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

# Patterns

> Let Loop investigate your traces on a schedule and record recurring problems and trends as patterns, each with supporting evidence and a suggested fix.

export const feature_0 = "Patterns"

export const verb_0 = "is"

[**<Icon icon="scan-search" /> Patterns**](https://www.braintrust.dev/app/~/patterns) uses [Loop](/docs/loop) to investigate your logs and raw trace data for recurring problems and trends, including behavior your scorers don't measure.

A pattern is a saved finding with supporting evidence, an explanation, and a suggested next step.

<Warning>
  {feature_0} {verb_0} in [public preview](/docs/feature-lifecycle) and can change before reaching general availability.
</Warning>

Use Patterns to:

* Find failures affecting a group of users or regressions, whether or not a scorer covers them.
* Track cost and latency drift in recurring LLM calls.
* Discover recurring successes and emerging use cases.
* Give a coding agent a pattern and its evidence as a prompt to implement a fix.

<Tip>
  Follow [Active observability for coding agents](/docs/cookbook/recipes/CodingAgentInsights) to configure Topics facets and a Loop automation that finds recurring problems in coding-agent sessions.
</Tip>

## How discovery works

Patterns are produced by a scheduled [Loop automation](/docs/loop/automations). Each run:

1. Queries recent data according to the automation's instruction and default query range.
2. Investigates findings through queries and individual traces using the [Debugger](/docs/observe/debug-traces).
3. Records findings with supporting evidence, or updates an existing pattern when new evidence matches it.

Loop uses Frequency to measure how often a behavior occurs when trace data can reliably identify it. Findings can also include monitor charts and representative traces. When Frequency cannot be measured, Loop provides trace evidence and recommends how to measure it.

Scheduled runs review active patterns and refresh Frequency measurements. Loop can close a pattern when recent, relevant data shows the behavior has stopped. Missing data or a failed query is not enough. Your closure outcomes and feedback guide later findings. See [Close or reopen](/docs/observe/patterns/review#close-or-reopen).

You can also ask Loop to [find patterns](/docs/loop/capabilities#find-patterns) in an interactive thread. They appear in the same list.

## Requirements

Patterns needs model access and project permissions:

* Braintrust's [built-in models](/docs/admin/ai-providers#available-models) use your monthly [model credits](/docs/plans-and-limits#model-credits) and need no setup if you meet the [requirements](/docs/admin/ai-providers#requirements). To use your own key or continue after credits run out, configure an OpenAI-compatible [AI provider](/docs/admin/ai-providers).
* Anyone who can read the project's logs can read patterns. Closing and reopening a pattern also requires the project's [`Update` permission](/docs/admin/access-control#object-permissions).

## Patterns and Topics

[Topics](/docs/observe/topics) classifies and clusters traces so you can filter and chart them by user intent, sentiment, or issue. Patterns investigates findings in depth. Neither requires the other.

|                     | Topics                                                                                       | Patterns                                                                |
| ------------------- | -------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------- |
| Question it answers | What themes occur most often?                                                                | What keeps happening, why does it matter, and what should we do next?   |
| Output              | A classification on every trace                                                              | A focused set of findings, each with evidence and a suggested fix       |
| Scope               | Broad, across all your traces                                                                | Scans your traces, then investigates a subset of them in depth          |
| Models              | Braintrust built-in models, drawing on your [model credits](/docs/plans-and-limits#model-credits) | The same built-in models by default, or your own configured AI provider |
| Cadence             | Daily pipeline                                                                               | Scheduled Loop automation                                               |

Topics runs as a separate, low-cost pipeline on Braintrust-served models, regardless of your Loop model selection.

Loop can use topic classifications, scores, and human feedback in its investigations. It can also turn a pattern into a facet, scorer, classifier, or monitor to measure the behavior continuously at lower cost. See [Act on a pattern](/docs/observe/patterns/review#act-on-a-pattern).

## Next steps

* [Enable Patterns](/docs/observe/patterns/enable) and configure how often Loop looks for them.
* [Review and act on patterns](/docs/observe/patterns/review) once the first run finishes.
* [Discover insights with Topics](/docs/observe/topics) to classify your traces at a broader scale.
* [Run Loop on a schedule](/docs/loop/automations) for recurring analysis beyond pattern discovery.