Decagon details a self-improving autoresearch loop for inference stack optimization
kimberlywtan · x · 2026-10-29
Decagon engineers Pavi Dhiman and Cyrus Asgari published 'Building an inference stack that improves itself.' Every inference endpoint poses a different optimization problem shaped by model architecture, traffic patterns, hardware, and latency constraints. They built an autoresearch loop of diagnosis, experimentation, and measurement, where each fix exposes the next bottleneck and lessons carry across investigations—aiming for systems that get better at research as they accumulate evidence.
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