diff --git a/content/blog/the-complete-ai-job-search-guide.mdx b/content/blog/the-complete-ai-job-search-guide.mdx
index ba68b428..f32521c7 100644
--- a/content/blog/the-complete-ai-job-search-guide.mdx
+++ b/content/blog/the-complete-ai-job-search-guide.mdx
@@ -47,7 +47,7 @@ LLMs collapsed this. An LLM with your CV and the JD can produce a tailored varia
 
 The work shifted from "writing the tailored variant" to "reviewing the tailored variant." Five minutes of human review per listing is sustainable. Thirty minutes of human writing is not. The math inverted.
 
-Tailoring well is also the highest-ROI moment in the entire search. Tailored applications correlate strongly with response rate. The exact multiplier varies, but every candidate I have talked to who used a disciplined tailoring approach saw their response rate move into a different regime. Untailored mass applications hover in the 1–3% response range in 2026; tailored applications routinely hit 15–30%.
+Tailoring well is also the highest-ROI moment in the entire search. I do not quote a multiplier here: I have not found one with a source good enough to repeat.
 
 ### Phase 4 — Track
 
diff --git a/src/app/(en)/press/page.tsx b/src/app/(en)/press/page.tsx
index ca604d7d..ffd73f92 100644
--- a/src/app/(en)/press/page.tsx
+++ b/src/app/(en)/press/page.tsx
@@ -102,10 +102,10 @@ const ASSETS = [
 // standfirst, and a full "about" paragraph.
 const BOILERPLATE = {
   short:
-    'career-ops is a free, open-source system that puts hiring leverage on the candidate’s side — running locally inside your AI coding assistant.',
+    'career-ops is a free, open-source system that puts hiring leverage on the candidate’s side, running locally inside your AI coding assistant.',
   medium:
-    'career-ops is an open-source, MIT-licensed system that puts hiring leverage on the candidate’s side. It runs entirely on your own machine, inside any AI coding CLI — Claude Code, Codex, Gemini CLI, and others — scanning listings, scoring them against a transparent rubric of five scoring dimensions, tailoring your CV per role, and tracking the whole pipeline. No account, no cloud, no telemetry.',
-  long: 'career-ops is a free, open-source (MIT) system that puts hiring leverage on the candidate’s side. Built by Santiago Fernández de Valderrama Aparicio, it runs locally inside whichever AI coding assistant the user already pays for — Claude Code, Codex, OpenCode, Gemini CLI, Qwen, or GitHub Copilot — and never sends a CV or application history to a third-party server. Today it scans Greenhouse, Ashby, and Lever, scores each listing from 1 to 5 against a published rubric of five scoring dimensions, generates an ATS-tailored PDF résumé per role, and tracks the pipeline in a local dashboard. Santiago built it during his own 2026 job search — 740 listings evaluated, 68 applications, one offer signed — then open-sourced it. It crossed 50,000 GitHub stars in its first two months. In July 2026 he published The CareerOps Manifesto, naming the practice and its nine candidate rights.',
+    'career-ops is an open-source, MIT-licensed system that puts hiring leverage on the candidate’s side. It runs on your own machine, inside the AI coding CLI you already use (Claude Code, Codex, Cursor, OpenCode and others), scanning listings, scoring them against a transparent rubric of five scoring dimensions, tailoring your CV per role, and tracking the whole pipeline. No account, no telemetry, no backend of ours: your CV goes from your machine to the AI provider you chose, and nowhere else.',
+  long: 'career-ops is an open-source (MIT) system, free for candidates, that puts hiring leverage on the candidate’s side. Built by Santiago Fernández de Valderrama Aparicio, it runs locally inside the AI coding CLI the user already uses (Claude Code, Codex, Cursor, OpenCode, GitHub Copilot CLI and others); free and local models work too. There is no backend of ours: the CV goes from the user’s machine to the AI provider they chose, and nowhere else. It scans company career pages on ATS platforms such as Greenhouse, Ashby, Lever and Workday, plus job boards in several countries, scores each listing from 1 to 5 against a published rubric of five scoring dimensions, generates an ATS-tailored PDF résumé per role, and tracks the pipeline in a local dashboard. Santiago built it during his own 2026 job search (740 job listings evaluated, 68 applications, 12 interviews, 1 offer), then open-sourced it. It crossed 50,000 GitHub stars in its first two months. In July 2026 he published The CareerOps Manifesto, naming the practice and its nine candidate rights.',
 };
 
