Joe Rose, president at strategic technology provider JBS Dev , wants to cut through one of the myths of working with generative and agentic AI systems. “It’s a common misconception that your data has to be perfect before you do any of these types of workloads,” he explains. As a recent article in AI Fieldbook outlines , vendors and consultants – not surprisingly – suggest you need huge data lakes and multi-year data transformation programmes respectively. Executives are therefore scratching their heads at it all. The reality is slightly different. “The tooling has never been better than it is now to deal with poor quality data,” says Rose. “It’s almost remarkable what an LLM can understand on a half-written prompt.” It makes sense. If you’ve got such a tool available, then it’s worth utilising that to your advantage – with the correct guardrails in place. The inherent unpredictability of models means a need to handle bad output, which is where the human in the loop comes in.…