diff --git a/content/copilot/concepts/billing-and-usage/copilot-usage-metrics/copilot-metrics.md b/content/copilot/concepts/billing-and-usage/copilot-usage-metrics/copilot-metrics.md
index ef0820a13750..03d45a0b230c 100644
--- a/content/copilot/concepts/billing-and-usage/copilot-usage-metrics/copilot-metrics.md
+++ b/content/copilot/concepts/billing-and-usage/copilot-usage-metrics/copilot-metrics.md
@@ -168,7 +168,7 @@ Users are grouped into the following phases:
 
 | Phase | What it represents |
 |:--|:--|
-| Passive users | The user has not met the engagement threshold for a phase during the period. A passive user may still be using {% data variables.product.prodname_copilot_short %} regularly, for example by asking questions in {% data variables.copilot.copilot_chat_short %} or agent mode without applying any code edits. In the API, this phase is labeled `No Cohort`. |
+| Chat-first users | The user is active but hasn't used a qualifying feature on at least two distinct days in the trailing 28-day window. For example, a chat-first user may be asking questions in {% data variables.copilot.copilot_chat_short %} or agent mode without applying any code edits. In the API, this phase is labeled `No Cohort`. |
 | Phase 1: Code first | The user engaged with code completions and/or agent edits, where {% data variables.product.prodname_copilot_short %} writes changes directly into files in the IDE. Using {% data variables.copilot.copilot_chat_short %} or agent mode without producing code completion or agent edit activity does not qualify on its own. |
 | Phase 2: Agent first | The user engaged with a single {% data variables.product.github %}-based agent surface, such as {% data variables.copilot.copilot_cloud_agent %}, {% data variables.copilot.copilot_code-review_short %}, or {% data variables.copilot.copilot_cli_short %}. Both active engagement with {% data variables.copilot.copilot_code-review_short %} and having it automatically assigned to review a pull request count as the same surface. |
 | Phase 3: Multi-agent | The user engaged with two or more {% data variables.product.github %}-based agent surfaces, or with the {% data variables.copilot.github_copilot_app %}. |
@@ -179,17 +179,17 @@ Phase assignment is recalculated daily from the trailing 28-day window, so a use
 
 The impact dashboard counts every user who was active during the trailing 28-day window and groups each user by their current phase. The phase classification rules are the same, but the dashboard population is broader than the `totals_by_ai_adoption_phase.total_engaged_users` field in API and NDJSON reports, which counts users who were active on a specific day.
 
-Users who haven't met any phase's threshold are grouped into **Passive users**, which is not a measure of inactivity, but a signal that a user's engagement hasn't yet reached the level needed to reliably classify their adoption depth. For example, a user with fewer than two active days in the trailing 28-day window, or one who only lightly uses a surface like {% data variables.copilot.copilot_chat_short %} on {% data variables.product.prodname_dotcom_the_website %}, shows as a passive user.
+Users who haven't met any phase's threshold are grouped into **Chat-first users**, which is not a measure of inactivity, but a signal that a user's engagement hasn't yet reached the level needed to reliably classify their adoption depth. For example, a user with fewer than two active days in the trailing 28-day window, or one who only lightly uses a surface like {% data variables.copilot.copilot_chat_short %} on {% data variables.product.prodname_dotcom_the_website %}, shows as a chat-first user.
 
 Because phase assignment is based on **which surfaces a user engages with**, not simply how many actions they take, a user with high completion volume but no agent usage stays in Phase 1, while a user with lighter but broader usage across agent surfaces progresses to Phase 2 or Phase 3.
 
 For the underlying schema fields, see [AI adoption phase fields](/copilot/reference/copilot-usage-metrics/copilot-usage-metrics#ai-adoption-phase-fields).
 
