#software testing interview
115 related articles
·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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·7 min
The Complete Guide to LLM Application Engineer Interviews: Six High-Frequency Agent Topics
A focused guide to core LLM application engineer interview topics, covering agent architecture, Multi-Agent, Langfuse evaluation, security, and RAG optimization.
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·2 min
AI Testing Platform in Action: A Complete Guide to Accelerating Your Testing Workflow
Deep-dive into AI testing platforms: from auto-generating test cases from requirements docs to API testing, performance testing, and log analysis. Prepare for big tech interviews.
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·4 min
UK Sovereign AI: How Cosine AI Is Punching Above Its Weight Against American Compute Dominance
Cosine AI founder reveals how the UK's first sovereign LLM is being built — from government compute grants and RL credit attribution to multi-agent orchestration and synthetic data pipelines.
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·2 min
Which Coursera Advanced AI Courses Are Worth as Much as an Internship? Top Picks
Can online courses replace internships? We break down the real value of MLOps, Generative AI, and Deep Learning courses on Coursera, plus 3 strategies to get internship-level results.
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·4 min
Former OpenAI Researcher Warns: 70% Chance AI Spins Out of Control
Former OpenAI researcher Daniel Kokotajlo, who forfeited $2M in equity, warns of a 70% chance AI leads to catastrophic outcomes and superintelligence by 2029.
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·2 min
Getting Started with Codex: A Practical Guide to OpenAI's AI Coding Assistant
A practical guide to OpenAI Codex: core features, Codex vs. Claude Code comparison, and why the Codex+DeepSeek combo doesn't work. Avoid common pitfalls and boost your coding productivity.
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·3 min
The Complete Guide to Looping Engineering: Building Efficient Agent Loops from Scratch
A deep dive into Looping Engineering — covering the five core loop elements (Trigger, Goal, Judgment, Feedback, Memory), when to use loops, and a step-by-step guide to building a topic-selection loop with Claude Code.
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·3 min
Agent Performance Evaluation: A Three-Layer Framework and Engineering Implementation Guide
A deep dive into the three-layer AI Agent evaluation framework — outcome, process, and system layers — covering trajectory evaluation, tool call accuracy, automated testing, and key engineering challenges.
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·3 min
AI/ML Students Lost in Job Search? A Deep Comparison of Four Career Paths and How to Choose
AI/ML students unsure which career path to pursue? Compare AI engineering, SDE, PM, and UI/UX in depth — with honest entry barriers and a practical self-assessment framework.
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·3 min
CS Students' Summer Prep: How to Strategically Choose Between ML Internships and Data Analytics Roles
How should a CS+Stat junior efficiently prep for data/ML internships? We break down the real market gap, skill priorities, and a focused 3-month strategy.
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·3 min
AI Tool Selection Guide for Test Engineers: A Hybrid Approach to Avoid Three Common Pitfalls
How should test engineers choose AI tools? This guide breaks down the pitfalls of pure AI solutions and recommends a hybrid strategy using tools like DeepSeek, TRAE, Claude Code, and Skill encapsulation.
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After Getting Started with AI/ML: Shou…
·3 min
After Getting Started with AI/ML: Should You Pursue an Internship or Continue Studying?
Already trained models and implemented neural nets from scratch — should you apply for internships or keep studying? A practical guide to entry-level AI roles and how to advance.
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·3 min
Programmer to AI Engineer: You're Already 80% There — Here Are the 6 Skills You're Missing
Programmers transitioning to AI engineering aren't starting from scratch. Learn the 6 core skills — LLM APIs, RAG, prompt engineering, LLMOps — needed to make the leap.
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·3 min
AI Agents Are Reshaping Software Testing: A Practical Guide from Cursor to LangChain
A deep dive into AI-powered testing: Cursor Skills, Coze agents, and LangChain multi-agent systems for automated test case generation, BDD, and review workflows.
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·3 min
GPT-5.6 and ChatGPT Work Launch: AI Evolves from Conversational Assistant to Task Executor
OpenAI launches the GPT-5.6 family (Sol/Terra/Luna), ChatGPT Work, a new desktop app, and Hosted Sites — marking AI's evolution from Q&A assistant to autonomous task executor.
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·4 min
The Complete Roadmap from DevOps to MLOps: Skill Transfer and Toolchain Guide
How can DevOps engineers transition to MLOps? This guide explains the core differences between MLOps and DevOps, offers a phased learning path, tool recommendations (MLflow, DVC, Kubeflow), and practical project ideas.
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·4 min
6 Months of Self-Taught Machine Learning: A Complete Roadmap from Zero to Job-Ready
A self-learner completed a full progression from math foundations and core ML to deep learning in 6 months—hand-writing a Transformer and implementing gradient boosting from scratch. This article breaks down the highlights and blind spots of this real roadmap.
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·6 min
AI Agent Development Learning Path: Four Stages from Zero to Hands-On Projects
A systematic breakdown of the AI agent development learning path, covering four stages: fundamentals, RAG knowledge bases, tool use, multi-agent collaboration, and hands-on projects.
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·4 min
The Complete AI Agent Development Learning Path: From Zero to Enterprise-Grade Practice
A systematic AI Agent development learning path covering fundamentals, prompt engineering, tool calling, multi-agent collaboration, and hands-on practice with LangChain, CrewAI, and Dify.
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