Browse past weeks of engineering reads.
Developers face high context overhead and token waste when scaffolding AI agents locally and struggle to bridge the gap between development environments and production-grade deployment on Google Cloud.
Developers need a way to reliably control, monitor, and extend AI model generation calls in production agentic applications without modifying core business logic.
Converting a brittle, monolithic sales research AI prototype into a production-ready agent that eliminates silent failures, fragile parsing, and lacks observability.