Labs
Building a data flywheel for our agent harness
An observability pipeline that reads production traces at corpus scale, names recurring failure modes, and proves the fix held.
Comparisons
Deep dives into the infrastructure, architecture, and technical decisions behind Conversion.
Labs
Our text-to-query agent went from 45 seconds on frontier models to 2 seconds on GLM 5.3 Flash, with the same accuracy at 1/20 the cost. This post describes the architecture, evaluation loop, and lessons learned.
Engineering (6)
Labs
An observability pipeline that reads production traces at corpus scale, names recurring failure modes, and proves the fix held.
Labs
A median request carried 150,000 tokens. Most of our context work since comes down to one move, applied repeatedly.
Labs
How and why we made our harness model-agnostic, and what per-turn portability actually cost us.
Engineering
We’re sharing how we power marketing automation at scale using Temporal. By rethinking how workflows run, update, and scale, we’ve built a system that reliably handles millions of contacts and long-lived automations without breaking a sweat.
Engineering
This article dives into how we designed and built the data connector and data synchronization platform — the component responsible for syncing millions of our customers’ most important business records in from and out to their CRM’s every day.
Engineering
How we built the service-to-service communication layer behind Conversion, handling over 30 million requests a day across 350+ endpoints.