re:cinq's Napkins

Your platform has grown into an uncontrollable web of tools, integrations, and dependencies. Teams struggle to navigate layers of outdated tech, making even simple changes a nightmare. The result? Slow development, endless troubleshooting, and rising frustration.

Your platform should enable developers, not slow them down. But when teams are stuck waiting for approvals, resources, or fixes, productivity grinds to a halt. If everything has to go through a single system, that system becomes the problem.

When official platforms don't meet developer needs, they find workarounds. Instead of using approved tools, they create their own solutions—leading to inconsistency, security risks, and fragmentation. Shadow IT isn't just rebellion; it's a signal that something is broken.

Managing AI infrastructure should be simple, but dependency conflicts often turn into a nightmare. Different versions of TensorFlow, PyTorch, CUDA, and NVIDIA drivers create compatibility issues that slow down development and break production workflows. Without a standardized approach, teams face constant headaches troubleshooting mismatches and reconfiguring environments.

AI workloads demand high-performance GPUs, but inefficient scheduling leads to bottlenecks and underutilization. When multiple teams compete for limited GPU resources without proper orchestration, jobs get delayed, developers get frustrated, and hardware sits idle. Without an optimized scheduling strategy, scaling AI workloads efficiently becomes nearly impossible.