Shelf Blog: Generative AI

When enterprises entrust AI agents with real-world capabilities and decisions (such as responding to customers or processing claims), an urgent question arises: How can we trust what the agent does? AI governance is the answer. It is a framework of policies, controls, and oversight that ensures AI...

Do you know the two main ways to incorporate your company’s knowledge into a language model? You can either retrieve it on-demand (RAG) or “bake” it directly into the model (fine-tuning). But if you make the wrong choice, you’ll end up with a bloated budget, outdated answers, or the need to...

Context engineering is the practice of designing and managing the complete information environment that AI agents use to reason and act. Unlike prompt engineering, which optimizes a single input prompt, context engineering builds a complete system of knowledge, memory, tools, and governance that...

When an AI agent invents a return policy that doesn’t exist or refers to a contract clause that never existed, these are AI hallucinations. In a consumer chatbot, this is simply annoying. In an enterprise agent that responds to customers or makes operational decisions, however, it poses a massive...

We’re still buzzing from last week’s NRF event. Over three days, our team connected with nearly 500 retailers and industry leaders and the energy around what’s possible with AI was palpable. But beyond the excitement, what struck us most were the candid, unfiltered conversations...

San Francisco was buzzing last week, and Dreamforce 2025 made one thing crystal clear: the next era of enterprise is agentic. On the show floor, it was clear that more enterprises are finally realizing what we’ve known for years: data quality is what determines whether GenAI delivers promised ROI...