> For the complete documentation index, see [llms.txt](https://docs.lleverage.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.lleverage.ai/administer-and-govern/rollout-and-operations/moving-changes-to-production.md).

# Moving changes to production

Treat testing and publishing as operational change, especially when Workflows can affect external systems.

A Lleverage change can affect real operational work, so the release question is not only “does it run?” but “is this the version we are prepared to operate?”

## Test with production consequences in mind

Workflow tests are real executions. They can call real Connections and cause real external side effects. Use safe inputs and appropriate environments where the connected system supports them.

Testing should cover the failure and human-handoff paths as well as the happy path.

## Publish deliberately

Builder changes live in Draft. Publishing creates the version used for live execution according to the current active/default version semantics. Publishing can also affect live triggers and schedules.

For material processes, agree who is allowed to publish and what evidence they need before doing so.

## Prefer bounded changes

When changing a live operation:

* know which Project and Workflow are affected;
* understand which triggers, schedules and Connections can be exercised;
* keep unrelated changes out of the same release where practical;
* know how you will recognize a bad outcome quickly;
* know who can stop, correct or replace the live path.

The product supplies versioning and execution evidence; the release policy remains an organisational decision.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.lleverage.ai/administer-and-govern/rollout-and-operations/moving-changes-to-production.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