-The impact dashboard's **adoption multiplier** divides the average amount of pull requests merged for engaged users, which are ones in Phase 1, 2, or 3, by the amount of pull requests merged for Passive users.
+The impact dashboard's **adoption multiplier** divides the average amount of pull requests merged for engaged users, which are ones in Phase 1, 2, or 3, by the amount of pull requests merged for chat-first users.
 
 This shows the relative impact of deeper adoption, independent of how many users fall into each phase. This is a measurement to understand the potential lift that becoming a more engaged user can provide.
 
-For example, if users in the engaged cohorts averaged 20 pull requests/user/month and the passive cohort averaged 10, then the equation is 20 / 10 = 2x multiplier.
+For example, if engaged users averaged 20 merged pull requests per user per month and chat-first users averaged 10, the multiplier is 20 / 10 = 2x.
 
 ### Understanding industry comparisons
 
diff --git a/content/copilot/how-tos/copilot-on-github/set-up-copilot/configure-code-review.md b/content/copilot/how-tos/copilot-on-github/set-up-copilot/configure-code-review.md
index 60679c67336b..b34e3b20500a 100644
--- a/content/copilot/how-tos/copilot-on-github/set-up-copilot/configure-code-review.md
+++ b/content/copilot/how-tos/copilot-on-github/set-up-copilot/configure-code-review.md
@@ -168,3 +168,13 @@ You can configure how {% data variables.copilot.copilot_code-review_short %} com
    * **Let organizations decide**: Organization owners can choose whether to enable {% data variables.product.prodname_copilot_short %} approvals.
    * **Enable for selected organizations**: {% data variables.product.prodname_copilot_short %} approvals are enabled only for the organizations you select.
    * **Disabled everywhere**: Organizations cannot enable {% data variables.product.prodname_copilot_short %} approvals. This is the default.
+
+## Configuring {% data variables.copilot.copilot_code-review_short %} with the API
+
+You can use the {% data variables.product.github %} REST and GraphQL APIs to manage some {% data variables.copilot.copilot_code-review_short %} settings.
+
+* **Enterprise**: Enable or disable {% data variables.copilot.copilot_code-review_short %} for all organizations, or let organization owners decide.
+* **Organization**: Enable or disable {% data variables.copilot.copilot_code-review_short %} when the enterprise lets organization owners decide, set the default review effort level, and configure the runner that {% data variables.copilot.copilot_code-review_short %} uses.
+* **Repository**: Set the review effort level and choose whether reviews use custom instructions and MCP servers.
+
+Other settings on this page, such as maximum review effort, billing, and approvals, are not available through the API. For more information, see [GraphQL API reference for {% data variables.product.prodname_copilot_short %}](/graphql/reference/copilot).
diff --git a/content/copilot/how-tos/copilot-on-github/use-copilot-agents/copilot-code-review.md b/content/copilot/how-tos/copilot-on-github/use-copilot-agents/copilot-code-review.md
index 9c8b1e685595..9188dc2e2f96 100644
--- a/content/copilot/how-tos/copilot-on-github/use-copilot-agents/copilot-code-review.md
+++ b/content/copilot/how-tos/copilot-on-github/use-copilot-agents/copilot-code-review.md
@@ -29,7 +29,7 @@ By default, {% data variables.product.prodname_copilot_short %} leaves a "Commen
 
 {% data variables.product.prodname_copilot_short %}'s review comments work like comments from human reviewers. Add reactions, reply, resolve, or hide them. Any replies you add are visible to other people but not to {% data variables.product.prodname_copilot_short %}.
 
-You can also request a review from {% data variables.product.prodname_copilot_short %} through the {% data variables.product.github %} REST API by requesting `copilot-pull-request-reviewer[bot]` as a reviewer. For more information, see [AUTOTITLE](/rest/pulls/review-requests#request-reviewers-for-a-pull-request).
+You can also use the {% data variables.product.github %} REST API to request reviews from {% data variables.product.prodname_copilot_short %} and to identify reviews and comments from {% data variables.copilot.copilot_code-review_short %}. For more information, see [AUTOTITLE](/rest/pulls/review-requests#request-reviewers-for-a-pull-request), [AUTOTITLE](/rest/pulls/reviews), and [AUTOTITLE](/rest/pulls/comments).
 
