<p>Hydration is one of the most important concepts in modern frontend frameworks, yet also one of the most misunderstood.</p>

<p>In 2025, frameworks like <strong>React 18+, Vue/Nuxt 3, SvelteKit, SolidStart, Qwik, Astro</strong> all approach hydration differently — some progressively, some selectively, some partially, some never fully.</p>

<p>This post breaks it all down with <strong>real examples</strong>, <strong>SSR + SSG scenarios</strong>, and an extended example so the concept stays in your mind forever.</p>




<h2>
  
  
  🌊 What Is Hydration?
</h2>

<p>When a page is <strong>SSR or SSG</strong>, the browser gets plain HTML:<br>
</p>

<div class="highlight js-code-highlight">
<pre class="highlight html"><code><span class="nt">&lt;div</span> <span class="na">id=</span><span class="s">"app"</span><span class="nt">&gt;</span>
  <span class="nt">&lt;button&gt;</span>Click me<span class="nt">&lt;/button&gt;</span>
  <span class="nt">&lt;ul&gt;</span>
    <span class="nt">&lt;li&gt;</span>Item 1<span class="nt">&lt;/li&gt;</span>
    <span class="nt">&lt;li&gt;</span>Item 2<span class="nt">&lt;/li&gt;</span>
  <span class="nt">&lt;/ul&gt;</span>
<span class="nt">&lt;/div&gt;</span>
</code></pre>

</div>



<p>But HTML alone does nothing — no JavaScript, no event listeners.</p>

<p><strong>Hydration</strong> is when the framework:</p>

<ul>
<li>Loads JS bundles</li>
<li>Recreates the virtual component tree</li>
<li>Attaches event listeners</li>
<li>Activates reactivity</li>
<li>Makes the page interactive</li>
</ul>

<p>Another way to say it:</p>

<blockquote>
<p>SSR/SSG gives HTML.<br>
Hydration gives life.</p>
</blockquote>




<h2>
  
  
  🟥 Old Hydration Model (Pre-React 18 / Classic Vue / SvelteKit)
</h2>

<p>Traditionally, hydration happened <strong>linearly</strong>, top-to-bottom:<br>
</p>

<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code>1. Hydrate App()
2. Hydrate Header()
3. Hydrate Navbar()
4. Hydrate Sections()
5. Hydrate Footer()
</code></pre>

</div>



<p>Linear hydration has <strong>three big problems</strong>:</p>

<h3>
  
  
  ❌ 1. Slow Time-To-Interactive
</h3>

<p>Because hydration must finish <strong>before the user can interact</strong> safely.</p>

<h3>
  
  
  ❌ 2. Big JS bundle runs all at once
</h3>

<p>Blocks main thread.</p>

<h3>
  
  
  ❌ 3. Offscreen components hydrate early
</h3>

<p>Even things not visible yet.</p>

<p>This model works, but it’s outdated for large apps.</p>




<h2>
  
  
  🟩 React 18+: Selective Hydration (Smarter, Not Linear)
</h2>

<p>React 18 replaced “hydrate everything in order” with:</p>

<blockquote>
<p><strong>Hydrate what’s needed, when it’s needed.<br>
Skip or delay the rest.</strong></p>
</blockquote>

<p>React evaluates multiple signals:</p>

<h3>
  
  
  React 18 automatically detects:
</h3>

<ul>
<li><strong>Which components are visible</strong></li>
<li><strong>Which components are interactive</strong></li>
<li><strong>Which have pending Suspense data</strong></li>
<li><strong>Which are above-the-fold</strong></li>
<li><strong>Which the user interacts with first</strong></li>
<li><strong>Which are heavier or lower priority</strong></li>
</ul>

<h3>
  
  
  Hydration priority:
</h3>

<p>1️⃣ Visible + interactive components<br>
2️⃣ User-clicked or user-focused components<br>
3️⃣ Above-the-fold content<br>
4️⃣ Suspense boundaries that resolved<br>
5️⃣ Below-the-fold or non-interactive UI<br>
6️⃣ Everything else, when browser is idle</p>

<p>This is <strong>selective hydration</strong> — only hydrate the parts users need <em>immediately</em>.</p>


<h2>
  
  
  🟦 How Suspense Affects Hydration
</h2>

<p>Consider:<br>
</p>

<div class="highlight js-code-highlight">
<pre class="highlight jsx"><code><span class="p">&lt;</span><span class="nc">Suspense</span> <span class="na">fallback</span><span class="p">=</span><span class="si">{</span><span class="p">&lt;</span><span class="nc">LoadingUser</span> <span class="p">/&gt;</span><span class="si">}</span><span class="p">&gt;</span>
  <span class="p">&lt;</span><span class="nc">UserProfile</span> <span class="p">/&gt;</span>
<span class="p">&lt;/</span><span class="nc">Suspense</span><span class="p">&gt;</span>
</code></pre>

</div>



<p>React can stream HTML in chunks:</p>

<ul>
<li>Server streams <code>&lt;LoadingUser /&gt;</code> first</li>
<li>Later streams <code>&lt;UserProfile /&gt;</code> when data resolves</li>
<li>Client hydrates these boundaries <strong>independently</strong>
</li>
<li>Hydration can happen <strong>in the middle</strong>, <strong>out of order</strong>, or <strong>scattered</strong>
</li>
</ul>

<p>Suspense creates natural hydration islands.</p>




<h2>
  
  
  🔥 BIG Real-World Example (SSR + Suspense + Complex Layout)
</h2>

<p>Imagine a dashboard:<br>
</p>

<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code>+----------------------+
| Navbar               |
+----------------------+
| Sidebar | Chart      |
|         | (Suspense) |
|         |            |
+----------------------+
</code></pre>

</div>



<h3>
  
  
  Server Output (HTML)
</h3>

<ul>
<li>Navbar rendered immediately</li>
<li>Sidebar rendered immediately</li>
<li>Chart is slow → Suspense fallback is sent</li>
</ul>

<p>Client sees:<br>
</p>

<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code>Navbar (interactive instantly)
Sidebar (interactive instantly)
Chart loading skeleton…
</code></pre>

