Product Updates

🗑️ Delete a Single Feature Gate User Override

You can now remove an individual user from a Feature Gate override without touching the rest of the list.

What you can do now

One new endpoint is available on statsigapi.net/console/v1/:

DELETE /console/v1/gates/{gateName}/overrides/userID/{userID}

Why this matters

Before this, removing a single user override meant fetching the full override list, mutating it locally, and re-posting it, which could be risky when test runs are happening concurrently. Now, you can target and remove exactly one user, leaving every other override untouched.

Try it out

Review the full API reference in the Statsig Console API docs.

🚨 PagerDuty Integration for Topline Alerts

Statsig Topline Alerts can now page PagerDuty directly.

What you can do now

• Add PagerDuty services to the Integrations catalog once with a name and Events API v2 routing key.

• Select one or more PagerDuty services per alert in the Notifications settings.

• Test your wiring end-to-end before you rely on it — test pages are tagged [TEST] and never collide with real incidents.

• Deleting a PagerDuty service that an alert still references is blocked, and disabled integrations are clearly flagged.

Why this matters

Topline Alerts catch anomalies in your most critical product metrics, but a notification that in Slack or email isn't always enough when something is on fire. Now, the same alert that fires in Statsig can page your on-call team in PagerDuty, closing the gap between detecting a problem and fixing it quickly.

Try it out

Go to Integrations in the Statsig console, add your PagerDuty service, then open any Topline Alert and configure PagerDuty under Notifications.

Learn more in the Statsig Topline Alerts docs.

✅ Autotune Reviews via Console, Console API, and MCP

You can now submit Autotune changes for review and manage the full review lifecycle across the console, Console API, and MCP.

What you can do now

• Submit Autotune configuration changes for review before they reach production.

• Approve, reject, or cancel in-flight Autotune reviews from the console, via CAPI, or through the MCP.

• Teams with reviews required can now enforce that same approval workflow on Autotunes, the same way they do for gates and experiments.

Why this matters

Teams running Autotune for high-stakes decisions need the same guardrails they have everywhere else. Any change to a live Autotune can shift traffic allocation immediately, so being able to require an approval before it goes out matters. Reviews are now consistent across gates, experiments, and Autotunes.

Try it out

If you have the Statsig MCP set up, try a prompt like:

"Using the Statsig MCP, open a review to update the winner threshold on autotune_name and submit it for approval."

Learn more in the Statsig Reviews docs.

🔐 Granular Delete Permission for Configs

You can now separate the ability to delete configs from the ability to edit them.

What you can do now

• Manage Edit, Archive, and Delete as distinct permissions on your Role Permissions page

Why this matters

Previously, delete was bundled into a single "Edit Delete Configs" permission with no way to separate them. Now, you can grant edit access broadly and keep delete access narrow, without having to create workarounds or roles with too many extra permissions.

FYI!

This is opt-in and not on by default. To enable granular delete permissions for your organization, contact your Statsig account team. Once enabled, the separate Delete permission will appear on your Role Permissions page under Project Settings.

Try it out

Learn more in the Statsig Access Management docs.

🔬 Experiment Reviews via Console API and MCP

The full experiment review lifecycle is now accessible over the Console API and the Statsig MCP.

What you can do now

We now have eight new CAPI endpoints and nine new MCP tools cover the complete review lifecycle:

• Create a review proposing a change to an experiment

• List an experiment's reviews, newest first

• Get a single review including status, proposed change, author, and reviewers

• Look up who is eligible to approve or reject

• Edit a pending review's metadata

• Approve or reject an in-flight review

• Cancel a pending review

• Commit an approved review to apply it to the live experiment

Why this matters

Before, creating and moving an experiment review through approval required the console, blocking any automated workflow that touched a review-gated experiment. Now you can propose, approve, and commit experiment changes entirely through the API or MCP, with no manual console step in the way.

Try it out

If you have the Statsig MCP set up, try a prompt like:

"Open a review to make a decision on experiment_name, shipping the Test group."

Review the full API reference in the Statsig Console API docs.

🔎 Audit Overrides Across Your Entire Project

You can now query all overrides across your project in a single API call.

What you can do now

We now have one new endpoint available on statsigapi.net/console/v1/:

GET /console/v1/overrides

Why this matters

Before , finding where a user was overridden meant querying each gate, experiment, and layer one by one. Now you can audit overrides project-wide in a single call, whether you're debugging unexpected behavior for a specific user, running a compliance audit, or cleaning up override sprawl.

Try it out

Review the full API reference in the Statsig Overrides Audit docs.

📣 Follow Dynamic Configs

You can now follow and unfollow Dynamic Configs to get notified when they're updated.

What you can do now

• Follow a Dynamic Config to receive notifications whenever it's updated

• Unfollow at any time to stop receiving notifications

Why this matters

Dynamic Configs often control things like API settings and rollout thresholds. Being able to follow means the right people get notified the moment a Dynamic Config updated, without having to watch the console or find out after the fact.

Try it out

Open a Dynamic Config in the Statsig console and click Follow to subscribe to updates.

Learn more in the Statsig Console docs.

🔍 Feature Gate Reviews in the Console API

The full feature gate review lifecycle is now exposed over the Console API.

What you can do now

Eight new endpoints cover the complete review lifecycle:

POST /gates/:id/reviews create a review with the proposed change GET /gates/:id/reviews list reviews, newest first GET /gates/:id/reviews/:reviewID get a single review PUT /gates/:id/reviews/:reviewID edit metadata or content PUT /gates/:id/reviews/:reviewID/approve approve PUT /gates/:id/reviews/:reviewID/reject reject DELETE /gates/:id/reviews/:reviewID cancel an in-flight review GET /gates/:id/eligible_reviewers look up eligible reviewers

Why this matters

Before , creating and moving a review through approval required the console, blocking any automated workflow that touched a review-gated gate. Now you can propose, approve, and commit gate changes entirely through the API, with no manual console step in the way.

Try it out

Review the full API reference in the Statsig Console API docs.

🗄️ Parameter Store Management in the Statsig MCP

You can now create and manage Parameter Stores directly through the Statsig MCP.

What you can do now

Three new tools are available on api.statsig.com/v1/mcp:

• Create_Param_Store

• Update_Param_Store

• Delete_Param_Store

Why this matters

Now, you can create a store, define its parameters, and point them at a gate or experiment without leaving your agent flow, making end-to-end feature provisioning possible for the first time.

Try it out

If you have the Statsig MCP set up, try a prompt like:

• "Using the Statsig MCP, create a Parameter Store called checkout-config and add a static boolean parameter "express_checkout_enabled" set to true.

Learn more in the docs: Statsig MCP Overview.

🧪 Leaner Experiment Reads

Experiment reads just got a lot leaner and easier.

What you can do now

Trimmed and batched experiment reads

• Fetch multiple experiments in a single call instead of one round-trip per experiment.

• A single experiment trims from ~66 fields down to just what you ask for, achieving up to 95-99% context reduction.

Why this matters

For agentic workflows reasoning across many experiments, pulling full payloads burns through context windows fast. Field trimming and batching keep those workflows lean.

Learn more in the docs: Statsig MCP Overview.