Your Tech Stack Has an AI Problem: How to Audit and Fix It in 2026

The Stack That Made Sense in 2022 Might Be Working Against You Now Two years ago, the advice was consistent: pick boring technology. Rails, Django, Postgres, maybe some Redis. Proven tools, well-understood failure modes, strong hiring pools. That advice isn't wrong. But it's incomplete in 2026, because the definition of "boring" is changing fast. The tools that were exotic in 2022 - vector databases, LLM APIs, streaming inference, semantic search - are now table stakes. And teams whose stacks weren't designed to integrate them are spending engineering cycles on plumbing rather than product.