LLM Testing

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Beyond the Checklist: A Practitioner’s Review of IMDA’s LLM Testing Starter Kit

ai, AI (Artificial Intelligence), AI Evaluation, AI Governance, AI safety, Artificial Intelligence, Enterprise AI, Enterprise Technology, Generative AI, IMDA, LLM Testing, Machine Learning, MLOps, Responsible AI, Spritle Blog

Introduction As large language models move from proof-of-concept into production systems that touch real users, real money, and real decisions, the industry has been crying out for structured, actionable guidance on how to test them responsibly. IMDA’s Starter Kit for Testing LLM-Based Applications is a meaningful answer to that call. It arrives at exactly the […]

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Testing Beyond Pass or Fail: A QA Engineer’s Lessons from IMDA’s LLM Testing Starter Kit at Spritle

Adversarial Testing, ai, AI (Artificial Intelligence), AI Application Testing, AI Governance, AI Product Quality, AI Quality Assurance, AI security, AI Security Testing, AI Testing, Artificial Intelligence, Bias Testing, Generative AI, Generative AI Testing, Hallucination Testing, IMDA LLM Testing Starter Kit, LLM Testing, Prompt injection testing, QA Best Practices, QA Engineering, Quality Assurance, Red Teaming, Responsible AI, Semantic Similarity Testing, Software Testing, Spritle Blog, SpritleSoftware

I’ve been in QA for a few years now. I know how testing works. You write a test case. You define the expected result. You run it. It either passes or fails. Simple. So when our team started working on an AI-powered feature, I thought, okay, same process. Different kind of input, but same idea.

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Breaking the Black Box: From Traditional QA to AI Assurance and Governance

ai, AI (Artificial Intelligence), AI & QA Innovation, AI + Compliance, AI Assurance, AI Governance, AI Quality Engineering, AI Risk Management, AI safety, AI Trust and Reliability, AI Validation, Artificial Intelligence, Enterprise AI, Enterprise Technology, Generative AI, Generative AI Testing, LLM Testing, QA, QA Automation, QA Engineering, QA process, Quality Assurance, Quality Engineering, Red Teaming, Responsible AI, Software Testing, Spritle Blog, SpritleSoftware

I recently had the opportunity to review IMDA’s Starter Kit for Testing LLM-Based Applications for Safety and Reliability. As someone who has spent over 14 years in Quality Assurance, I was curious to see how established testing principles are being adapted to address the unique challenges introduced by Large Language Models (LLMs). What I expected

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Testing for Trust: What IMDA’s LLM Testing Starter Kit Teaches Us At Spritle About AI Assurance

Breaking the Black Box: From Traditional QA to AI Assurance and Governance I recently had the opportunity to review IMDA’s Starter Kit for Testing LLM-Based Applications for Safety and Reliability. As someone who has spent over 14 years in Quality Assurance, I was curious to see how established testing principles are being adapted to address

Testing for Trust: What IMDA’s LLM Testing Starter Kit Teaches Us At Spritle About AI Assurance Read More »