You describe the workload it runs.

No picking 4090 vs A100.
No region debates.
No infra overhead.

Launching April 28 (12:01 AM PDT):
https://www.producthunt.com/prod...

Curious what s been breaking for you when running AI workloads.

I ve been working in the AI + infrastructure space, building distributed systems and execution layers.

For the past few months, I ve been building Jungle Grid focused on removing the need to manually pick GPUs and deal with infra when running AI workloads.

We re launching on April 28th (12:01 AM PDT):
https://www.producthunt.com/prod...

Would love to connect with others working on AI infra or performance-heavy systems.

Most AI workflows still require choosing GPUs, regions, and providers upfront.

In practice, that leads to:

• overpaying for capacity

• jobs failing due to mismatch (OOM, CUDA issues)

• time wasted debugging infra instead of running workloads

At what point does this abstraction break?