Are massive language models overkill for simple AI tasks?

In this episode, we explore the SLM-First architecture—a smarter, cost-effective approach that routes most queries to small, specialized models (SLMs), and only escalates to larger LLMs when necessary.

What You’ll Learn:
✅ Why using giant LLMs for every task is expensive and inefficient
✅ How SLMs reduce latency, cost, and environmental impact
✅ When and why to escalate to larger models
✅ The tools, strategies, and guardrails that make SLM-first practical today
✅ Real-world savings, performance metrics, and governance benefits

Whether you're building enterprise AI apps or scaling internal tools, this episode breaks down how to do more with less—without compromising quality.