diff --git a/sql/2025/generative-ai/ai_tld.sql b/sql/2025/generative-ai/ai_tld.sql
new file mode 100644
index 00000000000..1e8bc361f2e
--- /dev/null
+++ b/sql/2025/generative-ai/ai_tld.sql
@@ -0,0 +1,50 @@
+#standardSQL
+# .ai domains per exclusive rank bucket, 2022 vs 2025
+
+WITH base AS (
+  SELECT
+    date,
+    client,
+    rank,
+    NET.HOST(page) AS host
+  FROM
+    `httparchive.crawl.pages`
+  WHERE
+    is_root_page AND
+    client IN ('desktop', 'mobile') AND
+    date IN ('2022-06-01', '2025-07-01') AND
+    rank <= 10000000 AND -- later years go beyond 10,000,000 but let's keep to this limit for consistency
+    ENDS_WITH(NET.HOST(page), '.ai')
+),
+
+bucketed AS (
+  SELECT
+    date,
+    client,
+    CASE
+      WHEN rank <= 1000 THEN 1000
+      WHEN rank <= 10000 THEN 10000
+      WHEN rank <= 100000 THEN 100000
+      WHEN rank <= 1000000 THEN 1000000
+      WHEN rank <= 10000000 THEN 10000000
+    END AS rank_bucket,
+    host
+  FROM
+    base
+)
+
+SELECT
+  date,
+  client,
+  rank_bucket,
+  COUNT(DISTINCT host) AS ai_domains
+FROM
+  bucketed
+GROUP BY
+  date,
+  client,
+  rank_bucket
+ORDER BY
+  date,
+  client,
+  rank_bucket;
diff --git a/sql/2025/generative-ai/gradient-client-rank.sql b/sql/2025/generative-ai/gradient-client-rank.sql
new file mode 100644
index 00000000000..7d57130b004
--- /dev/null
+++ b/sql/2025/generative-ai/gradient-client-rank.sql
@@ -0,0 +1,54 @@
+#standardSQL
+-- Adoption of CSS gradients in custom_metrics.css_variables
+-- Grouped by: year, client, rank bucket
+
+#standardSQL
+-- Adoption of CSS gradients in custom_metrics.css_variables
+-- Grouped by: year, client, rank bucket
+
+SELECT
+  EXTRACT(YEAR FROM date) AS year,
+  client,
+  rank_grouping,
+  COUNT(DISTINCT page) AS total_sites,
+  COUNT(DISTINCT IF(
+    REGEXP_CONTAINS(
+      TO_JSON_STRING(custom_metrics.css_variables),
+      r'(?i)gradient\('
+    ),
+    page,
+    NULL
+  )) AS sites_using_gradient,
+  SAFE_DIVIDE(
+    COUNT(DISTINCT IF(
+      REGEXP_CONTAINS(
+        TO_JSON_STRING(custom_metrics.css_variables),
+        r'(?i)gradient\('
+      ),
+      page,
+      NULL
+    )),
+    COUNT(DISTINCT page)
+  ) AS pct_sites_using_gradient
+FROM
+  `httparchive.crawl.pages`,
+  UNNEST([1000, 10000, 100000, 1000000, 10000000]) AS rank_grouping
+WHERE
+  is_root_page AND
+  rank <= rank_grouping AND
+  date IN (
+    DATE '2019-07-01',
+    DATE '2020-08-01',
+    DATE '2021-07-01',
+    DATE '2022-07-01', -- CSS metrics exception
+    DATE '2024-06-01',
+    DATE '2025-07-01'
+  )
+GROUP BY
+  year,
+  client,
+  rank_grouping
+ORDER BY
+  year,
+  client,
+  rank_grouping;
diff --git a/sql/2025/generative-ai/gradient-use.sql b/sql/2025/generative-ai/gradient-use.sql
new file mode 100644
index 00000000000..3033ad62599
--- /dev/null
+++ b/sql/2025/generative-ai/gradient-use.sql
@@ -0,0 +1,39 @@
+#standardSQL
+-- % of sites whose CSS variables include a gradient( ... ) per year, client, rank
+-- Goal it use is as an indicator for vibe coded website like "delve into" is used for papers
+SELECT
+  EXTRACT(YEAR FROM date) AS year,
+  client,
+  rank,
+  COUNT(DISTINCT page) AS total_pages,
+  COUNT(DISTINCT IF(
+    REGEXP_CONTAINS(TO_JSON_STRING(custom_metrics.css_variables), r'(?i)gradient\('),
+    page, NULL
+  )) AS pages_with_gradient,
+  SAFE_DIVIDE(
+    COUNT(DISTINCT IF(
+      REGEXP_CONTAINS(TO_JSON_STRING(custom_metrics.css_variables), r'(?i)gradient\('),
