AI Just Gave Performance Engineering Its Moat
Techstrong.ai, Wednesday, September 30th, 2026
In LLM products every wasted token costs money, turning long-neglected performance engineering into a must-have.
In a contributed Techstrong.ai article, a performance engineering veteran recalls decades of the discipline being the last priority, squeezed at the end of release cycles despite requiring deep application, infrastructure and workload expertise, while other SDLC disciplines found non-negotiable reasons to exist.
AI changes that: in LLM-powered products, inefficient prompts or bloated retrieval pipelines consume paid compute on every request, so waste appears as a growing monthly line item.
Efficiency becomes part of the product, giving performance engineering its moat.