</div>



<h3>
  
  
  Hydration (React 18):
</h3>

<p>1️⃣ User clicks sidebar → React hydrates sidebar immediately<br>
2️⃣ Navbar is visible → hydrate early<br>
3️⃣ Chart fallback hydrates next (lightweight)<br>
4️⃣ Actual Chart component hydrates <strong>only when its data resolves</strong><br>
5️⃣ Footer hydrates when browser is idle</p>

<p>This is <strong>selective, scattered, priority-driven hydration.</strong></p>


<h2>
  
  
  🟨 Is Progressive Hydration Needed in React?
</h2>

<p><strong>React 18 already does a form of progressive hydration</strong>:</p>

<p>✔ Selective hydration<br>
✔ Suspense boundary hydration<br>
✔ Hydrate-on-interaction<br>
✔ Hydrate-visible-first<br>
✔ Hydrate background content later<br>
✔ Hydrate streaming chunks as they arrive</p>

<p>React does not call it “progressive hydration,” but practically, it achieves that behavior.</p>


<h2>
  
  
  🟩 SSG + Hydration — Does Hydration Still Happen?
</h2>

<p>Yes.</p>

<p>SSG also needs hydration because:</p>

<ul>
<li>HTML is static</li>
<li>But JS must still attach event handlers</li>
<li>Framework re-runs components on client</li>
<li>Event listeners get connected</li>
<li>State becomes reactive</li>
</ul>

<p>Example:<br>
A static blog page still hydrates “Like Button”, comments, interactive parts.</p>

<p>SSG = static HTML + hydration on client.</p>


<h2>
  
  
  🔰 How Other Frameworks Handle Progressive Hydration
</h2>

<p>Now let's compare how different frameworks hydrate:</p>


<h2>
  
  
  🟦 Vue 3 (Classic) — Linear Hydration
</h2>

<p>Vue's default hydration is still <strong>linear</strong> unless using advanced tooling.</p>
<h3>
  
  
  Hydration flow:
</h3>


<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code>1. Hydrate root instance
2. Hydrate children in DOM order
3. Hydrate nested components
4. Finally hydrate leaf nodes
</code></pre>

</div>

<h3>
  
  
  Downsides:
</h3>

<ul>
<li>Slower interactivity for large pages</li>
<li>No Suspense-driven hydration</li>
<li>No hydrate-on-interaction by default</li>
</ul>

<p>But this changes with <strong>Nuxt 3</strong>…</p>


<h2>
  
  
  🟩 Nuxt 3 — “Progressive, Island-Style” Hydration
</h2>

<p>Nuxt 3 introduced <strong>partial hydration capabilities</strong>, similar to islands architecture:</p>
<h3>
  
  
  ✔ <code>client:only</code>
</h3>

<p>Component is only hydrated when needed:<br>
</p>

<div class="highlight js-code-highlight">
<pre class="highlight html"><code><span class="nt">&lt;client-only&gt;</span>
  <span class="nt">&lt;FancyChart</span> <span class="nt">/&gt;</span>
<span class="nt">&lt;/client-only&gt;</span>
</code></pre>

</div>



<h3>
  
  
  ✔ Async Components + Suspense
</h3>

<p>Nuxt 3 supports Suspense-like behavior:<br>
</p>

<div class="highlight js-code-highlight">
<pre class="highlight html"><code><span class="nt">&lt;Suspense&gt;</span>
  <span class="nt">&lt;UserProfile</span> <span class="nt">/&gt;</span>
<span class="nt">&lt;/Suspense&gt;</span>
</code></pre>

</div>



<p>This allows:</p>

<ul>
<li>above-the-fold hydration first</li>
<li>async component hydration later</li>
<li>streamed HTML + partial hydration</li>
</ul>

<h3>
  
  
  ✔ Nuxt + Nitro + Island Optimizations
</h3>

<p>Nuxt aggressively optimizes hydration for:</p>

<ul>
<li>per-component hydration</li>
<li>hydration skipping for static parts</li>
<li>“hybrid island architecture”</li>
</ul>

<p>While it's not as automatic as React's selective hydration,<br>
Nuxt 3 can achieve progressive hydration with explicit patterns.</p>


<h2>
  
  
  🟧 SvelteKit — Progressive Hydration by Default
</h2>

<p>SvelteKit hydrates:</p>

<ul>
<li>visible sections first</li>
<li>interactive sections first</li>
<li>lazy components when needed</li>
</ul>

<p>Svelte also supports <strong>component-level hydration</strong>:</p>

<ul>
<li>preload only what's visible</li>
<li>lazy load everything else</li>
<li>hydrate only when scrolled into view</li>
<li>hydrate on interaction</li>
</ul>

<p>Very efficient because Svelte compiles away most framework runtime.</p>


<h2>
  
  
  🟦 SolidStart — Fine-Grained Hydration
</h2>

<p>Solid uses reactive primitives and compiles away components.<br>
Hydration happens:</p>

<ul>
<li>per DOM node</li>
<li>per reactive signal</li>
<li>not per component</li>
</ul>

<p>This makes hydration extremely granular.</p>

<p>SolidStart naturally does <strong>progressive + selective hydration</strong>.</p>


<h2>
  
  
  🟣 Qwik — No Hydration (Resumes Instead)
</h2>

<p>Qwik doesn’t hydrate at all.</p>

<p>It <strong>resumes</strong> the app from HTML with embedded state.<br>
Event listeners are attached lazily.</p>

<p>Progressive hydration is built-in because Qwik doesn't hydrate entire trees — it loads behavior on demand.</p>


<h2>
  
  
  🌑 Astro — Island Architecture (Hydrate Only What You Ask)
</h2>

<p>Astro hydrates components only when instructed:<br>
</p>

<div class="highlight js-code-highlight">
<pre class="highlight html"><code><span class="nt">&lt;Counter</span> <span class="na">client:load</span> <span class="nt">/&gt;</span>
<span class="nt">&lt;Chart</span> <span class="na">client:visible</span> <span class="nt">/&gt;</span>
<span class="nt">&lt;Sidebar</span> <span class="na">client:idle</span> <span class="nt">/&gt;</span>
</code></pre>

</div>



<p>Modes:</p>

<ul>
<li><code>client:load</code></li>
<li><code>client:visible</code></li>
<li><code>client:idle</code></li>
<li><code>client:media</code></li>
<li><code>client:hover</code></li>
</ul>