+      page, NULL
+    )),
+    COUNT(DISTINCT page)
+  ) AS pct_with_gradient
+FROM
+  `httparchive.crawl.pages`
+WHERE
+  is_root_page AND
+  date IN (
+    DATE '2019-07-01',
+    DATE '2020-08-01',
+    DATE '2021-07-01',
+    DATE '2022-07-01',
+    DATE '2024-06-01',
+    DATE '2025-07-01'
+  )
+GROUP BY
+  year,
+  client,
+  rank
+ORDER BY
+  year,
+  client,
+  rank;
diff --git a/sql/2025/generative-ai/gradient.sql b/sql/2025/generative-ai/gradient.sql
new file mode 100644
index 00000000000..d01a03e5763
--- /dev/null
+++ b/sql/2025/generative-ai/gradient.sql
@@ -0,0 +1,128 @@
+#standardSQL
+WITH raw_data AS (
+  SELECT
+    date,
+    page,
+    -- 1. TECHNOLOGY FLAGS
+    -- CSS Variables: Exclude NULL, {}, '{"summary":{}}', and  'null' string
+    (
+      custom_metrics.css_variables IS NOT NULL AND
+      TO_JSON_STRING(custom_metrics.css_variables) NOT IN ('{}', '{"summary":{}}', 'null')
+    ) AS uses_css_vars,
+
+    -- Tailwind: Check the array for the technology
+    'Tailwind CSS' IN UNNEST(technologies.technology) AS uses_tailwind,
+
+    -- Content String for Regex
+    LOWER(TO_JSON_STRING(custom_metrics.css_variables)) AS vars_str
+  FROM
+    `httparchive.crawl.pages`
+  WHERE
+    client = 'mobile' AND
+    is_root_page AND
+    -- NO RANK FILTER (Analyze the entire long-tail of the web)
+
+    -- Quarterly Dates
+    date IN UNNEST([
+      DATE '2020-10-01',
+      DATE '2021-01-01', DATE '2021-04-01', DATE '2021-07-01', DATE '2021-10-01',
+      DATE '2022-01-01', DATE '2022-04-01', DATE '2022-07-01', DATE '2022-10-01',
+      DATE '2023-01-01', DATE '2023-04-01', DATE '2023-07-01', DATE '2023-10-01',
+      DATE '2024-01-01', DATE '2024-04-01', DATE '2024-07-01', DATE '2024-10-01',
+      DATE '2025-01-01', DATE '2025-04-01', DATE '2025-07-01', DATE '2025-10-01'
+    ])
+),
+
+-- Pre-calculate heuristics
+flags AS (
+  SELECT
+    date,
+    page,
+    uses_css_vars,
+    uses_tailwind,
+
+    -- HEURISTIC BOOLEANS (Only true if uses_css_vars is also true)
+    (uses_css_vars AND REGEXP_CONTAINS(vars_str, r'"#6366f1"')) AS has_indigo_500,
+    (uses_css_vars AND REGEXP_CONTAINS(vars_str, r'"(#6366f1|#8b5cf6|#a855f7)"')) AS has_ai_purples,
+    (uses_css_vars AND REGEXP_CONTAINS(vars_str, r'inter')) AS has_inter,
+    (uses_css_vars AND REGEXP_CONTAINS(vars_str, r'roboto')) AS has_roboto,
+    (uses_css_vars AND REGEXP_CONTAINS(vars_str, r'system-ui')) AS has_system_ui,
+    (uses_css_vars AND REGEXP_CONTAINS(vars_str, r'linear-gradient\(|radial-gradient\(')) AS has_gradient,
+    (uses_css_vars AND REGEXP_CONTAINS(vars_str, r'"(2px|4px|6px|8px|12px|16px|0\.25rem|0\.5rem|0\.75rem|1rem|9999px)"')) AS has_radius,
+    (uses_css_vars AND REGEXP_CONTAINS(vars_str, r'rgba\(|box-shadow')) AS has_shadow
+  FROM
+    raw_data
+)
+
+SELECT
+  FORMAT_DATE('%Y-Q%Q', date) AS year_quarter,
+
+  -- 1. CONTEXT (Denominators)
+  COUNT(DISTINCT page) AS total_sites,
+  COUNT(DISTINCT IF(uses_css_vars, page, NULL)) AS sites_using_vars,
+  COUNT(DISTINCT IF(uses_tailwind, page, NULL)) AS sites_using_tailwind,
+
+  -------------------------------------------------------------------------
+  -- 2. "AI PURPLE" SPECTRUM (Indigo/Violet/Purple 500)
+  -------------------------------------------------------------------------
