#AI testing skills
860 related articles
·2 min
AI Skills in Practice: How Test Engineers Can Automate API Testing and Generate Test Cases at Scale
Learn how AI Skills are transforming software testing. This guide covers Skill architecture, learning paths, and real-world applications in API automation and WebApp testing.
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·3 min
6 AI Testing Skills Covering the Full Workflow, Boosting Efficiency Several Times Over
6 AI Skills for test engineers: test case generation, PRD-to-XMind, JMeter scripts, Playwright automation, performance reports, and requirement checklists—completing 2-3 days of work in half a day.
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·3 min
MCP vs Skills: Understanding the Key to AI Testing Efficiency
Understand the key differences between MCP (Model Context Protocol) and Skills through practical analogies and real testing scenarios to boost AI-driven test automation efficiency.
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Claude Code Skills Encapsulation: Maki…
·1 min
Claude Code Skills Encapsulation: Making AI Testing Tools Truly Efficient and Reusable
Learn how to encapsulate Claude Code Agent Skills for test case design. Solve prompt repetition pain points with on-demand loading and skill reuse techniques.
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Tutorials·3 min
Supabase Real-World Testing: How MCP+Skills Enable AI Agents to Safely Operate Databases
Supabase's experiments show how MCP+Skills solve security gaps when AI agents operate databases, with three key principles for writing effective Agent Skills.
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Tech Frontiers·2 min
Must-Know AI Skills for Software Testing Interviews in 2026: Four Core Competencies & Top Interview Questions Explained
In 2026, AI skills are a hard requirement for software testing roles. Learn the four core competencies enterprises demand, top interview questions with answer frameworks, and a complete learning path.
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·3 min
How to Interview Engineers in the AI Era: Practical Insights on Restructuring the Interview Process
When AI coding tools render traditional algorithm interviews ineffective, how should teams restructure? Insights from a year of practice on evaluating systems thinking, problem decomposition, and human-AI collaboration.
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·3 min
NLP/ML PhD Job Search: Paid Resource Recommendations and Preparation Strategies for Research Scientist Interviews
A guide to paid resources for NLP/ML PhD students preparing for Research Scientist interviews, covering coding, ML fundamentals, system design, and mock interviews with budget allocation strategies.
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·2 min
Do Codex Skills Actually Save Tokens? A Six-Run Task-Size Benchmark Test
A six-run task-size benchmark tests whether Codex Skills actually save tokens. Data reveals cost-benefit performance across different task complexities.
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·3 min
M.A.R.A: Training AI Tanks to Fight from Scratch Using Reinforcement Learning
Deep dive into how the M.A.R.A project trains AI tanks through reinforcement learning, from basic movement to 2v2 team coordination, exploring MARL, self-play, and adversarial game AI.
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·2 min
Dynamic Workflows: A New Paradigm for AI-Driven Quantitative Strategies
Explore how dynamic workflows are transforming quantitative strategy development. From agent orchestration to adaptive strategy iteration, discover the potential and challenges of AI-driven workflows.
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Third-Party Cybersecurity Evaluations …
·2 min
Third-Party Cybersecurity Evaluations of OpenAI Models: A Deep Dive into Methodology and Industry Impact
An in-depth analysis of third-party cybersecurity evaluation methodologies for OpenAI models, covering red teaming, vulnerability discovery assessment, risk classification, and impact on AI governance.
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·3 min
JustInterview.ai Deep Dive: How an AI Full-Cycle Recruitment Platform Achieves 20x Faster Hiring
Deep dive into how JustInterview.ai uses AI interviews, coding tests, and Vibe Coding challenges to cover the full recruitment pipeline from JD to offer, enabling 20x faster hiring.
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·2 min
AI Video Generation Goes Viral: When AI Editing Makes Professional Creators Feel Outclassed
A viral social media post reveals stunning advances in AI video generation. From Sora to Runway, AI tools are reshaping content creation — a deep dive into the tech, controversies, and creator strategies.
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·3 min
Does Your School Matter for Breaking into Machine Learning? The Truth About Credentials vs. Capability
Does school background really matter for entering machine learning? This article analyzes the real impact of credentials and provides more effective strategies for building competitiveness.
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·3 min
Debunking 8 Myths About GenAI in Software Engineering: The Truth Behind AI-Powered Programming
An in-depth analysis of 8 common myths about GenAI in software engineering, covering AI replacing programmers, code quality, productivity, security, and compliance.
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·3 min
The Complete Machine Learning Learning Roadmap: From Anxiety to Clarity
Overwhelmed by machine learning? This practical ML roadmap breaks the journey into three phases—math basics, classical ML, and deep learning—with mindset tips and project strategies for engineers.
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·2 min
Studio Pedagogy: The Deep Logic and Practical Guide to Project-Based Learning
An in-depth analysis of studio pedagogy's core principles and implementation, exploring how this project-based learning model from art and design education applies to programming, AI, and tech education.
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·3 min
Math First or Build Cool Projects? A Deep Dive into Technical Learning Paths
An Indian undergrad faces a tech path dilemma: stick with math-first fundamentals or pivot to flashy projects? Deep analysis of math vs. project experience for quant research and OR careers.
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·3 min
From DevOps to MLOps: Market Demand, Transition Path, and Practical Advice
In-depth analysis of transitioning from DevOps to MLOps: core differences, market demand, required skills, and a practical three-step path for operations engineers making rational career decisions.
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