<p>A pure island architecture.<br>
Astro minimizes JS for non-interactive content, best-in-class for performance.</p>




<h2>
  
  
  🟩 Summary: How Frameworks Hydrate
</h2>

<div class="table-wrapper-paragraph"><table>
<thead>
<tr>
<th>Framework</th>
<th>Hydration Style</th>
<th>Notes</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>React 18+</strong></td>
<td>Selective, priority-based, Suspense-aware</td>
<td>Automatic</td>
</tr>
<tr>
<td><strong>Vue 3 classic</strong></td>
<td>Linear</td>
<td>Simple but slower</td>
</tr>
<tr>
<td><strong>Nuxt 3</strong></td>
<td>Partial/Client-only/Islands</td>
<td>Supports progressive hydration</td>
</tr>
<tr>
<td><strong>SvelteKit</strong></td>
<td>Progressive</td>
<td>Hydrates visible/interacted UI first</td>
</tr>
<tr>
<td><strong>SolidStart</strong></td>
<td>Fine-grained</td>
<td>Tiny hydration chunks</td>
</tr>
<tr>
<td><strong>Qwik</strong></td>
<td>No hydration → Resume</td>
<td>Most advanced</td>
</tr>
<tr>
<td><strong>Astro</strong></td>
<td>Islands</td>
<td>Hydrate only what you choose</td>
</tr>
</tbody>
</table></div>




<h2>
  
  
  🎉 Final Thoughts
</h2>

<p>In modern SSR/SSG frameworks:</p>

<ul>
<li>Hydration is <em>the cost of interactivity</em>
</li>
<li>Linear hydration is slow</li>
<li>Progressive + selective hydration is the future</li>
<li>React 18+ achieves it automatically</li>
<li>Nuxt 3, SvelteKit, Qwik, Astro each do it differently</li>
<li>Suspense brings async-shaped hydration</li>
<li>Streaming SSR improves TTFB dramatically</li>
</ul>

<p>If you understand hydration deeply,<br>
you understand the foundation of modern web frameworks in 2025.</p>

تعتبر عملية الترطيب مفهومًا حيويًا ولكنه غالبًا ما يُساء فهمه في أطر العمل الحديثة للواجهة الأمامية. في عام 2025، تتبنى أطر العمل مثل React 18+ وVue/Nuxt 3 وSvelteKit وSolidStart وQwik وAstro أساليب مختلفة للترطيب، بما في ذلك الترطيب التدريجي والانتقائي والجزئي، وبعضها لا يكتمل أبدًا. يقدم هذا المقال تحليلًا شاملاً لعملية الترطيب مع أمثلة حقيقية، ويغطي سيناريوهات التقديم من جانب الخادم (SSR) وتوليد المواقع الثابتة (SSG)، مما يضمن فهمًا جيدًا للمفهوم.

La hidratación es un concepto crucial pero a menudo mal entendido en los frameworks frontend modernos. En 2025, frameworks como React 18+, Vue/Nuxt 3, SvelteKit, SolidStart, Qwik y Astro adoptan diferentes enfoques para la hidratación, incluyendo progresiva, selectiva, parcial y algunos que nunca se hidratan completamente. Este artículo ofrece un desglose completo de la hidratación con ejemplos reales, abarcando escenarios de Renderizado del Lado del Servidor (SSR) y Generación de Sitios Estáticos (SSG), asegurando que el concepto se entienda bien.

L'hydratation est un concept crucial mais souvent mal compris dans les frameworks frontend modernes. En 2025, des frameworks tels que React 18+, Vue/Nuxt 3, SvelteKit, SolidStart, Qwik et Astro adoptent différentes approches de l'hydratation, y compris progressive, sélective, partielle et certains qui ne s'hydratent jamais complètement. Cet article fournit une analyse complète de l'hydratation avec des exemples concrets, couvrant les scénarios de rendu côté serveur (SSR) et de génération de site statique (SSG), garantissant une bonne compréhension du concept.

Hydration is a crucial yet often misunderstood concept in modern frontend frameworks. In 2025, frameworks such as React 18+, Vue/Nuxt 3, SvelteKit, SolidStart, Qwik, and Astro adopt various approaches to hydration, including progressive, selective, partial, and some that never fully hydrate. This article provides a comprehensive breakdown of hydration with real examples, covering Server-Side Rendering (SSR) and Static Site Generation (SSG) scenarios, ensuring the concept is well understood.

🧠 Hydration, Selective Hydration & Progressive Hydration Explained (React vs Vue/Nuxt vs Others)

<A HREF="https://fortune.com/2025/11/19/exclusive-doppel-raises-70-million-series-c-at-more-than-600-million-valuation-to-fight-ai-powered-social-engineering-attacks/"><IMG VSPACE="4" HSPACE="4" BORDER="0" ALIGN="RIGHT" SRC="http://www.techmeme.com/251119/i39.jpg"></A>
<P><A HREF="http://www.techmeme.com/251119/p39#a251119p39" TITLE="Techmeme permalink"><IMG WIDTH=11 HEIGHT=12 SRC="http://www.techmeme.com/img/pml.png" STYLE="border:none;padding:0;margin:0;"></A> Allie Garfinkle / <A HREF="http://www.fortune.com/">Fortune</A>:<BR>
<SPAN STYLE="font-size:1.3em;"><B><A HREF="https://fortune.com/2025/11/19/exclusive-doppel-raises-70-million-series-c-at-more-than-600-million-valuation-to-fight-ai-powered-social-engineering-attacks/">Doppel, which makes an AI social engineering detection service, raised a $70M Series C led by Bessemer at a $600M+ valuation, up from $205M in May</A></B></SPAN>&nbsp; &mdash;&nbsp; Senior Finance Reporter And Author Of Term Sheet&nbsp; &mdash;&nbsp; I tried to fool my brother, sort of.&nbsp; &mdash;&nbsp; Next to him and his Pekingese on the couch &hellip; </P>

دوبل، وهي شركة متخصصة في خدمات الكشف عن الهندسة الاجتماعية باستخدام الذكاء الاصطناعي، نجحت في جمع 70 مليون دولار في جولة تمويل من السلسلة C بقيادة بيسمر. وقد زادت هذه الجولة من تقييم الشركة إلى أكثر من 600 مليون دولار، ارتفاعًا من 205 مليون دولار في مايو.