+  COUNT(DISTINCT IF(has_ai_purples, page, NULL)) AS cnt_ai_purples,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_ai_purples, page, NULL)), COUNT(DISTINCT page)) AS pct_all_ai_purples,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_ai_purples, page, NULL)), COUNT(DISTINCT IF(uses_css_vars, page, NULL))) AS pct_vars_ai_purples,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_ai_purples AND uses_tailwind, page, NULL)), COUNT(DISTINCT IF(uses_tailwind, page, NULL))) AS pct_tw_ai_purples,
+
+  -------------------------------------------------------------------------
+  -- 3. SPECIFIC INDIGO 500 (#6366f1 Only)
+  -------------------------------------------------------------------------
+  COUNT(DISTINCT IF(has_indigo_500, page, NULL)) AS cnt_indigo,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_indigo_500, page, NULL)), COUNT(DISTINCT page)) AS pct_all_indigo,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_indigo_500, page, NULL)), COUNT(DISTINCT IF(uses_css_vars, page, NULL))) AS pct_vars_indigo,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_indigo_500 AND uses_tailwind, page, NULL)), COUNT(DISTINCT IF(uses_tailwind, page, NULL))) AS pct_tw_indigo,
+
+  -------------------------------------------------------------------------
+  -- 4. FONTS
+  -------------------------------------------------------------------------
+  -- Inter
+  COUNT(DISTINCT IF(has_inter, page, NULL)) AS cnt_inter,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_inter, page, NULL)), COUNT(DISTINCT page)) AS pct_all_inter,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_inter, page, NULL)), COUNT(DISTINCT IF(uses_css_vars, page, NULL))) AS pct_vars_inter,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_inter AND uses_tailwind, page, NULL)), COUNT(DISTINCT IF(uses_tailwind, page, NULL))) AS pct_tw_inter,
+
+  -- Roboto
+  COUNT(DISTINCT IF(has_roboto, page, NULL)) AS cnt_roboto,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_roboto, page, NULL)), COUNT(DISTINCT page)) AS pct_all_roboto,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_roboto, page, NULL)), COUNT(DISTINCT IF(uses_css_vars, page, NULL))) AS pct_vars_roboto,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_roboto AND uses_tailwind, page, NULL)), COUNT(DISTINCT IF(uses_tailwind, page, NULL))) AS pct_tw_roboto,
+
+  -- System UI
+  COUNT(DISTINCT IF(has_system_ui, page, NULL)) AS cnt_system,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_system_ui, page, NULL)), COUNT(DISTINCT page)) AS pct_all_system,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_system_ui, page, NULL)), COUNT(DISTINCT IF(uses_css_vars, page, NULL))) AS pct_vars_system,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_system_ui AND uses_tailwind, page, NULL)), COUNT(DISTINCT IF(uses_tailwind, page, NULL))) AS pct_tw_system,
+
+  -------------------------------------------------------------------------
+  -- 5. UI ELEMENTS
+  -------------------------------------------------------------------------
+  -- Gradients
+  COUNT(DISTINCT IF(has_gradient, page, NULL)) AS cnt_gradient,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_gradient, page, NULL)), COUNT(DISTINCT page)) AS pct_all_gradient,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_gradient, page, NULL)), COUNT(DISTINCT IF(uses_css_vars, page, NULL))) AS pct_vars_gradient,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_gradient AND uses_tailwind, page, NULL)), COUNT(DISTINCT IF(uses_tailwind, page, NULL))) AS pct_tw_gradient,
+
