Most AI readiness assessments measure data quality while ignoring the workflow fragmentation that actually predicts failure. They give you 8/10 while your teams drown in 47 different tools.
Bad examples teach AI boundaries better than good ones. After testing hundreds of few-shot prompts in production at Tallyfy, here is why negative examples consistently improve AI performance by showing what not to do.
The most damaging AI incidents stem from process breakdowns, not technical failures. Here is how to build incident response that addresses the real causes.
Most companies communicate AI changes like feature announcements when they should focus on career growth opportunities. Mid-size companies have a unique advantage here - they can make it personal.
Great prompts are discovered through systematic iteration and testing, not designed upfront. After years of terrible attempts, here is what actually works for professional prompt engineering.
RAG systems dont create new security risks - they amplify whatever data security posture you already have. Weak access controls become glaringly obvious when your AI can retrieve anything.