AI Development

AI development generates more data than traditional workflows: training runs, model checkpoints, generated code, dataset versions. BrontoFarm provides the temporal infrastructure to track, reproduce, and recover every iteration.

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The AI Development Challenge

AI development creates unique storage challenges:

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    Experiment tracking: Which dataset + model + hyperparameters produced this result?
  • -
    Model checkpoints: Hours of training lost when storage fills up or gets corrupted.
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    Dataset versioning: Reproducing results requires exact dataset state.
  • -
    AI-generated code: Copilot and Claude generate code faster than developers can commit.

Traditional Approach vs. Temporal

Manual checkpointing:

"I'll save this model every 10 epochs and hope nothing crashes"

BrontoFarm:

"Every write is preserved. Recover to any point, including mid-epoch."

AI Development Use Cases

Model Training

Every checkpoint preserved automatically. Recover from crashes, compare training runs, branch from any epoch.

  • Automatic checkpoint preservation
  • Instant rollback on failure
  • Compare runs across time

Dataset Management

Version your training data alongside models. Reproduce experiments with exact dataset state.

  • Dataset versioning
  • Reproducible experiments
  • Data lineage tracking

AI-Assisted Coding

AI coding assistants generate code faster than developers commit. Capture everything, decide what to keep later.

  • Every save captured
  • Recover discarded suggestions
  • Full development history

Experiment Tracking

Correlate results with exact system state. No more "which version of the data did that run use?"

  • Timestamp-based correlation
  • Exact state reproduction
  • Branch for variations

Coming Soon: BrontoRepo

In Development

BrontoRepo

Every artifact has a history

BrontoRepo is purpose-built for AI development workflows. Continuous versioning for code, models, and artifacts. Git captures intent. BrontoRepo captures reality.

Learn more about BrontoRepo

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