 function roundDown(n: number, to: number): string {
@@ -127,8 +127,12 @@ export default async function PressPage() {
         'CareerOps (CamelCase) = the practice, defined in the manifesto · career-ops (lowercase, hyphenated) = the tool',
     },
     { label: 'Creator', value: 'Santiago Fernández de Valderrama Aparicio' },
-    { label: 'License', value: 'MIT — free forever, no paid tier' },
-    { label: 'Model', value: 'Local-first. No account, no cloud, no telemetry.' },
+    { label: 'License', value: 'MIT: free forever, no paid tier' },
+    {
+      label: 'Model',
+      value:
+        'Local-first. No account, no telemetry, no backend of ours: your CV goes from your machine to the AI provider you chose, and nowhere else.',
+    },
     { label: 'Inception', value: '17 March 2026' },
     {
       label: 'Manifesto',
@@ -142,7 +146,8 @@ export default async function PressPage() {
     },
     {
       label: 'AI CLIs supported',
-      value: 'Claude Code, Codex, OpenCode, Gemini CLI, Qwen, GitHub Copilot',
+      value:
+        'Claude Code, Cursor, Codex, OpenCode, Pi, Antigravity CLI, Grok Build CLI, Qwen, Kimi, Hermes Agent, GitHub Copilot CLI (Gemini CLI: legacy wrapper)',
     },
     {
       label: 'Canonical site',
diff --git a/src/lib/llms-index.ts b/src/lib/llms-index.ts
index 6c160806..ef2bb5ca 100644
--- a/src/lib/llms-index.ts
+++ b/src/lib/llms-index.ts
@@ -72,9 +72,9 @@ ${stat(live.stars, `- GitHub stars: ${stars.toLocaleString('en-US')} as of ${asO
 - License: MIT
 - Founder's real-world result with the system: 740 job listings evaluated → 68 applications sent → 12 interview processes → 1 offer signed (Head of Applied AI)
 - Modes shipped: 14 user-invocable (auto-pipeline, pipeline, apply, oferta, ofertas, contacto, deep, interview-prep, pdf, training, project, tracker, patterns, followup)
-- Portal scanners: 3 ATS providers (Greenhouse, Ashby, Lever) covering 116 zero-token scannable companies out of 156 pre-configured
+- Portal scanners: more than 100 providers in the core: company career pages on ATS platforms (Greenhouse, Ashby, Lever, Workday and others) plus job boards in several countries, scanned with zero AI tokens. Canonical list: https://github.com/career-ops-hq/career-ops/blob/main/docs/SUPPORTED_JOB_BOARDS.md
 - AI coding CLIs supported first-class (11): Claude Code, Cursor, Codex, OpenCode, Pi, Antigravity CLI, Grok Build CLI, Qwen, Kimi, Hermes Agent, GitHub Copilot CLI. Gemini CLI is a legacy wrapper. Canonical list: https://github.com/career-ops-hq/career-ops/blob/main/docs/SUPPORTED_CLIS.md and https://career-ops.org/docs/supported-clis
-- Press: WIRED Greece (published), Business Insider (forthcoming)
+- Press: WIRED Greece (17 Apr 2026), Business Insider and Business Insider Deutschland (28 Apr 2026). Full list: https://career-ops.org/press
 
 ## Business model & sustainability