It is quite remarkable to see how @DoorDash is currently running artificial intelligence at an incredibly massive scale. To put things into perspective, AI agents completed a total of 130,000 engineering tasks for the company in just a single month.
When a business reaches this immense level of volume, it becomes clear that the base model is no longer the sole factor for success. Operating effectively at this stage requires a completely robust infrastructure. Specifically, organizations must ensure proper agent identity, secure tool access, strict permissions, seamless communication, comprehensive observability, and highly reliable execution.
Understanding these complex systemic needs is precisely the reason @Fetch_ai designed a complete, end-to-end Agent stack instead of merely releasing another standalone AI application.
You can explore the full story and learn more about this development here: https://www.infoq.com/news/2026/08/doordash-flux-cloud-agent/
When a business reaches this immense level of volume, it becomes clear that the base model is no longer the sole factor for success. Operating effectively at this stage requires a completely robust infrastructure. Specifically, organizations must ensure proper agent identity, secure tool access, strict permissions, seamless communication, comprehensive observability, and highly reliable execution.
Understanding these complex systemic needs is precisely the reason @Fetch_ai designed a complete, end-to-end Agent stack instead of merely releasing another standalone AI application.
You can explore the full story and learn more about this development here: https://www.infoq.com/news/2026/08/doordash-flux-cloud-agent/