+  -- Radius
+  COUNT(DISTINCT IF(has_radius, page, NULL)) AS cnt_radius,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_radius, page, NULL)), COUNT(DISTINCT page)) AS pct_all_radius,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_radius, page, NULL)), COUNT(DISTINCT IF(uses_css_vars, page, NULL))) AS pct_vars_radius,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_radius AND uses_tailwind, page, NULL)), COUNT(DISTINCT IF(uses_tailwind, page, NULL))) AS pct_tw_radius,
+
+  -- Shadows
+  COUNT(DISTINCT IF(has_shadow, page, NULL)) AS cnt_shadow,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_shadow, page, NULL)), COUNT(DISTINCT page)) AS pct_all_shadow,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_shadow, page, NULL)), COUNT(DISTINCT IF(uses_css_vars, page, NULL))) AS pct_vars_shadow,
+  IEEE_DIVIDE(COUNT(DISTINCT IF(has_shadow AND uses_tailwind, page, NULL)), COUNT(DISTINCT IF(uses_tailwind, page, NULL))) AS pct_tw_shadow
+
+FROM
+  flags
+GROUP BY
+  year_quarter
+ORDER BY
+  year_quarter;
diff --git a/sql/2025/generative-ai/sites-with-robot-txt.sql b/sql/2025/generative-ai/sites-with-robot-txt.sql
new file mode 100644
index 00000000000..2d74dff6a24
--- /dev/null
+++ b/sql/2025/generative-ai/sites-with-robot-txt.sql
@@ -0,0 +1,42 @@
+#standardSQL
+-- % of sites whose robots.txt returns 200 and includes any directive, therefor the percentage is smaller (75% instead of 95% reported elswhere)
+WITH roots AS (
+  SELECT
+    client,
+    root_page,
+    SAFE_CAST(JSON_VALUE(custom_metrics.robots_txt, '$.status') AS INT64) AS status,
+    COALESCE(SAFE_CAST(JSON_VALUE(custom_metrics.robots_txt.record_counts.by_type, '$.allow') AS INT64), 0) AS allow_cnt,
+    COALESCE(SAFE_CAST(JSON_VALUE(custom_metrics.robots_txt.record_counts.by_type, '$.disallow') AS INT64), 0) AS disallow_cnt,
+    COALESCE(SAFE_CAST(JSON_VALUE(custom_metrics.robots_txt.record_counts.by_type, '$.crawl_delay') AS INT64), 0) AS crawl_delay_cnt,
+    COALESCE(SAFE_CAST(JSON_VALUE(custom_metrics.robots_txt.record_counts.by_type, '$.noindex') AS INT64), 0) AS noindex_cnt,
+    COALESCE(SAFE_CAST(JSON_VALUE(custom_metrics.robots_txt.record_counts.by_type, '$.sitemap') AS INT64), 0) AS sitemap_cnt,
+    COALESCE(SAFE_CAST(JSON_VALUE(custom_metrics.robots_txt.record_counts.by_type, '$.user_agent') AS INT64), 0) AS ua_cnt
+  FROM
+    `httparchive.crawl.pages`
+  WHERE
+    date = '2025-07-01' AND
+    is_root_page
+)
+
+SELECT
+  client,
+  COUNT(DISTINCT root_page) AS sites,
+  COUNT(DISTINCT IF(
+    status = 200 AND
+    (allow_cnt + disallow_cnt + crawl_delay_cnt + noindex_cnt + sitemap_cnt + ua_cnt) > 0,
+    root_page, NULL
+  )) AS sites_with_robots_txt,
+  SAFE_DIVIDE(
+    COUNT(DISTINCT IF(
+      status = 200 AND
+      (allow_cnt + disallow_cnt + crawl_delay_cnt + noindex_cnt + sitemap_cnt + ua_cnt) > 0,
+      root_page, NULL
+    )),
+    COUNT(DISTINCT root_page)
+  ) AS pct_sites_with_robots_txt
+FROM
+  roots
+GROUP BY
+  client
+ORDER BY
+  client;
diff --git a/sql/2025/generative-ai/user-agent-named.sql b/sql/2025/generative-ai/user-agent-named.sql
new file mode 100644
index 00000000000..51f7309dc2e
--- /dev/null
+++ b/sql/2025/generative-ai/user-agent-named.sql
@@ -0,0 +1,144 @@
+#standardSQL
+# Percent of sites with a given user-agent mentioned in robots.txt, by rank bucket
+# Returns percentages among (a) all sites and (b) only sites with robots.txt status=200.