 ## Work with suggested changes
 
diff --git a/content/copilot/how-tos/use-copilot-agents/use-code-review.md b/content/copilot/how-tos/use-copilot-agents/use-code-review.md
index 8e551a13812a..3cd3669768f1 100644
--- a/content/copilot/how-tos/use-copilot-agents/use-code-review.md
+++ b/content/copilot/how-tos/use-copilot-agents/use-code-review.md
@@ -64,7 +64,7 @@ These instructions explain how to use {% data variables.copilot.copilot_code-rev
 
    Any comments you add to {% data variables.product.prodname_copilot_short %}'s review comments will be visible to humans, but they won't be visible to {% data variables.product.prodname_copilot_short %}, and {% data variables.product.prodname_copilot_short %} won't reply.
 
-You can also request a review from {% data variables.product.prodname_copilot_short %} through the {% data variables.product.github %} REST API by requesting `copilot-pull-request-reviewer[bot]` as a reviewer. For more information, see [AUTOTITLE](/rest/pulls/review-requests#request-reviewers-for-a-pull-request).
+You can also use the {% data variables.product.github %} REST API to request reviews from {% data variables.product.prodname_copilot_short %} and to identify reviews and comments from {% data variables.copilot.copilot_code-review_short %}. For more information, see [AUTOTITLE](/rest/pulls/review-requests#request-reviewers-for-a-pull-request), [AUTOTITLE](/rest/pulls/reviews), and [AUTOTITLE](/rest/pulls/comments).
 
 ## Enabling automatic reviews
 
diff --git a/content/copilot/reference/copilot-usage-metrics/copilot-usage-metrics.md b/content/copilot/reference/copilot-usage-metrics/copilot-usage-metrics.md
index 1483a8861199..532e1b51d04d 100644
--- a/content/copilot/reference/copilot-usage-metrics/copilot-usage-metrics.md
+++ b/content/copilot/reference/copilot-usage-metrics/copilot-usage-metrics.md
@@ -53,8 +53,8 @@ These metrics appear in the impact dashboard, which groups users into adoption c
 |:--|:--|
 | Engagement trends | How the organization's adoption cohort mix and pull request throughput (total pull requests merged per month) have changed over the last six months. |
 | Feature engagement | Number of active users who engaged with each included {% data variables.product.prodname_copilot_short %} feature on at least two distinct days during the inclusive 28-day window. |
-| Adoption cohort distribution | Share of licensed users grouped into each adoption phase (Passive users, Phase 1, Phase 2, Phase 3) for the period. Passive users correspond to the `No Cohort` value in the API. |
-| Adoption multiplier | Compares engaged users (Phase 1, 2, or 3) against passive users on code shipped (pull requests merged per user per month) and time to merge pull requests, to show the relative impact of deeper {% data variables.product.prodname_copilot_short %} adoption. |
+| Adoption cohort distribution | Share of licensed users grouped into each adoption phase (Chat-first users, Phase 1, Phase 2, Phase 3) for the period. Chat-first users correspond to the `No Cohort` value in the API. |
+| Adoption multiplier | Compares engaged users (Phase 1, 2, or 3) against chat-first users on code shipped (pull requests merged per user per month) and time to merge pull requests, to show the relative impact of deeper {% data variables.product.prodname_copilot_short %} adoption. |
 | Recommendations | Suggested actions, such as configuring {% data variables.copilot.copilot_cloud_agent %} or enabling {% data variables.copilot.copilot_code-review_short %}, based on the organization's current cohort distribution. |
 
 ## Code generation dashboard metrics
@@ -236,17 +236,17 @@ The 28-day aggregate reports (`enterprise-28-day` and `organization-28-day`) are
 