Doppel, una empresa que se especializa en servicios de detección de ingeniería social mediante IA, ha recaudado con éxito 70 millones de dólares en una ronda de financiación Serie C liderada por Bessemer. Esta ronda ha elevado la valoración de la empresa a más de 600 millones de dólares, un aumento significativo desde los 205 millones en mayo.

Doppel, une entreprise spécialisée dans les services de détection d'ingénierie sociale par IA, a levé avec succès 70 millions de dollars lors d'un tour de financement de série C dirigé par Bessemer. Ce tour de financement a porté la valorisation de l'entreprise à plus de 600 millions de dollars, contre 205 millions en mai.

Doppel, a company specializing in AI social engineering detection services, has successfully raised $70 million in a Series C funding round led by Bessemer. This funding round has increased the company's valuation to over $600 million, a significant rise from $205 million in May.

Doppel, which makes an AI social engineering detection service, raised a $70M Series C led by Bessemer at a $600M+ valuation, up from $205M in May (Allie Garfinkle/Fortune)

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<p><a href="https://fetch.ai/">Fetch AI</a>, a startup founded and led by former DeepMind founding investor, Humayun Sheikh, <a href="https://www.businesswire.com/news/home/20251119088395/en/Fetch-Combines-Personalized-AI-with-Multi-Agent-Collaboration-to-Handle-Complex-Consumer-Tasks-Launches-Claim-Your-Agent-to-Fight-Brand-Knock-Offs">today announced the release</a> of three interconnected products designed to provide the trust, coordination, and interoperability needed for large-scale AI agent ecosystems. </p><p>The launch includes <a href="https://asi1.ai/">ASI:One</a>, a personal-AI orchestration platform; <a href="https://business.fetch.ai/">Fetch Business</a>, a verification and discovery portal for brand agents; and <a href="https://agentverse.ai/?sort=relevancy&amp;page=1&amp;recommended=true">Agentverse</a>, an open directory hosting more than two million agents. </p><p>Together, the system positions Fetch as an infrastructure provider for what it calls the “Agentic Web”—a layer where consumer AIs and brand AIs collaborate to complete tasks instead of merely suggesting them.</p><p>The company says the tools address a central limitation in current consumer AI: models can provide recommendations but cannot reliably execute multi-step actions that require coordination across businesses. Fetch’s approach centers on enabling agents from different organizations to interoperate securely, using verified identities and shared context to complete end-to-end workflows.</p><p>“We’re creating the same foundation for agents that Google created for websites,” said Humayun Sheikh, Founder and CEO of Fetch AI, and an early investor in DeepMind, in a press release provided to VentureBeat. “Instead of just finding information, your personal AI coordinates with verified brand agents to get things done.”</p><h2><b>Background: Fetch’s Founding and DeepMind Connection </b></h2><p>Fetch AI was founded in 2017 by Humayun Sheikh, an entrepreneur whose early investment in DeepMind helped support the company’s commercial development before its acquisition by Google. “I was one of the first five people at DeepMind and its first investor. My check was the first one in,” Sheikh said, reflecting on the period when advanced machine learning research was still largely inaccessible outside major technology companies.</p><p>His early experience helped shape Fetch’s direction. “Even in 2013, it was clear to me that agentic systems were going to be the ones that worked. That’s where I focused—on the agentic web,” Sheikh noted. Fetch built on this thesis by developing infrastructure for autonomous software agents, focusing on verifiable identity, secure data exchange, and multi-agent coordination. </p><p>Over the past several years, the company has expanded to a 70-person team across Cambridge and Menlo Park, raised approximately $60 million, and accumulated more than one million users interacting with its model—data that informed the design of the newly launched products.</p><p>Sheikh added that his decision to bootstrap the company initially came directly from the proceeds of the DeepMind exit, noting in the interview that while the sale to Google was “a good exit,” he believed the team could have held out for a higher valuation. </p><p>The early self-funding period allowed Fetch to begin work in 2015—well before transformer architectures went mainstream—on the hypothesis that agentic infrastructure would become foundational to applied AI.</p><h2><b>ASI:One — A Platform for Multi-Agent Orchestration</b></h2><p>At the core of the launch is <b>ASI:One</b>, a language model interface designed specifically for coordinating multiple agents rather than addressing isolated queries. Fetch describes it as an “intelligence layer” that handles context sharing, task routing, and preference modeling.</p><p>The system stores user-level signals such as favored airlines, dietary constraints, budget ranges, loyalty program identifiers, and calendar availability. When a user requests a complex task—such as planning a trip with flights, hotels, and restaurant reservations—ASI:One retrieves those preferences and delegates work to the appropriate verified agents. The agents then return actionable outputs, including inventory and booking options, rather than generic recommendations.</p><p>In practice, ASI:One functions as a workflow generator across organizational boundaries. By contrast with conventional LLM applications, which often rely on APIs or RAG techniques to surface information, ASI:One is built to coordinate autonomous agents that can complete transactions. Fetch notes that personalization improves over time as the model accumulates structured preference data.</p><p>Sheikh emphasized the distinction between orchestrated execution and traditional AI output. “This isn’t searching for options separately and hoping they work together,” he said. “It’s orchestration.” </p><p>He added that Fetch’s architecture is intentionally modular: “Our architecture is a mix of agentic and expert models. One large model isn’t enough—you need specialists. That’s why we built ASI1, tuned specifically for agentic systems.”</p><p>The interview also revealed new details about ASI:One’s personalization systems: the platform uses multiple user-owned knowledge graphs to store preferences, travel history, social connections, and contextual constraints. </p><p>These knowledge graphs are siloed per user and not co-mingled with any Fetch-operated data. Sheikh described this as a “deterministic backbone” that gives the personal AI a stable memory layer beyond the probabilistic output of a single large model.</p><p>ASI:One launches in Beta today, with a broader release planned for early 2026. Fetch also offers ASI:One Mobile, released earlier this year, giving users access to the same agent-orchestration capabilities on iOS and Android. The mobile app connects directly to Agentverse and the user’s knowledge graphs, enabling on-the-go task execution and real-time interaction with registered agents.