depth Look at Enterprise-Level Development
Can AI coding tools let non-developers replace programmers? This deep dive examines Vibe Coding's real limits, compares Claude Code vs. Codex, and reveals the methodology behind enterprise-grade AI-assisted software engineering.
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·2 min
IDA Pro + MCP in Action: AI-Assisted Reverse Engineering of a Music App's Signature Algorithm
A hands-on walkthrough of using IDA Pro with MCP for AI-assisted reverse engineering of a music app's Sign signature algorithm, covering traffic capture, endpoint analysis, and .so binary analysis.
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·3 min
AI Development for Java Engineers: A Complete Guide to LangChain4j Agents
Java developers can build AI apps too! Learn LangChain4j fundamentals including RAG, Agents, Function Calling, and hands-on projects — no Python required.
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·4 min
How Engineers Can Avoid Becoming Mere Code Reviewers in the AI Era: Addy Osmani's Answer
Google's Addy Osmani at AI Engineer conference: as AI agents outpace human review, engineers' core value lies in the "verdict" — deciding what's worth building and owning outcomes.
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·2 min
3-Month Roadmap to Becoming an AI/LLM Engineer: A Systematic Learning Guide
A 3-month structured roadmap for developers transitioning into AI/LLM engineering: Python & API basics, LangChain/FastAPI stack, and RAG/Agent projects.
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·3 min
A Former Tencent Engineer's Complete Journey Building a 'Decision Paralysis' Mini Program with AI
A former Tencent engineer used CodeBuddy AI to solo-build a 'Decision Paralysis' mini program — from a phone specs spreadsheet to a fully launched WeChat app.
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·2 min
Daedalus: A Deep Dive into the Ollama-Based Local AI Engineering Runtime
Daedalus is an open-source local AI engineering runtime built on Ollama, covering architecture, debugging, and security. Zero token costs, full privacy, integrates with Claude Code and OpenCode.
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·2 min
Vibe Coding vs AI Engineering: A Practical Enterprise-Level Comparison Guide
A deep dive comparing Vibe Coding vs AI Engineering, with hands-on analysis of Claude Code and Codex, two real projects, and the role of Skills in enterprise AI development.
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