@hemnam

When Prompts Go Wrong: Hidden Risks in AI Every QA Engineer Must Know

18h ago · 6 min read · As I continue my learning journey in Generative AI, today I explored something critical: Prompt misuse and security risks While prompt engineering helps us get better results, poorly designed prompts

Prompt Engineering Is a Skill: How QA Engineers Make AI Reliable

May 4 · 7 min read · As I continue documenting my daily learning in Generative AI, today’s focus was on prompt engineering—and it became clear very quickly that prompting is not guesswork or experimentation. From a QA per

Why One Metric Is Never Enough to Evaluate Generative AI

Apr 30 · 3 min read · As I continue documenting my daily learning, today I focused on model evaluation for Generative AI, specifically understanding ROUGE, BLEU and BERT Score. These metrics are commonly used to evaluate t

Fine‑Tuning Isn’t Optional: How QA Engineers Make AI Models Production‑Ready

Apr 29 · 4 min read · As part of my daily learning journey in AI, today I focused on fine‑tuning foundation models and quickly realized something important: Most AI models fail not because they are weak — but because they

Why Foundation Models Fail Without Business Context

Apr 27 · 4 min read · As I continue documenting what I learn each day about AI, today’s focus was on optimizing foundation models for real business use cases, understanding Retrieval‑Augmented Generation (RAG), using AI ag