Picture a five person software team on the morning of a release.
Their coding agents are ready to test fixes, but the environments they need are still coming online.
The clock moves while the backlog grows.
That is a scenario, but the constraint is real.
Daytona, a runtime for AI generated code execution and agent workflows, recently compared sandbox startup times.
In its test, NVIDIA Vera brought 1,000 sandboxes online in 10.8 seconds.
It reached 2,000 in 27 seconds.
The tested AMD EPYC 9755 reached 1,000 in 88.4 seconds.
The interesting part is how that changes a small team's decision.
Instead of owning everything, they can rent the capacity when a release or experiment calls for it.
Low cost GPU power lets a team run more tests before a release and try a new workflow without waiting for fixed capacity.
BHK Cloud offers RTX 3090 compute from $0.15/hr.
Buy Now Pay Later means zero upfront and payment after one month.
https://ai.bhkcloud.com/?utm_source=linkedin&utm_medium=social&utm_campaign=bhk_social_2026w41&utm_content=morning Where does your team lose more time in an AI workflow: running the work or getting the environment ready?
Originally posted on linkedin_personal