Product Updates

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7/13/2026
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🔐 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 niine 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.

6/23/2026
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📣 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.

6/22/2026
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🔍 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.

6/16/2026
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🗄️ 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.

6/11/2026
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🧪 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.

🔓 Read-Only MCP Access

The Statsig MCP now supports read-only users.

What you can do now

Read-only MCP access

  • Users on a read-only role can now connect to the Statsig MCP and use it for analysis workflows.

Why this matters

Now teams can give people who are on a read-only role access to use Statsig MCP for analysis.

Try it out

If you have the Statsig MCP set up, try a prompt like: "Using the Statsig MCP, fetch experiments exp_a and exp_b and show only their hypothesis and primaryMetrics."

Learn more in the docs: Statsig MCP Overview.

🎰 Create Autotunes in the Statsig MCP

Now, you can create an Autotune (multi-armed bandit) experiment directly through the Statsig MCP, no console required.

What you can do now

  • Create an Autotune by describing the arms, success event, exploration and attribution windows, and winner threshold.

  • Autotunes are created as drafts by default, so no traffic is reallocated until you start it from the console.

  • The agent confirms before writing, prompting for confirmation before anything is created.

One new tool is available on api.statsig.com/v1/mcp:

  • Create_autotune

Why this matters

Teams running Autotune for live AI agent experiments can now manage the full setup through agents. Instead of manually configuring a multi-armed bandit in the console, you can describe what you want and let the agent build it, keeping your agentic workflows end-to-end.

Try it out

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

  • "Using the Statsig MCP, create an Autotune called checkout-button-color with a control variant {color: blue} and a treatment variant {color: green}, optimizing for the event 'checkout', with 24hr exploration and attribution windows and a 95% winner threshold."

Learn more in the docs: Statsig MCP Overview.

🗑️ Single-Override DELETE Endpoints in the Console API

You can now delete individual experiment and layer overrides directly via the Console API, no GET-mutate-POST workaround needed.

What you can do now

  • Delete a single conditional or userID override from an experiment or layer via path-param DELETEs.

  • Target a specific environment with an optional environment query param, or omit it for the all-environments bucket.

  • Call these endpoints cleanly from OpenAPI-generated or SDK-based clients, since they use path and query params only with no DELETE body.

Four new endpoints are available on statsigapi.net/console/v1/:

  • DELETE /experiments/:id/overrides/conditional/:type/:name

  • DELETE /experiments/:id/overrides/userID/:userID

  • DELETE /layers/:id/overrides/conditional/:type/:name

  • DELETE /layers/:id/overrides/userID/:userID

:type is gate or segment. :name is the gate or segment name. All four endpoints are idempotent, returning 200 even when no matching override exists.

Why this matters

SDK-based E2E testing frameworks often need to clean up individual overrides between test runs. The previous approach required fetching the full overrides object, mutating it locally, and re-posting it, which is fragile and hard to parallelize. These endpoints make override teardown a single, safe, idempotent call.

