Yes, you can automatically enable and disable feature flags in GrowthBook by setting start and end timestamps. This functionality is called "Feature Flag Scheduling" and is available for users with Pro or Enterprise plans. Here's how it works: 1. You can set specific start and end dates/times for feature flag rules. 2. The feature flag will automatically turn on at the start time and off at the end time. 3. This scheduling can be applied to various rule types, including force rules, rollout rules, and experiment rules. To set up scheduling for a feature flag: 1. Go to the feature flag you want to schedule. 2. Create a rule (e.g., an override rule). 3. Below the condition targeting, you can create schedule rules with start and end dates/times. It's worth noting that while you can schedule individual rules within a feature flag, turning off the entire feature flag still requires manual intervention. This feature is particularly useful for managing time-sensitive features, such as holiday promotions or temporary experiments. [GrowthBook Docs: Scheduling Features](https://docs.growthbook.io/features/scheduling) [GitHub PR: Feature Flag Scheduling](https://github.com/growthbook/growthbook/pull/765) If you need more granular control or automation beyond simple start/end scheduling, you might consider using GrowthBook's REST API in conjunction with external scheduling tools or scripts to programmatically manage feature flags.

Yes, GrowthBook provides some suggestions for naming conventions for feature flags and experiments. Here are the key recommendations: 1. Be as specific as possible when naming features and experiments. This helps with quick searching and organization [GrowthBook Best Practices](https://docs.growthbook.io/using/growthbook-best-practices#naming). 2. Consider using a format like

<project scope>_<project name>

or include the year, quarter, or team information in the name. For example: - "23-Q4 New user registration modal" - "23-Team3 Simplified checkout flow" This approach allows you to quickly see when the experiment was run or which team worked on it [GrowthBook Best Practices](https://docs.growthbook.io/using/growthbook-best-practices#naming). 3. For experiments related to specific features, you might want to include the feature name in the experiment name. This helps in tracking multiple experiments for the same feature over time [Forum Conversation](https://linen.growthbook.io/t/8099082/are-there-any-naming-convention-best-practices-for-experimen). 4. Consider adding a month/year to the feature name if you plan to run multiple experiments on the same feature. This can help with querying analytics data more easily [Forum Conversation](https://linen.growthbook.io/t/8099082/are-there-any-naming-convention-best-practices-for-experimen). 5. Use camelCase for feature flag names if your codebase primarily uses JavaScript. However, note that as of March 2023, GrowthBook saved feature names in lowercase. There was a feature request to support camelCase, so you may want to check the current status [Forum Conversation](https://linen.growthbook.io/t/10025306/hi-all-thank-you-for-creating-growthbook-it-seems-like-fanta). 6. You can also use tags to describe feature types (e.g., rollout, killswitch, experiment) and feature lifespan (temporary, permanent) [Forum Conversation](https://linen.growthbook.io/t/13689080/hi-all-we-re-starting-a-project-to-integrate-growthbook-and-). Remember, the key is to choose a naming convention that works best for your team and stick to it consistently. This will make it easier to manage and track your features and experiments over time.