 #### {% data variables.product.prodname_copilot_short %} feature engagement fields
 
-The optional `copilot_feature_engagement` object summarizes the report's rolling active-user population and engagement with seven features. For the `day_totals` entry whose `day` matches `report_end_day`, `copilot_feature_engagement.active_user_count` equals the sum of the mutually exclusive `totals_by_ai_adoption_phase[].users_in_phase_28d` values.
+The optional `copilot_feature_engagement` object summarizes the report's rolling active-user population and engagement with nine features. For the `day_totals` entry whose `day` matches `report_end_day`, `copilot_feature_engagement.active_user_count` equals the sum of the mutually exclusive `totals_by_ai_adoption_phase[].users_in_phase_28d` values.
 
-Counts for individual features overlap because a user can engage with more than one feature. Do not add the `engaged_user_count` values together. The initial feature set reports active and passive {% data variables.copilot.copilot_code-review_short %} as separate features. It does not include {% data variables.copilot.copilot_chat_short %} or {% data variables.product.prodname_vscode_shortname %} Agent.
+Counts for individual features overlap because a user can engage with more than one feature. Do not add the `engaged_user_count` values together. The feature set reports active and passive {% data variables.copilot.copilot_code-review_short %} as separate features.
 
-{% data variables.copilot.copilot_chat_short %} is planned for a later release after 28 consecutive days of data have been collected and report consumers support the additional entry.
+The array also includes {% data variables.copilot.copilot_chat_short %} (`chat`) and the {% data variables.product.prodname_vscode_shortname %} Agents window (`vscode_agent`). These two features are reported for engagement only and aren't used to classify adoption phases. `chat` covers {% data variables.copilot.copilot_chat_short %} use captured by usage metrics, including agent mode. Users counted under `agent_edit` are also counted under `chat`. Reports for windows before these features were added can contain only the original seven entries.
 
 | Field | Type | Nullable | Description |
 |:--|:--|:--|:--|
 | `copilot_feature_engagement.active_user_count` | `integer` | No | Nonnegative number of distinct active users in the inclusive 28-day report window. A valid zero-user report sets this field to `0`. |
-| `copilot_feature_engagement.totals_by_feature` | `array` | No | Feature engagement counts. The initial array contains exactly one entry for each of these values: `code_completion`, `agent_edit`, `code_review_passive`, `code_review_active`, `cloud_agent`, `copilot_cli`, and `github_app`. A valid zero-user report includes all seven entries with `engaged_user_count` set to `0`. |
-| `copilot_feature_engagement.totals_by_feature[].feature` | `string` | No | Feature identifier. In this object, `github_app` represents the {% data variables.copilot.github_copilot_app_short %}. This differs from the `copilot_app` value used in activity breakdown arrays such as `totals_by_feature`. |
+| `copilot_feature_engagement.totals_by_feature` | `array` | No | Feature engagement counts, sorted alphabetically by `feature`. The array contains exactly one entry for each of these values: `agent_edit`, `chat`, `cloud_agent`, `code_completion`, `code_review_active`, `code_review_passive`, `copilot_cli`, `github_app`, and `vscode_agent`. A valid zero-user report includes all nine entries with `engaged_user_count` set to `0`. |
+| `copilot_feature_engagement.totals_by_feature[].feature` | `string` | No | Feature identifier. In this object, `github_app` represents the {% data variables.copilot.github_copilot_app_short %}. Activity breakdown arrays such as `totals_by_feature` use `copilot_app` instead. The `vscode_agent` value represents the dedicated {% data variables.product.prodname_vscode_shortname %} Agents window, not agent mode in the editor. |
 | `copilot_feature_engagement.totals_by_feature[].engaged_user_count` | `integer` | No | Nonnegative number of distinct active users who engaged with the feature on at least two distinct days during the inclusive 28-day report window. |
 
