4d ago · 7 min read · As platform engineering evolves, we are constantly battling alert fatigue. We run our vulnerability scanners, generate endless Software Bill of Materials (SBOMs), and drop massive PDF reports onto dev
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May 1 · 10 min read · Automated regression testing is no longer just about rerunning test cases after every change. In modern systems, it’s about ensuring that rapid releases, distributed architectures, and constant update
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Mar 18 · 15 min read · Automated Unit Tests, or AUT, are a concept that most developers do not initially see as beneficial. When I was introduced to AUT, my reaction was was, “I’m going to write buggy code, to test my buggy
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Mar 17 · 4 min read · Writing manual test cases is a fundamental responsibility for QA engineers. However, generating comprehensive test scenarios for every web form can be repetitive and time-consuming. To explore how AI
Join discussionFeb 12 · 10 min read · If you just want the highlights, here’s a quick summary before we dive in 👇 TL;DR AI testing tools now range from AI-assisted helpers to fully autonomous agents. A new category — AI + human layer (managed AI QA) — combines automation with expert v...
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Feb 7 · 1 min read · In a world where applications evolve rapidly and delivery cycles grow shorter, ensuring software quality is no longer optional. This is where Testing Automation becomes a strategic ally for development and QA teams. Testing Automation involves using ...
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Jan 31 · 14 min read · Shipping Copilot Studio agents without systematic, automated testing is risky: large language models (LLMs) are non‑deterministic, topic routing can drift, and integrations fail in ways casual “chat tests” won’t catch. Microsoft’s Copilot Studio Kit ...
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Jan 27 · 7 min read · The promise of Large Language Models (LLMs) is immense, but so is the challenge of ensuring their output quality. As AI-assisted development becomes ubiquitous, a new adversary has emerged: ‘AI Slop.’ This isn't just about occasional errors; it's the...
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Jan 14 · 6 min read · Preface In the field of quantitative trading, the execution of strategies often requires precise programming control and complex system integration. However, with the advancement of artificial intelligence and natural language processing technologies...
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