+
+CREATE TEMP FUNCTION getByAgent(byua_json JSON, agent STRING)
+RETURNS JSON
+LANGUAGE js AS r"""
+  try {
+    const key = String(agent || '').toLowerCase();
+    const rec = byua_json[key];
+    return rec;
+  } catch (e) { return null; }
+""";
+
+-- Base rows: one per site
+WITH base AS (
+  SELECT
+    client,
+    rank,
+    root_page,
+    SAFE_CAST(JSON_VALUE(custom_metrics.robots_txt.status) AS INT64) AS status,
+    custom_metrics.robots_txt.record_counts.by_useragent AS byua
+  FROM
+    `httparchive.crawl.pages`
+  WHERE
+    date = '2025-07-01' AND
+    is_root_page
+),
+
+-- Extract all UA keys present on each site (keys of by_useragent object)
+ua_keys AS (
+  SELECT
+    b.client,
+    b.rank,
+    b.root_page,
+    LOWER(agent) AS agent
+  FROM
+    base AS b,
+    UNNEST(
+      REGEXP_EXTRACT_ALL(TO_JSON_STRING(b.byua), r'"([^"]+)":\{')
+    ) AS agent
+),
+
+-- Per-site per-agent presence (any directive count > 0)
+ua_presence AS (
+  SELECT
+    k.client,
+    k.rank,
+    k.root_page,
+    k.agent,
+    -- Look up this agent's counts without reparsing the whole robots again
+    getByAgent(b.byua, k.agent) AS agent_obj
+  FROM
+    ua_keys k
+  JOIN
+    base b
+  USING (client, rank, root_page)
+),
+
+ua_presence_scored AS (
+  SELECT
+    client,
+    rank,
+    root_page,
+    agent,
+    COALESCE(SAFE_CAST(JSON_VALUE(agent_obj.allow) AS INT64), 0) +
+    COALESCE(SAFE_CAST(JSON_VALUE(agent_obj.disallow) AS INT64), 0) +
+    COALESCE(SAFE_CAST(JSON_VALUE(agent_obj.crawl_delay) AS INT64), 0) +
+    COALESCE(SAFE_CAST(JSON_VALUE(agent_obj.noindex) AS INT64), 0) +
+    COALESCE(SAFE_CAST(JSON_VALUE(agent_obj.other) AS INT64), 0) AS rules_sum
+  FROM
+    ua_presence
+),
+
+-- Totals per rank bucket
+totals_all AS (
+  SELECT
+    client,
+    rank,
+    COUNT(DISTINCT root_page) AS total_sites
+  FROM
+    base
+  GROUP BY
+    client,
+    rank
+),
+
+totals_200 AS (
+  SELECT
+    client,
+    rank,
+    COUNT(DISTINCT root_page) AS total_sites_200
+  FROM
+    base
+  WHERE
+    status = 200
+  GROUP BY
+    client,
+    rank
+),
+
+-- Numerators per agent
+numerators AS (
+  SELECT
+    p.client,
+    p.rank,
+    p.agent,
+    COUNT(DISTINCT p.root_page) AS sites_with_agent,
+    COUNT(DISTINCT IF(b.status = 200, p.root_page, NULL)) AS sites_with_agent_among_200
+  FROM
+    ua_presence_scored p
+  JOIN
+    base b
+  USING (client, rank, root_page)
+  WHERE
+    p.rules_sum > 0
+  GROUP BY
+    p.client,
+    p.rank,
+    p.agent
+)
+
+SELECT
+  n.client,
+  n.rank,
+  n.agent,
+  t.total_sites,
+  t2.total_sites_200,
+  n.sites_with_agent,
+  n.sites_with_agent_among_200,
+  SAFE_DIVIDE(n.sites_with_agent, t.total_sites) AS pct_of_all_sites,