 ### User-teams fields
@@ -611,7 +611,7 @@ A user is classified into a phase based on the {% data variables.product.prodnam
 
 | Phase | Engagement criteria |
 |:--|:--|
-| No Cohort (displayed as "Passive users" in the impact dashboard) | The user isn't engaged with any feature that qualifies for a phase. This doesn't mean the user is inactive. A user in this group can still be using {% data variables.product.prodname_copilot_short %} regularly and consuming premium requests, but hasn't used a qualifying feature on at least two distinct days within the trailing 28-day window. The most common case is conversational use of {% data variables.copilot.copilot_chat_short %} or agent mode, recorded as `chat_panel_agent_mode`, that never produces `code_completion` or `agent_edit` activity. Copying code out of a chat response also doesn't produce either signal. |
+| No Cohort (displayed as "Chat-first users" in the impact dashboard) | The user isn't engaged with any feature that qualifies for a phase. This doesn't mean the user is inactive. A user in this group can still be using {% data variables.product.prodname_copilot_short %} regularly and consuming premium requests, but hasn't used a qualifying feature on at least two distinct days within the trailing 28-day window. The most common case is conversational use of {% data variables.copilot.copilot_chat_short %} or agent mode, recorded as `chat_panel_agent_mode`, that never produces `code_completion` or `agent_edit` activity. Copying code out of a chat response also doesn't produce either signal. |
 | Phase 1: Code first | Engaged with inline code completions (the `code_completion` value of the `feature` dimension) or with agent edits written directly to files (the `agent_edit` value of the `feature` dimension). |
 | Phase 2: Agent first | Engaged with exactly one {% data variables.product.github %}-based agent surface: {% data variables.copilot.copilot_cli_short %} (the `copilot_cli` value of the `feature` dimension), {% data variables.copilot.copilot_cloud_agent %} (`used_copilot_cloud_agent`), or {% data variables.copilot.copilot_code-review_short %} (`used_copilot_code_review_active` or `used_copilot_code_review_passive`). Active and passive {% data variables.copilot.copilot_code-review_short %} count together as a single surface. |
 | Phase 3: Multi-agent | Engaged with the {% data variables.copilot.github_copilot_app_short %} (the `copilot_app` value of the `feature` dimension), or engaged with two or more of the agent surfaces listed for Phase 2. |
diff --git a/content/copilot/reference/copilot-usage-metrics/example-schema.md b/content/copilot/reference/copilot-usage-metrics/example-schema.md
index face41037c2e..1db1e42e1900 100644
--- a/content/copilot/reference/copilot-usage-metrics/example-schema.md
+++ b/content/copilot/reference/copilot-usage-metrics/example-schema.md
@@ -309,7 +309,7 @@ In this example, `used_copilot_code_review_active` and `used_copilot_code_review
     "loc_suggested_to_delete_sum" : 6,
     "missing_client_telemetry_user_count" : 0,
     "monthly_active_agent_users" : 0,
-    "monthly_active_chat_users" : 0,
+    "monthly_active_chat_users" : 2,
     "monthly_active_copilot_cloud_agent_users" : 1,
     "monthly_active_copilot_code_review_users" : 1,
     "monthly_active_local_byok_users" : 2,
@@ -567,19 +567,22 @@ In this example, `used_copilot_code_review_active` and `used_copilot_code_review
   "copilot_feature_engagement" : {
     "active_user_count" : 2,
     "totals_by_feature" : [ {
-      "feature" : "code_completion",
-      "engaged_user_count" : 2
-    }, {
       "feature" : "agent_edit",
       "engaged_user_count" : 1
     }, {
-      "feature" : "code_review_passive",
+      "feature" : "chat",
+      "engaged_user_count" : 2
+    }, {
+      "feature" : "cloud_agent",
       "engaged_user_count" : 1
+    }, {
+      "feature" : "code_completion",
+      "engaged_user_count" : 2
     }, {
       "feature" : "code_review_active",
       "engaged_user_count" : 1
     }, {
-      "feature" : "cloud_agent",
+      "feature" : "code_review_passive",
       "engaged_user_count" : 1
     }, {
       "feature" : "copilot_cli",
@@ -587,6 +590,9 @@ In this example, `used_copilot_code_review_active` and `used_copilot_code_review
     }, {
       "feature" : "github_app",
       "engaged_user_count" : 1
+    }, {
+      "feature" : "vscode_agent",
