Deep dives, developer case studies, and optimization reviews written directly by our embedded Forward Deployed AI Engineering teams.
Why single-prompt prompts fail when scaled, and how to structure production-grade multi-agent architectures that execute complex, long-running tasks reliably.
A deep dive into the technical design patterns used by our FDE pods to eliminate inference bottlenecks, leverage semantic caching, and build lightning-fast AI interfaces.
Why standard SWEs and strategy consultancies struggle to ship production-grade AI, and how embedded Forward Deployed Engineer (FDE) pods bridge the integration gap.