</p><h2><b>Fetch Business — Verified Identity and Brand Control</b></h2><p>To enable reliable coordination between consumers and companies, Fetch is introducing a verification and discovery portal called Fetch Business. </p><p>The platform allows organizations to verify their identity and claim an official Brand Agent handle—for example, @Hilton or @Nike—regardless of which tools they use to build the underlying agent.</p><p>Fetch positions the product as an analogue to ICANN domain registration and SSL certificate systems for websites. Verified status is intended to protect consumers from interacting with counterfeit or untrusted agents, a problem the company describes as a major barrier to widespread agent adoption.</p><p>The system includes low-code tools for small businesses to create agents in a few steps and connect real-time APIs such as inventory, booking systems, or CRM platforms. </p><p>“With Fetch, you can create an agent in one minute. It gets a handle, like a Twitter username, and you can personalize it completely—even give it your social media permissions to post on your behalf,” Sheikh said. Once a brand claims its namespace, its agent becomes discoverable to consumer AIs and other agents inside Agentverse.</p><p>The company has pre-reserved thousands of brand namespaces in anticipation of demand. Verification status persists across any platform that integrates with Agentverse, creating a portable identity layer for business agents.</p><p>The interview highlighted that Fetch Business inherits web-trust primitives directly: domain owners verify their identity by inserting a short code snippet into their existing website backend, allowing the system to pass a cryptographic challenge and grant the agent an authenticity badge similar to a “blue check” for agent identities. Sheikh framed this as “reusing the trust layer the web already spent decades building.”</p><p>Companies can begin claiming agents now at <a href="https://business.fetch.ai/"><b>business.fetch.ai</b></a>.</p><h2><b>Agentverse — An Open Directory of More Than Two Million Agents</b></h2><p>The final component of the release is <a href="https://agentverse.ai/">Agentverse</a>, an open directory and cloud platform that hosts agents and enables cross-ecosystem discoverability. Fetch states that millions of agents have already registered, spanning travel, retail, entertainment, food service, and enterprise categories.</p><p>Agentverse provides metadata, capability descriptions, and routing logic that ASI:One uses to identify appropriate agents for specific tasks. It also supports secure communication and data exchange between agents. The company notes that the directory is platform-agnostic: agents built with any framework can join and interoperate.</p><p>According to Sheikh, the lack of a discovery layer is one reason most AI agents see little or no usage. “Ninety percent of AI agents never get used because there’s no discovery layer,” he said. </p><p>He framed the role of Agentverse in more technical terms: “Right now, if you build an agent, there’s no universal way for others to discover it. That’s what AgentVerse solves—it’s like DNS for agents.” He also described the system as an essential component of the emerging agent economy: “Fetch is building the Google of agents. Just like websites needed search, agents need discovery, trust, and interaction—Fetch provides all of that.”</p><p>The interview further underscored that Agentverse is cloud-agnostic by design. Sheikh contrasted this with competing agent ecosystems tied to specific cloud providers, arguing that a universal registry is only viable if independent of proprietary cloud environments. He said the open architecture enables an LLM to query any agent “within one minute of deployment,” turning agent publication into a near-instantaneous process similar to registering a domain.</p><p>Agentverse also integrates payment pathways, enabling agents to execute purchases using partners such as Visa, Skyfire, and supported stablecoins. Consumers can configure spending limits or require explicit approval for transactions.</p><h2><b>Industry Context and Implications</b></h2><p>Fetch’s launch comes at a time when consumer AI platforms are exploring the shift from static chat interfaces toward autonomous agents capable of completing actions. However, most agent systems remain limited by siloed architectures, limited interoperability, and weak verification standards.</p><p>Fetch positions its infrastructure as a response to these limitations by providing a cross-platform coordination layer, identity system, and directory service. The company argues that an agent ecosystem requires consistent verification mechanisms to ensure that consumers interact with authentic brand representatives rather than imitations. By establishing namespace control and portable trust indicators, Fetch Business aims to fill a gap similar to early web domain verification.</p><p>At the same time, ASI:One attempts to centralize user preference data in a way that enables more efficient personalization and multi-agent coordination. This approach differs from generalist LLM applications, which often lack persistent preference architectures or direct access to brand-controlled agents.</p><p>The interview also made clear that micropayments and digital transaction infrastructure are central to Fetch’s long-term vision. Sheikh referenced integrations with protocols such as Coinbase’s 402 and AP2, positioning these capabilities as essential for autonomous agents to complete end-to-end tasks that include financial execution.</p><h2><b>Takeaway</b></h2><p>Fetch’s combined release of ASI:One, Fetch Business, and Agentverse introduces an interconnected stack designed to support large-scale deployment and usage of AI agents. The company frames the system as foundational infrastructure for an agentic ecosystem, where consumer AIs can coordinate with verified brand agents to complete tasks reliably and securely. The additions to its identity, discovery, and orchestration layers reflect Fetch’s long-standing thesis—rooted partly in lessons from DeepMind’s early development—that intelligence becomes meaningful only when paired with the capacity to act.</p>

أطلقت شركة Fetch AI، وهي شركة ناشئة يقودها هميون شيخ، ثلاثة منتجات مترابطة تهدف إلى تعزيز نظام وكلاء الذكاء الاصطناعي. تشمل العروض الجديدة ASI:One، وهي منصة تنسيق ذكاء اصطناعي شخصي، وFetch Business، وهو بوابة للتحقق والاكتشاف لوكلاء العلامات التجارية، وAgentverse، وهو دليل مفتوح يضم أكثر من مليوني وكيل. تسعى هذه المبادرة إلى إنشاء بنية تحتية قوية لما تصفه Fetch بـ 'الويب الوكالي.'

Fetch AI, una startup dirigida por Humayun Sheikh, ha lanzado tres productos interconectados destinados a mejorar el ecosistema de agentes de IA. Las nuevas ofertas incluyen ASI:One, una plataforma de orquestación de IA personal, Fetch Business, un portal de verificación y descubrimiento para agentes de marca, y Agentverse, un directorio abierto con más de dos millones de agentes. Esta iniciativa busca establecer una infraestructura sólida para lo que Fetch describe como la 'Web Agente.'