+      "engaged_user_count" : 1
     } ]
   },
   "report_end_day" : "2025-10-01",
@@ -614,7 +620,7 @@ In this example, `used_copilot_code_review_active` and `used_copilot_code_review
     "loc_suggested_to_delete_sum" : 3,
     "missing_client_telemetry_user_count" : 1,
     "monthly_active_agent_users" : 0,
-    "monthly_active_chat_users" : 0,
+    "monthly_active_chat_users" : 2,
     "monthly_active_copilot_cloud_agent_users" : 0,
     "monthly_active_copilot_code_review_users" : 0,
     "monthly_active_local_byok_users" : 0,
@@ -776,19 +782,22 @@ In this example, `used_copilot_code_review_active` and `used_copilot_code_review
   "copilot_feature_engagement" : {
     "active_user_count" : 2,
     "totals_by_feature" : [ {
-      "feature" : "code_completion",
-      "engaged_user_count" : 2
-    }, {
       "feature" : "agent_edit",
       "engaged_user_count" : 1
     }, {
-      "feature" : "code_review_passive",
+      "feature" : "chat",
+      "engaged_user_count" : 2
+    }, {
+      "feature" : "cloud_agent",
       "engaged_user_count" : 1
+    }, {
+      "feature" : "code_completion",
+      "engaged_user_count" : 2
     }, {
       "feature" : "code_review_active",
       "engaged_user_count" : 1
     }, {
-      "feature" : "cloud_agent",
+      "feature" : "code_review_passive",
       "engaged_user_count" : 1
     }, {
       "feature" : "copilot_cli",
@@ -796,6 +805,9 @@ In this example, `used_copilot_code_review_active` and `used_copilot_code_review
     }, {
       "feature" : "github_app",
       "engaged_user_count" : 1
+    }, {
+      "feature" : "vscode_agent",
+      "engaged_user_count" : 1
     } ]
   },
   "report_end_day" : "2025-10-01",
diff --git a/content/copilot/reference/copilot-usage-metrics/interpret-copilot-metrics.md b/content/copilot/reference/copilot-usage-metrics/interpret-copilot-metrics.md
index c368d45cdda9..32e8b7f4f442 100644
--- a/content/copilot/reference/copilot-usage-metrics/interpret-copilot-metrics.md
+++ b/content/copilot/reference/copilot-usage-metrics/interpret-copilot-metrics.md
@@ -86,7 +86,7 @@ The impact dashboard's adoption cohort distribution shows the share of users in
 | Signal | What it suggests | Suggested action |
 |:--|:--|:--|
 | Shrinking Phase 1 share, growing Phase 2 or Phase 3 share | Users are progressing from code completions toward agent-driven workflows. | Continue current enablement; consider sharing internal success stories to sustain momentum. |
-| Large or growing passive users share | Many licensed users haven't yet reached the engagement threshold for a phase. | Verify license assignment and IDE setup; offer onboarding to re-engage inactive users. Also check whether affected users rely primarily on a surface that isn't part of any phase's classification criteria, such as {% data variables.copilot.copilot_chat_short %} on {% data variables.product.prodname_dotcom_the_website %}. |
+| Large or growing chat-first users share | These users are active but haven't used a qualifying feature on at least two distinct days in the trailing 28-day window. They may primarily use {% data variables.copilot.copilot_chat_short %} without producing `code_completion` or `agent_edit` activity. | Help these users try code completions, agent edits, or agent surfaces such as {% data variables.copilot.copilot_cloud_agent %} or {% data variables.copilot.copilot_cli_short %}. Also verify license assignment and IDE setup for users who rarely use any surface. |
 | Stalled progression from Phase 1 to Phase 2 | Users are comfortable with completions and chat but haven't adopted agent surfaces. | Follow a recommendation card, such as configuring {% data variables.copilot.copilot_cloud_agent %}, or run a demo of agent workflows. |
 | Stalled progression from Phase 2 to Phase 3 | Users have adopted one agent surface but haven't layered in additional agent surfaces. | Follow a recommendation card, such as enabling {% data variables.copilot.copilot_code-review_short %}, to introduce a second agent surface. |
 | A user's phase changes from one day to the next without a change in their habits | Phase assignment is recalculated daily from the trailing 28-day window, so a user's phase shifts as older days roll out of the window. | This is expected behavior, not a data error; no action needed. |
@@ -95,17 +95,17 @@ When you see a recommendation card in the dashboard, such as configuring {% data
 
