<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Vercel on SoloSoft</title><link>https://www.solosoft.dev/es/tags/vercel/</link><description>Recent content in Vercel on SoloSoft</description><generator>Hugo</generator><language>es-es</language><lastBuildDate>Fri, 01 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://www.solosoft.dev/es/tags/vercel/index.xml" rel="self" type="application/rss+xml"/><item><title>Agent Browser: Automatizacion de Navegador Open-Source de Vercel para Agentes IA</title><link>https://www.solosoft.dev/es/post/agent-browser-vercel-2026/</link><pubDate>Fri, 01 May 2026 00:00:00 +0000</pubDate><guid>https://www.solosoft.dev/es/post/agent-browser-vercel-2026/</guid><description>&lt;p&gt;Web automation has been a solved problem for decades — if you are willing to write code. Tools like Playwright, Puppeteer, and Selenium give developers precise control over browser interactions, letting them automate complex web workflows. But these tools require explicit instructions for every action: find this element, click it, wait for navigation, fill this field, submit.&lt;/p&gt;
&lt;p&gt;Agent Browser, from Vercel Labs, reimagines browser automation for the AI era. Instead of writing step-by-step browser scripts, you describe your goal in natural language, and the AI agent plans and executes the browser interactions. The tool combines Playwright&amp;rsquo;s reliable browser control with LLM-powered page understanding and action planning — letting you automate web workflows with the same ease as asking a human assistant.&lt;/p&gt;</description></item><item><title>Streamdown: El Renderizador de Markdown en Streaming de Vercel</title><link>https://www.solosoft.dev/es/post/streamdown-vercel-2026/</link><pubDate>Fri, 01 May 2026 00:00:00 +0000</pubDate><guid>https://www.solosoft.dev/es/post/streamdown-vercel-2026/</guid><description>&lt;p&gt;El auge de las interfaces de chat impulsadas por LLM ha creado un problema peculiar de experiencia de usuario: ver texto aparecer caracter por caracter es emocionante, pero ver Markdown parcialmente renderizado parpadear y saltar es frustrante. Cuando un LLM genera un bloque de codigo, una tabla o una lista anidada, los renderizadores Markdown estandar no pueden manejar la llegada incremental de tokens. Esperan la salida completa, luego la renderizan toda de una vez &amp;ndash; frustrando el proposito del streaming. Los usuarios miran texto sin procesar hasta que el stream termina, luego la pagina salta cuando todo se reformatea simultaneamente.&lt;/p&gt;</description></item></channel></rss>