You probably don’t need to train your own AI model — and in our latest AI Explainer video, we show why!Interview
Most teams think they need custom model training to get real context. But in practice? Training is slow, expensive, brittle, and hard to govern. And for 95% of company use cases, you can get better results faster by pulling in your content at runtime using secure RAG, tailored instructions, and task-specific agents. In this episode of our AI Explainer Series with Box CTO, Ben Kus, we break down: When training actually makes sense (rare, high-risk, ultra-specialized workflows) Why most companies don’t need it — and how RAG + instructions deliver grounded, auditable answers instantly Real patterns from the field: caching, hybrid RAG, and policy-aware prompting to reduce latency, cost, and risk Ben and I would love to hear from you…What is one task in your org that feels like it “needs” a custom model — and what problem are you trying to solve with it? If you’re catching up, you can also check out other highly-requested explainers: Secure RAG for the Enterprise AI-powered Data Ex
