Control Feature Flags in Your Own Workflow with the WorkOS API

Feature flags have become standard practice in modern software iteration, but most teams stop at the "click a button in the admin panel" level: operations staff manually add allowlists and toggle percentages in a management UI, creating fragmented processes that are hard to audit. WorkOS has opened up its Feature Flags targeting endpoints in its API, letting developers directly add or remove target organizations and users from their own systems. This article, based on the official documentation, breaks down what these endpoints can do and what "removing a target" really means.

Why Feature Flag Targeting Deserves Its Own API

The core of a feature flag isn't the "on" and "off" states—it's "who it's on for." Targeting determines which organizations and users can see a given flag. Historically, this step relied on manual operations: a product manager receives a customer support ticket, logs into the flag management console, searches for the organization ID, and adds it one by one. As the customer base grows and rollout strategies become more complex, this manual path quickly becomes a bottleneck and is prone to errors.

By exposing targeting as API endpoints, WorkOS essentially hands the question of "who can see the new feature" back to the business system itself. Your internal operations dashboard, customer success tools, or even automation scripts can all become triggers for flags, without needing to switch to a third-party console. For teams that already host their organization and user systems on WorkOS, this reduces the cost of maintaining identity data redundantly across multiple systems.

A Feature Flag is an engineering practice that lets teams dynamically control which users can see a feature without redeploying code. It replaces compile-time branching with runtime evaluation, enabling canary releases, A/B testing, and emergency kill switches to be completed in minutes. Common industry implementations include standalone services like LaunchDarkly, Unleash, and Flagsmith, as well as in-house solutions built on configuration centers.

Targeting is a sub-concept within feature flag systems, referring to the set of rules that define the "scope of effect" for a flag. Rules can match by user ID, organization ID, attributes (such as plan tier or region), or percentage buckets. During evaluation, the system checks targets against rules in priority order, falling back to a default value when no rule matches. Targeting is therefore essentially a lightweight policy engine rather than a simple boolean switch.

Adding and Removing Targets from Your Own System

According to the official documentation, developers can use these targeting endpoints to add organizations and users to a flag's scope, as well as remove them. This enables several typical engineering practices:

• Customer success-driven rollouts: When an enterprise customer requests early access, operations staff can simply check a box in their own dashboard and call the API to add that organization to the flag—no need to wait for engineering involvement.
• Automated allowlists: Connect flag targeting with your internal CRM or contract status so that visibility scope syncs automatically when paid tiers change.
• Internal testing and rollback: QA teams can batch-add internal organizations via scripts and remove them all at once after validation.

The common thread across these scenarios is embedding flag operations into existing workflows, rather than forcing workflows to adapt to the flag tool. For teams that need to frequently adjust rollout scope, the ability to "flip switches in your own system" is more valuable than yet another management console.

What Removing a Target Really Means

The official documentation specifically reminds developers to understand the true semantics of "removing a target." This is an easily misunderstood operation: removing an organization or user from a flag's targeting does not equal turning off the flag's global state, nor does it necessarily mean that user immediately reverts to old behavior—the actual effect depends on the flag's default value and evaluation logic.

From an engineering perspective, it's important to distinguish two types of semantics: "the target is no longer explicitly specified" versus "the target is explicitly excluded." The former simply revokes a targeted grant, and the target may fall back to default rules; the latter may actively exclude the target from the flag. If teams mix these two intents in automation scripts, they risk incidents where they "think it's off but it's actually still in rollout." Therefore, when using targeting endpoints, it's advisable to include removal operations alongside the flag's default state and evaluation priority in test cases, rather than only validating the add path.

In a typical feature flag evaluation model, a flag's final value is determined by multiple layers of rules: explicit targeting rules, percentage rollouts, and default values. When a target is removed, the system skips that targeting rule and continues evaluating downward. If the flag's default value is "on," the user may still see the new feature; only when the default is "off" and no other rule matches will the user revert to old behavior.

"Explicit exclusion" is different—it typically exists as a separate exclusion rule with higher priority than targeting rules, ensuring the target never enters the rollout under any circumstances. Understanding the difference between these two requires first clarifying the flag's evaluation order and default value configuration, which is also where automation scripts are most likely to trip up.

Engineering Recommendations for Implementation

Include targeting changes in auditing. Since flag operations happen in your own system, change records should also stay in your own system. Recording who added or removed which organization from which flag and when can help quickly pinpoint issues when problems arise.

Distinguish between environments and tenants. Organization and user IDs often differ between test and production environments. Automation scripts should avoid hardcoding to prevent accidentally adding targets in production.

Test the removal path as thoroughly as the addition path. Most teams only verify that "the feature is visible after adding," but overlook whether "behavior matches expectations after removal." Given that removal semantics depend on default values, this path deserves even more coverage.

Control call permissions. Targeting endpoints directly determine feature visibility, so their access control should be treated like production configuration to avoid unintended calls.

Summary

By opening Feature Flags targeting as an API, WorkOS points toward a more engineering-oriented way of using flags: a flag is no longer a console you need to log into separately, but an ordinary step in your workflow. What truly requires thought isn't the API call itself, but clarifying what "removal" actually means in your system's semantics.