 ## Reviewing the adoption multiplier
 
-The adoption multiplier compares engaged users (Phase 1, 2, or 3) against passive users on code shipped (pull requests merged per user per month) and time to merge pull requests. This shows the relative impact of deeper adoption, independent of how many users fall into each phase.
+The adoption multiplier compares engaged users (Phase 1, 2, or 3) against chat-first users on code shipped (pull requests merged per user per month) and time to merge pull requests. This shows the relative impact of deeper adoption, independent of how many users fall into each phase.
 
 | Signal | What it suggests | Suggested action |
 |:--|:--|:--|
-| Engaged users merge more pull requests per user per month than passive users | Deeper {% data variables.product.prodname_copilot_short %} adoption is associated with higher individual output. | Use this comparison to support the case for continued enablement investment. |
-| Engaged users merge fewer pull requests per user per month than passive users | Engaged users may be spending more time on larger or more complex work, or the comparison may reflect differences in team composition rather than adoption depth. | Cross-reference with adoption cohort distribution and team-level data before drawing conclusions; avoid treating the multiplier as a standalone measure of productivity. |
-| Engaged users merge pull requests faster than passive users | Deeper adoption is associated with a shorter pull request lifecycle. | Use this comparison alongside pull request lifecycle metrics to evaluate overall delivery impact. |
-| Multiplier stays flat despite growth in Phase 2 or Phase 3 share | Agent adoption hasn't yet translated into a measurable difference in output between engaged and passive users. | Check whether agent usage is concentrated in a few users or teams, and whether enough time has passed since rollout for the impact to show. |
+| Engaged users merge more pull requests per user per month than chat-first users | Deeper {% data variables.product.prodname_copilot_short %} adoption is associated with higher individual output. | Use this comparison to support the case for continued enablement investment. |
+| Engaged users merge fewer pull requests per user per month than chat-first users | Engaged users may be spending more time on larger or more complex work, or the comparison may reflect differences in team composition rather than adoption depth. | Cross-reference with adoption cohort distribution and team-level data before drawing conclusions; avoid treating the multiplier as a standalone measure of productivity. |
+| Engaged users merge pull requests faster than chat-first users | Deeper adoption is associated with a shorter pull request lifecycle. | Use this comparison alongside pull request lifecycle metrics to evaluate overall delivery impact. |
+| Multiplier stays flat despite growth in Phase 2 or Phase 3 share | Agent adoption hasn't yet translated into a measurable difference in output between engaged and chat-first users. | Check whether agent usage is concentrated in a few users or teams, and whether enough time has passed since rollout for the impact to show. |
 
 > [!NOTE]
-> The adoption multiplier compares two different populations of users, not the same users over time. Differences in team composition, project complexity, or seniority between engaged and passive users can influence the comparison as much as {% data variables.product.prodname_copilot_short %} adoption itself.
+> The adoption multiplier compares two different populations of users, not the same users over time. Differences in team composition, project complexity, or seniority between engaged and chat-first users can influence the comparison as much as {% data variables.product.prodname_copilot_short %} adoption itself.
 