Try it out

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

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OpenAI
"Statsig's experimentation capabilities stand apart from other platforms we've evaluated. The ease of use, simplicity of integration help us efficiently get insight from every experiment we run. Statsig's infrastructure and experimentation workflows have also been crucial in helping us scale to hundreds of experiments across hundreds of millions of users."
Paul Ellwood
Head of Data Engineering
SoundCloud
"We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion."
Don Browning
SVP, Data & Platform Engineering
Whatnot
"Excited to bring Statsig to Whatnot! We finally found a product that moves just as fast as we do and have been super impressed with how closely our teams collaborate."
Rami Khalaf
Product Engineering Manager
"Statsig has enabled us to quickly understand the impact of the features we ship."
Shannon Priem
Lead PM
Ancestry
"I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig."
Partha Sarathi
Director of Engineering
"Working with the Statsig team feels like we're working with a team within our own company."
Jeff To
Engineering Manager
"[Statsig] enables shipping software 10x faster, each feature can be in production from day 0 and no big bang releases are needed."
Matteo Hertel
Founder
OpenAI
"Statsig has been an amazing collaborator as we've scaled. Our product and engineering team have worked on everything from advanced release management to custom workflows to new experimentation features. The Statsig team is fast and incredibly focused on customer needs - mirroring OpenAI so much that they feel like an extension of our team."
Chris Beaumont
Data Scientist
"The ability to easily slice test results by different dimensions has enabled Product Managers to self-serve and uncover valuable insights."
Preethi Ramani
Chief Product Officer
"We decreased our average time to decision made for A/B tests by 7 days compared to our in-house platform."
Berengere Pohr
Team Lead - Experimentation
"Statsig is a powerful tool for experimentation that helped us go from 0 to 1."
Brooks Taylor
Data Science Lead
"We've processed over a billion events in the past year and gained amazing insights about our users using Statsig's analytics."
Ahmed Muneeb
Co-founder & CTO
SoundCloud
"Leveraging experimentation with Statsig helped us reach profitability for the first time in our 16-year history."
Zachary Zaranka
Director of Product
"Statsig enabled us to test our ideas rather than rely on guesswork. This unlocked new learnings and wins for the team."
David Sepulveda
Head of Data
Brex
"Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly."
Karandeep Anand
President
Ancestry
"We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig."
Partha Sarathi
Director of Engineering
Recroom
"Statsig has been a game changer for how we combine product development and A/B testing. It's made it a breeze to implement experiments with complex targeting logic and feel confident that we're getting back trusted results. It's the first commercially available A/B testing tool that feels like it was built by people who really get product experimentation."
Joel Witten
Head of Data
"We realized that Statsig was investing in the right areas that will benefit us in the long-term."
Omar Guenena
Engineering Manager
"Having a dedicated Slack channel and support was really helpful for ramping up quickly."
Michael Sheldon
Head of Data
"Statsig takes away all the pre-work of doing experiments. It's really easy to setup, also it does all the analysis."
Elaine Tiburske
Data Scientist
"We thought we didn't have the resources for an A/B testing framework, but Statsig made it achievable for a small team."
Paul Frazee
CTO
"We use Statsig's analytics to bring rigor to the decision-making process across every team at Wizehire."
Nick Carneiro
CTO
Notion
"We've successfully launched over 600 features behind Statsig feature flags, enabling us to ship at an impressive pace with confidence."
Wendy Jiao
Staff Software Engineer
"We chose Statsig because it offers a complete solution, from basic gradual rollouts to advanced experimentation techniques."
Carlos Augusto Zorrilla
Product Analytics Lead
"We have around 25 dashboards that have been built in Statsig, with about a third being built by non-technical stakeholders."
Alessio Maffeis
Engineering Manager
"Statsig beats any other tool in the market. Experimentation serves as the gateway to gaining a deeper understanding of our customers."
Toney Wen
Co-founder & CTO
"We finally had a tool we could rely on, and which enabled us to gather data intelligently."
Michael Koch
Engineering Manager
Notion
"At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It's also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us."
Mengying Li
Data Science Manager
OpenAI
"At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities."
Dave Cummings
Engineering Manager, ChatGPT
OpenAI
"Statsig has helped accelerate the speed at which we release new features. It enables us to launch new features quickly & turn every release into an A/B test."
Andy Glover
Engineer
"We knew upon seeing Statsig's user interface that it was something a lot of teams could use."
Laura Spencer
Chief of Staff
"The beauty is that Statsig allows us to both run experiments, but also track the impact of feature releases."
Evelina Achilli
Product Growth Manager
"Statsig is my most recommended product for PMs."
Erez Naveh
VP of Product
"Statsig helps us identify where we can have the most impact and quickly iterate on those areas."
John Lahr
Growth Product Manager
Whatnot
"With Warehouse Native, we add things on the fly, so if you mess up something during set up, there aren't any consequences."
Jared Bauman
Engineering Manager - Core ML
"In my decades of experience working with vendors, Statsig is one of the best."
Laura Spencer
Technical Program Manager
"Statsig is a one-stop shop for product, engineering, and data teams to come together."
Duncan Wang
Manager - Data Analytics & Experimentation
Whatnot
"Engineers started to realize: I can measure the magnitude of change in user behavior that happened because of something I did!"
Todd Rudak
Director, Data Science & Product Analytics
"For every feature we launch, Statsig saves us about 3-5 days of extra work."
Rafael Blay
Data Scientist
"I appreciate how easy it is to set up experiments and have all our business metrics in one place."
Paulo Mann
Senior Product Manager
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