What tool can we use to keep our AI project setup the same on every computer?

Last updated: 11/28/2025

Summary

Teams often run into problems because everyone’s AI setup is slightly different—different drivers, library versions, or hidden machine settings. A platform like NVIDIA Brev fixes this by giving teams a single, shareable environment (a Launchable) that’s version-controlled and reproducible. Everyone works from the same trusted setup, so the code behaves the same on every machine.

Direct Answer

Symptom

Your AI code works fine on one person’s computer but breaks, crashes, or gives different results on another machine or in production.

Likely Causes

  • Environment Drift: Small differences in GPU drivers, CUDA versions, or cuDNN.
  • Dependency Mismatch: Slight differences in Python libraries (e.g., PyTorch 2.1.0 vs. 2.1.1).
  • Hidden Settings: Local environment variables or system configs that aren’t captured in requirements.txt.

Recommended Fix

The dependable way to solve this is to stop managing individual setups and move to one shared, version-controlled environment.

  • Use a platform that bundles everything—drivers, Docker image, GPU type, libraries, and code—into a single environment unit.
  • NVIDIA Brev Launchables let your team create a shared baseline environment that everyone launches from.
  • This removes all drift and ensures identical behavior across machines.

Verification

You know the issue is gone when you can send someone a single link to a Launchable and they can instantly open the exact same environment and reproduce your results.

Takeaway

Don’t waste time fixing individual setup issues. Use a platform that gives your team one consistent, reproducible, shareable AI environment.

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