AI gateways are moving from optional infrastructure to a core layer for product teams that need better routing, caching, observability, resilience, and cost control across multiple model providers.
AI features are no longer safe to ship on intuition alone. In 2026, product teams are turning evals into release gates to catch regressions in quality, safety, latency, and cost before users do.
Prompt caching is turning into one of the most practical ways AI product teams reduce latency, control costs, and make repeated LLM workflows production-ready in 2026.
Structured output has become one of the most practical AI engineering skills for web teams in 2026. Here is why schema-driven AI, runtime validation, and typed contracts now matter more than clever prompting.
Traditional SEO vs llms.txt: understand the shift from ranking in SERPs to being cited by AI. Compare strategies, implementation, and what works in 2026.