Fetch AI, une startup dirigée par Humayun Sheikh, a lancé trois produits interconnectés visant à améliorer l'écosystème des agents IA. Les nouvelles offres comprennent ASI:One, une plateforme d'orchestration d'IA personnelle, Fetch Business, un portail de vérification et de découverte pour les agents de marque, et Agentverse, un annuaire ouvert avec plus de deux millions d'agents. Cette initiative vise à établir une infrastructure robuste pour ce que Fetch décrit comme le 'Web Agentique.'

Fetch AI, a startup led by Humayun Sheikh, has launched three interconnected products aimed at enhancing the ecosystem of AI agents. The new offerings include ASI:One, a personal-AI orchestration platform, Fetch Business, a verification and discovery portal for brand agents, and Agentverse, an open directory with over two million agents. This initiative seeks to establish a robust infrastructure for what Fetch describes as the 'Agentic Web.'

The Google Search of AI agents? Fetch launches ASI:One and Business tier for new era of non-human web

If aesthetics and efficiency top your list of needs, there are several Linux distributions that are right up your alley. Both Ubuntu Budgie and Pop!_OS should top that list.

Ubuntu Budgie vs. Pop!_OS: I've used both Linux distros - here's how to choose

React Hook Form هي مكتبة خفيفة مصممة لتبسيط إدارة النماذج في تطبيقات React. توفر تجربة مستخدم بديهية مع ميزات غنية بينما تقلل من الاعتماد على المكتبات الأخرى. تعزز المكتبة الأداء من خلال تقليل تعقيد الشيفرة وعدد إعادة العرض من خلال استخدام المكونات غير المتحكم بها بشكل افتراضي، مما يجعل التحقق من صحة النماذج سهلاً من خلال الاستفادة من العلامات HTML الموجودة.

React Hook Form es una biblioteca ligera diseñada para simplificar la gestión de formularios en aplicaciones React. Ofrece una experiencia de usuario intuitiva con características ricas mientras minimiza las dependencias. La biblioteca mejora el rendimiento al reducir la complejidad del código y el número de re-renderizados mediante el uso predeterminado de componentes no controlados, facilitando la validación de formularios al aprovechar el marcado HTML existente.

React Hook Form est une bibliothèque légère conçue pour simplifier la gestion des formulaires dans les applications React. Elle offre une expérience utilisateur intuitive avec des fonctionnalités riches tout en minimisant les dépendances. La bibliothèque améliore les performances en réduisant la complexité du code et le nombre de re-renders grâce à son utilisation par défaut de composants non contrôlés, rendant la validation des formulaires simple en s'appuyant sur le balisage HTML existant.

React Hook Form is a lightweight library designed to simplify form management in React applications. It offers an intuitive user experience with rich features while minimizing dependencies. The library enhances performance by reducing code complexity and the number of re-renders through its default use of uncontrolled components, making form validation straightforward by leveraging existing HTML markup.

Get Started with React Hook Form

<h1>
  
  
  Black Weeks. The big 50% is here.
</h1>

<p>Every year I get messages from developers saying the same thing:</p>

<p>“I want to ship faster.”<br>
“I’m tired of ugly templates.”<br>
“I don’t have time to design.”<br>
“I just want to build.”</p>

<p>That’s exactly why I built Lexington Themes in the first place — a growing library of <strong>Astro + Tailwind CSS templates</strong> built to look good, load fast, and get out of your way.</p>

<p>This Black Weeks, I’m doing something stupidly generous:</p>

<p><strong>50% OFF Full Access.</strong><br>
Use code <strong>LEX50</strong> at checkout.</p>

<p>You get <strong>all 39 premium themes</strong>, every future release, and ongoing updates. One time payment. No subscription nonsense.</p>

<p>— <strong><a href="https://lexingtonthemes.com/" rel="noopener noreferrer">https://lexingtonthemes.com/</a></strong></p>




<h2>
  
  
  Why developers keep choosing Lexington Themes
</h2>

<p>Since 2023, more than <strong>7,000 customers</strong> have launched sites with these templates. It became the <strong>largest Astro theme library</strong>, and even the Astro team gave it an award.</p>

<p>People describe them better than I ever could:</p>

<blockquote>
<p>“Top-notch design.”<br>
“Well-organized and fast.”<br>
“Beautifully coded — I’m actually learning from it.”<br>
“Every theme’s a piece of art.”<br>
“The best deal any web developer could make.”<br>
“Saved me weeks of work.”</p>
</blockquote>

<p>The point is: it’s not hype. It’s a real tool that helps real developers move faster.</p>




<h2>
  
  
  What you actually get
</h2>

<p>No hand-wavy marketing. Here’s the concrete stuff:</p>

<ul>
<li><strong>39 complete Astro + Tailwind templates</strong></li>
<li><strong>Every new theme added in the future</strong></li>
<li>
<strong>GitHub repository access</strong> (Full history + updates)</li>
<li>
<strong>Use in unlimited projects</strong> (personal + client work)</li>
<li><strong>Lifetime updates</strong></li>
<li><strong>Lifetime support (Discord + email)</strong></li>
<li><strong>Designs that don’t look like bargain-bin templates</strong></li>
<li>
<strong>SEO-ready structure</strong>, lightweight pages, optimized images</li>
<li>Works with <strong>Vercel, Netlify, Cloudflare, Node, GitHub Pages, Deno, AWS</strong>
</li>
<li>Extend with <strong>React, Vue, Svelte, Solid, TypeScript</strong>, whatever you want</li>
<li>Clean folder structure and type-safe content collections</li>
<li>Zero bloat. Zero headaches.</li>
</ul>

<p>And yes — you can ship a full site in a few hours if you’re not overthinking it.</p>




<h2>
  
  
  Who this is for
</h2>

<p>If you’re a:</p>

<ul>
<li>Freelancer who needs to deliver fast</li>
<li>Designer who wants clean starting points</li>
<li>Indie dev trying to ship a product</li>
<li>Agency that needs repeatable, reliable templates</li>
<li>Founder building a marketing site yesterday</li>
</ul>