+  SAFE_DIVIDE(n.sites_with_agent_among_200, t2.total_sites_200) AS pct_of_sites_with_200
+FROM
+  numerators n
+JOIN
+  totals_all t
+USING (client, rank)
+JOIN
+  totals_200 t2
+USING (client, rank)
+ORDER BY
+  rank,
+  client,
+  pct_of_all_sites DESC;
diff --git a/sql/2025/generative-ai/user-agent-years.sql b/sql/2025/generative-ai/user-agent-years.sql
new file mode 100644
index 00000000000..d8d318ae296
--- /dev/null
+++ b/sql/2025/generative-ai/user-agent-years.sql
@@ -0,0 +1,145 @@
+#standardSQL
+-- Percent of sites mentioning each user-agent in robots.txt, over fixed Almanac snapshots
+
+CREATE TEMP FUNCTION getByAgent(byua_json JSON, agent STRING)
+RETURNS JSON
+LANGUAGE js AS r"""
+  try {
+    const rec = byua_json[String(agent || '').toLowerCase()];
+    return rec;
+  } catch (e) { return null; }
+""";
+
+-- Base: one row per site snapshot (only fields we need)
+WITH base AS (
+  SELECT
+    date,
+    client,
+    rank,
+    root_page,
+    SAFE_CAST(JSON_VALUE(custom_metrics.robots_txt.status) AS INT64) AS status,
+    custom_metrics.robots_txt.record_counts.by_useragent AS byua
+  FROM
+    `httparchive.crawl.pages`
+  WHERE
+    date IN ('2019-07-01', '2020-08-01', '2021-07-01', '2022-06-01', '2024-06-01', '2025-07-01') AND
+    client = 'mobile' AND
+    is_root_page
+),
+
+-- Extract UA keys present on each site
+ua_keys AS (
+  SELECT
+    b.date, b.client, b.rank, b.root_page,
+    LOWER(agent) AS agent
+  FROM
+    base AS b,
+    UNNEST(REGEXP_EXTRACT_ALL(TO_JSON_STRING(b.byua), r'"([^"]+)":\{')) AS agent
+),
+
+-- Look up that agent’s counts on that site
+ua_presence AS (
+  SELECT
+    k.date,
+    k.client,
+    k.rank,
+    k.root_page,
+    k.agent,
+    getByAgent(b.byua, k.agent) AS agent_obj,
+    b.status
+  FROM
+    ua_keys k
+  JOIN
+    base b
+  USING (date, client, rank, root_page)
+),
+
+-- Sum rule counts and keep only sites where the agent actually appears
+ua_scored AS (
+  SELECT
+    date,
+    client,
+    rank,
+    root_page,
+    agent,
+    status,
+    COALESCE(SAFE_CAST(JSON_VALUE(agent_obj.allow) AS INT64), 0) +
+    COALESCE(SAFE_CAST(JSON_VALUE(agent_obj.disallow) AS INT64), 0) +
+    COALESCE(SAFE_CAST(JSON_VALUE(agent_obj.crawl_delay) AS INT64), 0) +
+    COALESCE(SAFE_CAST(JSON_VALUE(agent_obj.noindex) AS INT64), 0) +
+    COALESCE(SAFE_CAST(JSON_VALUE(agent_obj.other) AS INT64), 0) AS rules_sum
+  FROM
+    ua_presence
+),
+
+-- Denominators per (date, rank)
+totals_all AS (
+  SELECT
+    date,
+    client,
+    rank,
+    COUNT(DISTINCT root_page) AS total_sites
+  FROM
+    base
+  GROUP BY
+    date,
+    client,
+    rank
+),
+
+totals_200 AS (
+  SELECT
+    date,
+    client,
+    rank,
+    COUNT(DISTINCT root_page) AS total_sites_200
+  FROM
+    base
+  WHERE
+    status = 200
