> ## Documentation Index
> Fetch the complete documentation index at: https://docs.weaveos.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Introducing Silk 1

> Upgraded code output model. Better scores, clear reasoning, and calibration that learns from your team.

## What's changing

We've upgraded the model that scores your PRs.

Scores are now significantly more accurate — **3.3x** reduction in average prediction error — especially for complex refactors and cross-file changes.

Every score also now includes a plain-language explanation of how the model arrived at its estimate.

## What stays the same

Same scoring scale, same API, same reports, same dashboards.

A "3.0" under v2 still means three hours of expert engineer effort. Your integrations and alerts require zero changes.

You can expect a maximum of 5% difference in your overall metric scores with the new model, with most differences coming from a better estimate of bigger PRs.

## What's better

The model understands code at a deeper level:

1. Complexity of each line changed
2. Cross-file dependencies

**It also learns from your team using reinforcement learning**
When you override a score, the model adapts to your codebase's conventions over time.

## What you need to do

Nothing. Both models run side-by-side through the end of 2026, so there's no hard cutoff, you can compare estimates at all times.

During rollout, you'll have access to:

* A side-by-side toggle to compare v1 and v2 scores on any PR.
* V2 will also backfill your historical data, so you'll always be looking at one consistent model — no split in your reporting.
* We also recommend hand-picking a few PRs your engineers know well so we can walk through the estimates together and validate accuracy against your team's judgment.

## Optional: score calibration

After rollout, we suggest running a calibration exercise with your team to fine-tune score thresholds to your engineering culture. This can be scheduled anytime.

## Questions?

Reach out via Slack or at [support@workweave.ai](mailto:support@workweave.ai).


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