<p>— then Full Access saves you ridiculous amounts of time.</p>

<p>If you're the type who loves reinventing the wheel, this isn’t for you.</p>




<h2>
  
  
  The deal
</h2>

<p><strong>Black Weeks: 50% OFF Full Access</strong><br>
Use code <strong>LEX50</strong></p>

<p>— <strong><a href="https://lexingtonthemes.com/" rel="noopener noreferrer">https://lexingtonthemes.com/</a></strong></p>

<p>If you’ve been waiting for the right moment to grab it — this is the moment. It doesn’t get cheaper than this.</p>

<p>Ship faster. Look better. Stress less.</p>

أطلقت Lexington Themes عرض Black Weeks، حيث تقدم خصمًا بنسبة 50% على الوصول الكامل إلى مكتبتها من قوالب Astro وTailwind CSS. يتيح هذا العرض للمطورين شراء جميع القوالب المميزة البالغ عددها 39، بالإضافة إلى الإصدارات المستقبلية والتحديثات المستمرة مقابل دفعة واحدة باستخدام الرمز LEX50. منذ تأسيسها، جذبت Lexington Themes أكثر من 7000 عميل، مما يلبي احتياجات المطورين الذين يسعون للبناء بسرعة دون عناء التصميم أو استخدام القوالب غير الجذابة.

Lexington Themes ha lanzado su promoción de Black Weeks, ofreciendo un 50% de descuento en el acceso completo a su biblioteca de plantillas Astro y Tailwind CSS. Esta promoción permite a los desarrolladores adquirir todos los 39 temas premium, así como futuras versiones y actualizaciones continuas con un pago único utilizando el código LEX50. Desde su creación, Lexington Themes ha atraído a más de 7,000 clientes, atendiendo las necesidades de los desarrolladores que buscan construir rápidamente sin la molestia de diseñar o usar plantillas poco atractivas.

Lexington Themes a lancé sa promotion des Black Weeks, offrant une réduction de 50 % sur l'accès complet à sa bibliothèque de modèles Astro et Tailwind CSS. Cette promotion permet aux développeurs d'acheter tous les 39 thèmes premium, les futures versions et les mises à jour continues avec un paiement unique en utilisant le code LEX50. Depuis sa création, Lexington Themes a attiré plus de 7 000 clients, répondant aux besoins des développeurs qui cherchent à construire rapidement sans le tracas de la conception ou l'utilisation de modèles peu attrayants.

Lexington Themes has launched its Black Weeks promotion, offering a 50% discount on full access to its library of Astro and Tailwind CSS templates. This promotion allows developers to purchase all 39 premium themes, future releases, and ongoing updates with a one-time payment using the code LEX50. Since its inception, Lexington Themes has attracted over 7,000 customers, addressing the needs of developers who seek to build quickly without the hassle of designing or using unattractive templates.

Black Weeks. The big 50% is here.

<p>SQL Server 2025 has been <a href="https://techcommunity.microsoft.com/blog/sqlserver/sql-server-2025-is-now-generally-available/4470570" rel="noopener noreferrer">officially announced</a> at Microsoft Ignite 2025 and is now generally available.  It had been in public preview since May of 2025 and consumers have been eagerly anticipating the official release of one of Microsoft's most popular software products. I had previous written a fun article where I used AI and historical date like previews, events, and past release dates to try and guess the <a href="https://www.trustedtechteam.com/blogs/sql-server/sql-server-2025-release-date" rel="noopener noreferrer">release date of SQL Server 2025</a>.  </p>

<p>Now it's finally here, and with it comes a whole host of highly anticipated features, most notably AI integration. </p>

<h2>
  
  
  Major Themes
</h2>

<p><strong><a href="https://www.trustedtechteam.com/blogs/sql-server/sql-server-2025-new-ai-features" rel="noopener noreferrer">Built-in AI</a> &amp; vector search</strong></p>

<ul>
<li>SQL Server 2025 adds native support for vector-stores/indexing (via DiskANN) enabling semantic search over large datasets. </li>
<li>You can combine traditional keyword SQL queries with vector‐based search in one engine. </li>
<li>Support for retrieval-augmented generation (RAG) patterns, connecting to AI models via REST endpoints, etc. </li>
</ul>

<p><strong>Modern developer productivity enhancements</strong></p>

<ul>
<li>Native JSON support, regular expression support, REST APIs, GraphQL via Data API Builder, etc. </li>
<li>The idea is to let developers build AI-driven/modern applications whether on-premises or cloud with more extensibility. </li>
</ul>

<p><strong>Security, performance &amp; scalability</strong></p>

<ul>
<li>New authentication support via Microsoft Entra ID managed identities and outbound authentication via Azure Arc for hybrid/edge. </li>
<li>Improved query optimization: e.g., persisted statistics on replicas, improved locking mechanisms (TID Locking, LAQ) to reduce contention, improved batch processing and columnstore support for analytics. </li>
</ul>

<p><strong>Hybrid and cloud‐centric analytics &amp; data integration</strong></p>

<ul>
<li>Integration with Microsoft Fabric: near real-time replication of SQL Server data (mirrored database) into OneLake for analytics. </li>
<li>Better support for hybrid cloud, on-premises, and edge scenarios — managing, governing, monitoring across environments with Azure Arc, centralized management etc. </li>
</ul>

<h2>
  
  
  Why this matters
</h2>

<ul>
<li>The database is being positioned as a first‐class AI platform, not just a relational engine.</li>
<li>For companies with large datasets, or those looking to embed AI/semantic search capabilities, this version could significantly change how they build data and app-architectures.</li>
<li>For hybrid/edge scenarios (on-premises + cloud + edge), the enhancements around Azure Arc, Fabric integration, and real-time replication make it easier to maintain consistency, governance, and analytics across environments.</li>
<li>Developers get more flexible tooling (JSON, REST, GraphQL etc) so the barrier to building modern apps on top of the database is lower.</li>
<li>Performance/scalability/security updates mean this is not just “shiny new features” but also foundation</li>
</ul>

تم الإعلان رسميًا عن SQL Server 2025 في مؤتمر Microsoft Ignite 2025 وهو متاح الآن بشكل عام. بعد معاينة عامة منذ مايو 2025، يتضمن الإصدار ميزات متوقعة بشدة، لا سيما دمج الذكاء الاصطناعي، مما يعزز قدراته كواحد من أكثر منتجات البرمجيات شعبية من Microsoft.

