Use Cases

Coding Models

Repository-level coding demands more than a correct function. Diagnose failures across editing, testing, and debugging, then train with expert reasoning about real codebases and the dependencies that connect them.

Illustrative repository analysis

Where models
fall short

From diagnosis to improvement

BakeLens

Trace the coding pipeline

  • Follow the complete coding chain through the edit-test-debug loop to locate where the model’s approach breaks down.
  • Classify failures by root cause, connecting an incorrect result to the reasoning or assumptions behind the change.
  • Measure cross-file regressions to identify when a fix in one part of the repository breaks behavior in another.
Proof

Build repository-level expert data

  • Use real repository tasks annotated by senior engineers, with reasoning that explains the steps taken through the codebase.
  • Provide debugging traces that identify the root cause and explain why the proposed fix addresses it.
  • Build integration test data around cross-file dependencies and edge cases, extending coverage beyond isolated function behavior.

What you get

Coding Pipeline Diagnosis
A view of where the model fails in the edit-test-debug loop, how often those failures occur, and the root causes involved.
Expert Coding Datasets
Repository-level tasks annotated by senior engineers with step-by-step rationale, including the reasoning behind debugging and implementation decisions.
Integration Evaluation Suite
Tests designed to catch cross-file and cross-module failures, so evaluation reflects the behavior of changes within a connected codebase.

Have a use case in mind?

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