 ## Reviewing industry comparisons
 
@@ -114,7 +114,7 @@ The **Industry comparison** widget compares your enterprise's agentic adoption a
 | Signal | What it suggests | Suggested action |
 |:--|:--|:--|
 | Agentic adoption is above the peer median | A larger share of your users have adopted agent-first or multi-agent workflows than in the comparison cohort. | Continue the enablement practices that support agentic workflows, and review which teams still have lower adoption. |
-| Agentic adoption is below the peer median | Your enterprise has room to expand adoption of agent-first and multi-agent workflows. | Review the adoption cohort distribution, then prioritize onboarding or enablement for teams that remain passive or code-first. |
+| Agentic adoption is below the peer median | Your enterprise has room to expand adoption of agent-first and multi-agent workflows. | Review the adoption cohort distribution, then prioritize onboarding or enablement for teams that remain chat-first or code-first. |
 | Leverage is above the peer median | The ratio of merge rates between agentic and non-agentic users is higher in your enterprise than in the peer cohort. | Review the practices of teams with strong agentic adoption and consider whether those practices can be applied more broadly. |
 | Leverage is below the peer median | The ratio of merge rates between agentic and non-agentic users is lower than for the comparison cohort. | Check team composition, project complexity, and how recently agentic workflows were introduced before changing your rollout plan. |
 | Your ranking improves across reporting periods | Your enterprise's position has improved relative to the participating peer cohort. | Confirm that the improvement appears alongside sustained adoption and pull request trends before expanding enablement investment. |
diff --git a/content/copilot/reference/copilot-usage-metrics/reconciling-usage-metrics.md b/content/copilot/reference/copilot-usage-metrics/reconciling-usage-metrics.md
index 35de1f8c8e2c..fa2dac3d1f7e 100644
--- a/content/copilot/reference/copilot-usage-metrics/reconciling-usage-metrics.md
+++ b/content/copilot/reference/copilot-usage-metrics/reconciling-usage-metrics.md
@@ -43,7 +43,7 @@ The dashboard and APIs use shared definitions for key metrics:
 | Acceptance rate | Code completion acceptance rate | `code_acceptance_activity_count` ÷ `code_generation_activity_count` | Both sources calculate acceptance rate the same way, though rounding may differ. |
 | Agent adoption | Agent adoption chart | `totals_by_feature` where feature = “agent” | Reflects users who interacted with the {% data variables.copilot.copilot_agent_short %}. |
 | Language usage | Language usage charts | `totals_by_language_feature` or `totals_by_language_model` | The dashboard visualizes these aggregated fields. |
-| Adoption cohort/phase | Adoption cohort distribution (impact dashboard) | `ai_adoption_phase`, `totals_by_ai_adoption_phase` | The phase definitions are shared, but the populations differ. The dashboard includes every user active during the trailing 28-day window, while the aggregated `totals_by_ai_adoption_phase` field counts users active on the record's specific day. Dashboard and API cohort counts and percentages therefore do not match. Users displayed as "Passive users" in the dashboard correspond to the `No Cohort` API value. |
+| Adoption cohort/phase | Adoption cohort distribution (impact dashboard) | `ai_adoption_phase`, `totals_by_ai_adoption_phase` | The phase definitions are shared, but the populations differ. The dashboard includes every user active during the trailing 28-day window, while the aggregated `totals_by_ai_adoption_phase` field counts users active on the record's specific day. Dashboard and API cohort counts and percentages therefore do not match. Users displayed as "Chat-first users" in the dashboard correspond to the `No Cohort` API value. |
 
 For complete field descriptions, see [AUTOTITLE](/copilot/reference/copilot-usage-metrics).