SQL Server 2025 ha sido anunciado oficialmente en Microsoft Ignite 2025 y ya está disponible. Después de una vista previa pública desde mayo de 2025, el lanzamiento incluye características muy esperadas, especialmente la integración de IA, mejorando sus capacidades como uno de los productos de software más populares de Microsoft.

SQL Server 2025 a été officiellement annoncé lors de Microsoft Ignite 2025 et est désormais disponible. Après une période de prévisualisation publique depuis mai 2025, cette version comprend des fonctionnalités très attendues, notamment l'intégration de l'IA, renforçant ses capacités en tant que l'un des produits logiciels les plus populaires de Microsoft.

SQL Server 2025 has been officially announced at Microsoft Ignite 2025 and is now generally available. After a public preview since May 2025, the release includes highly anticipated features, particularly AI integration, enhancing its capabilities as one of Microsoft's most popular software products.

SQL Server 2025 is Here!

<h1>
  
  
  AI Amnesia: Erasing Knowledge Without a Trace
</h1>

<p>Imagine your AI model accidentally learned something it shouldn't have – sensitive customer data, for example. Current methods for deleting this information often require retraining the entire model, an expensive and time-consuming process. What if we could surgically remove that knowledge without starting from scratch?</p>

<p>The key lies in a novel approach: creating artificial "forgetting cues." We're teaching the model to unlearn specific data patterns by exposing it to carefully crafted synthetic examples. These examples are designed to strongly contradict the information we want the model to forget, effectively overwriting the problematic associations in its memory. This works even if you don’t have access to the original data you need to erase.</p>

<p>Think of it like this: you're trying to forget a bad song stuck in your head. Instead of trying to actively suppress it (which rarely works), you blast an even more catchy song. The new song overwrites the old one, effectively erasing it from your mental playlist.</p>

<p><strong>Benefits of Selective Forgetting:</strong></p>

<ul>
<li>  <strong>Enhanced Data Privacy:</strong> Remove sensitive data without compromising the overall model's performance.</li>
<li>  <strong>Reduced Retraining Costs:</strong> Avoid full model retraining, saving significant time and resources.</li>
<li>  <strong>Improved Model Security:</strong> Eliminate vulnerabilities introduced by unintentionally learned patterns.</li>
<li>  <strong>Adaptable Learning:</strong> Enables continuous refinement of AI models based on evolving data landscapes.</li>
<li>  <strong>Compliance Ready:</strong> Supports compliance with data privacy regulations like GDPR.</li>
<li>  <strong>Scalable Solutions:</strong> Works efficiently even with limited access to training data.</li>
</ul>

<p><strong>Practical Tip:</strong> One challenge is ensuring the synthetic data accurately targets the information you want to remove without negatively impacting the model's ability to generalize. Rigorous testing and validation with holdout datasets are crucial.</p>

<p>The promise of AI that can truly 'forget' opens exciting possibilities for responsible AI development. By enabling precise data deletion, we pave the way for more secure, compliant, and adaptable machine learning systems. Imagine AI models that can adapt to changing ethical guidelines or quickly unlearn incorrect information, all without massive retraining efforts. This is a crucial step towards trustworthy and responsible AI that respects data privacy and aligns with societal values. Future exploration could include extending this to different data modalities and model architectures.</p>

<p><strong>Related Keywords:</strong> machine unlearning, data privacy, few-shot learning, zero-shot learning, synthetic data, model editing, catastrophic forgetting, incremental learning, continual learning, deep learning, neural networks, data security, algorithmic fairness, responsible ai, ethical ai, federated unlearning, privacy-preserving ai, model retraining, AI governance, data deletion, GDPR compliance</p>

يتناول المقال نهجًا جديدًا لمعالجة مشكلة نسيان الذكاء الاصطناعي، حيث قد تحتفظ نماذج الذكاء الاصطناعي عن غير قصد بمعلومات حساسة. تتطلب الطرق التقليدية لحذف هذه البيانات غالبًا إعادة تدريب كاملة للنموذج، وهو ما يعد مكلفًا ويستغرق وقتًا. تتضمن التقنية الجديدة إنشاء 'إشارات نسيان' اصطناعية تساعد النموذج على نسيان أنماط بيانات معينة من خلال تعريضه لأمثلة صناعية تتناقض مع المعلومات غير المرغوب فيها، مما يسمح بإزالة المعرفة المستهدفة دون الحاجة للوصول إلى البيانات الأصلية.

El artículo aborda un nuevo enfoque para tratar el problema de la amnesia de la IA, donde los modelos de IA pueden retener inadvertidamente información sensible. Los métodos tradicionales para eliminar estos datos a menudo requieren un reentrenamiento completo del modelo, lo que es costoso y lleva tiempo. La nueva técnica implica crear 'señales de olvido' artificiales que ayudan al modelo a desaprender patrones de datos específicos al exponerlo a ejemplos sintéticos que contradicen la información no deseada, permitiendo así la eliminación selectiva de conocimientos sin necesidad de acceder a l…

L'article traite d'une nouvelle approche pour résoudre le problème de l'amnésie de l'IA, où les modèles d'IA peuvent involontairement conserver des informations sensibles. Les méthodes traditionnelles pour supprimer ces données nécessitent souvent un réentraînement complet du modèle, ce qui est coûteux et long. La nouvelle technique consiste à créer des 'cues d'oubli' artificiels qui aident le modèle à désapprendre des schémas de données spécifiques en lui présentant des exemples synthétiques qui contredisent les informations indésirables, permettant ainsi une suppression ciblée des connaissan…

The article discusses a novel approach to address the issue of AI amnesia, where AI models may inadvertently retain sensitive information. Traditional methods for deleting such data often require complete retraining of the model, which is costly and time-consuming. The new technique involves creating artificial 'forgetting cues' that help the model unlearn specific data patterns by presenting it with synthetic examples that contradict the unwanted information, allowing for targeted knowledge removal without needing access to the original data.

🧠 Hydration, Selective Hydration & Progressive Hydration Explained (React vs Vue/Nuxt vs Others)

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