AI doesn’t fail because the models aren’t good enough. It fails because the supporting architecture around the LLM, retrieval, memory, orchestration, and control layers is often incomplete or misapplied. Even state-of-the-art models can under deliver when they lack the intelligent scaffolding needed to translate raw capability into real-world performance.

Beyond the Hype At the Innovation Discovery Center, we've seen one pattern repeat itself: for every exciting new AI headline, there are a...