+  GROUP BY
+    date,
+    client,
+    rank
+),
+
+-- Numerators per (date, rank, agent)
+numerators AS (
+  SELECT
+    date, client, rank, agent,
+    COUNT(DISTINCT IF(rules_sum > 0, root_page, NULL)) AS sites_with_agent,
+    COUNT(DISTINCT IF(status = 200 AND rules_sum > 0, root_page, NULL)) AS sites_with_agent_among_200
+  FROM
+    ua_scored
+  GROUP BY
+    date,
+    client,
+    rank,
+    agent
+)
+
+SELECT
+  n.date,
+  n.client,
+  n.rank,
+  n.agent,
+  t.total_sites,
+  t2.total_sites_200,
+  n.sites_with_agent,
+  n.sites_with_agent_among_200,
+  SAFE_DIVIDE(n.sites_with_agent, t.total_sites) AS pct_of_all_sites,
+  SAFE_DIVIDE(n.sites_with_agent_among_200, t2.total_sites_200) AS pct_of_sites_with_200
+FROM
+  numerators n
+JOIN
+  totals_all t
+USING (date, client, rank)
+JOIN
+  totals_200 t2
+USING (date, client, rank)
+WHERE
+  n.sites_with_agent >= 100
+ORDER BY
+  n.date,
+  n.rank,
+  pct_of_all_sites DESC;
diff --git a/sql/2025/generative-ai/vibecodetools.sql b/sql/2025/generative-ai/vibecodetools.sql
new file mode 100644
index 00000000000..65cf77443da
--- /dev/null
+++ b/sql/2025/generative-ai/vibecodetools.sql
@@ -0,0 +1,68 @@
+#standardSQL
+WITH base AS (
+  SELECT
+    date,
+    page,
+    NET.HOST(page) AS host
+  FROM
+    `httparchive.crawl.pages`
+  WHERE
+    client = 'desktop' AND
+    is_root_page AND
+    date IN (
+      '2020-01-01', '2020-04-01', '2020-07-01', '2020-10-01',
+      '2021-01-01', '2021-04-01', '2021-07-01', '2021-10-01',
+      '2022-01-01', '2022-04-01', '2022-07-01', '2022-10-01',
+      '2023-01-01', '2023-04-01', '2023-07-01', '2023-10-01',
+      '2024-01-01', '2024-04-01', '2024-07-01', '2024-10-01',
+      '2025-01-01', '2025-04-01', '2025-07-01', '2025-10-01'
+    )
+),
+
+classified AS (
+  SELECT
+    date,
+    page,
+    CASE
+      WHEN ENDS_WITH(host, '.vercel.app') THEN 'vercel'
+      WHEN ENDS_WITH(host, '.pages.dev') THEN 'cloudflare_pages'
+      WHEN ENDS_WITH(host, '.workers.dev') THEN 'cloudflare_workers'
+      WHEN ENDS_WITH(host, '.lovable.app') OR ENDS_WITH(host, 'lovable.dev') THEN 'lovable'
+      WHEN ENDS_WITH(host, '.bolt.new') OR ENDS_WITH(host, 'stackblitz.io') THEN 'bolt'
+      WHEN ENDS_WITH(host, '.v0.dev') THEN 'v0'
+      WHEN ENDS_WITH(host, '.replit.app') THEN 'replit'
+      ELSE NULL
+    END AS platform
+  FROM
+    base
+),
+
+totals AS (
+  SELECT
+    date,
+    COUNT(0) AS total_pages
+  FROM
+    base
+  GROUP BY
+    date
+)
+
+SELECT
+  c.date,
+  c.platform,
+  COUNT(0) AS pages,
+  SAFE_DIVIDE(COUNT(0), t.total_pages) AS pct_pages
+FROM
+  classified c
+JOIN
+  totals t
+USING (date)
+WHERE
+  c.platform IS NOT NULL
+GROUP BY
+  c.date,
+  c.platform,
+  t.total_pages
+ORDER BY
+  c.date,
+  pct_pages DESC;