You can now view the Cron Jobs from your application in the Deployment Summary section of Deployments.

Try it out by deploying a Vercel Cron Job template. Once you deploy, Vercel automatically registers your cron jobs. Learn more in the Cron Jobs documentation.

Today we're releasing a brand new set of components designed to help you build the next generation of IDEs, coding apps and background agents.

Link to heading<Agent />

A composable component for displaying an AI SDK ToolLoopAgent configuration with model, instructions, tools, and output schema.

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npx ai-elements add agent

Link to heading<CodeBlock />

Building on what we've learned from Streamdown, we massively improved the code block component with support for a header, icon, filename, multiple languages and a more performant renderer.

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npx ai-elements add code-block

Link to heading<Commit />

The Commit component displays commit details including hash, message, author, timestamp, and changed files.

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npx ai-elements add commit

Link to heading<EnvironmentVariables />

The EnvironmentVariables component displays environment variables with value masking, visibility toggle, and copy functionality.

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npx ai-elements add environment-variables

Link to heading<FileTree />

The FileTree component displays a hierarchical file system structure with expandable folders and file selection.

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npx ai-elements add file-tree

Link to heading<PackageInfo />

The PackageInfo component displays package dependency information including version changes and change type badges.

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npx ai-elements add package-info

Link to heading<Sandbox />

The Sandbox component provides a structured way to display AI-generated code alongside its execution output in chat conversations. It features a collapsible container with status indicators and tabbed navigation between code and output views.

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npx ai-elements add sandbox

Link to heading<SchemaDisplay />

The SchemaDisplay component visualizes REST API endpoints with HTTP methods, paths, parameters, and request/response schemas.

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npx ai-elements add schema-display

Link to heading<Snippet />

The Snippet component provides a lightweight way to display terminal commands and short code snippets with copy functionality. Built on top of shadcn/ui InputGroup, it's designed for brief code references in text.

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npx ai-elements add snippet

Link to heading<StackTrace />

The StackTrace component displays formatted JavaScript/Node.js error stack traces with clickable file paths, internal frame dimming, and collapsible content.

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npx ai-elements add stack-trace

Link to heading<Terminal />

The Terminal component displays console output with ANSI color support, streaming indicators, and auto-scroll functionality.

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npx ai-elements add terminal

Link to heading<TestResults />

The TestResults component displays test suite results (like Vitest) including summary statistics, progress, individual tests, and error details.

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npx ai-elements add test-results

Link to headingBonus: <Attachments />

Not code related, but since attachment were being used in Message, PromptInput and more, we broke it out into its own component - a flexible, composable attachment component for displaying files, images, videos, audio, and source documents.

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npx ai-elements add attachments

Skills support is now available in bash-tool, so your AI SDK agents can use the skills pattern with filesystem context, Bash execution, and sandboxed runtime access.

This gives your agent a consistent way to pull in the right context for a task, using the same isolated execution model that powers filesystem-based context retrieval.

This allows giving your agent access to the wide variety of publicly available skills, or for you to write your own proprietary skills and privately use them in your agent.

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import {
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  experimental_createSkillTool as createSkillTool,
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  createBashTool,
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} from "bash-tool";
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import { ToolLoopAgent } from "ai";
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// Discover skills and get files to upload
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const { skill, files, instructions } = await createSkillTool({
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  skillsDirectory: "./skills",
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});
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// Create bash tool with skill files
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const { tools } = await createBashTool({
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  files,
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  extraInstructions: instructions,
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});
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// Use both tools with an agent
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const agent = new ToolLoopAgent({
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  model,
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  tools: { skill, ...tools },
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});

Read the bash-tool changelog for background and check out createSkillTool documentation.

You can now apply suggested code fixes from the Vercel Agent directly in the Vercel Dashboard.

When the Vercel Agent reviews your pull request, suggestions include a View suggestion button that lets you commit the fix to your PR branch, including changes that touch multiple files.

Suggestions open in the dashboard, where you can accept them in bulk or apply them one by one.

After you apply a suggestion, the review thread is automatically resolved. You can also track multiple concurrent Vercel Agent jobs from the Tasks page.

Get started with Vercel Agent code review in the Agent dashboard, or learn more in the documentation.

Montréal, Canada (yul1) is now part of Vercel’s global delivery network, expanding our footprint to deliver lower latency and improved performance for users in Central Canada.

The new Montréal region extends our globally distributed CDN’s caching and compute closer to end users, reducing latency without any changes required from developers. Montréal is generally available and handling production traffic.

Teams can configure Montréal as an execution region for Vercel Functions, powered by Fluid compute to enhance resource efficiency, minimize cold starts, and scale automatically with demand.

Teams with Canadian data residency requirements can also use Montréal to keep execution in Canada.

Learn more about Vercel Regions and Montréal regional pricing

We released skills, a CLI for installing and managing skill packages for agents.

Install a skill package with npx skills add <package>.

So far, skills has been used to install skills on: amp, antigravity, claude-code, clawdbot, codex, cursor, droid, gemini, gemini-cli, github-copilot, goose, kilo, kiro-cli, opencode, roo, trae, and windsurf.

Today we’re also introducing skills.sh, a directory and leaderboard for skill packages.

Use it to:

• discover new skills to enhance your agents

• browse skills by category and popularity

• track usage stats and installs across the ecosystem

Get started with npx skills add vercel-labs/agent-skills and explore skills.sh.

Cron jobs on Vercel no longer have per-team limits, and per-project limits were lifted to 100 on all plans.

Previously, all plans had a cap of 20 cron jobs per project, with per-team limits of 2 for Hobby, 40 for Pro, and 100 for Enterprise.

To get started, add cron entries to vercel.json:

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{
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  "crons": [
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    {
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      "path": "/api/send-slack-notification",
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      "schedule": "*/10 * * * *"
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    },
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    {
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      "path": "/api/daily-backup",
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      "schedule": "0 2 * * * *"
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    },
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    {
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      "path": "/api/hourly-onboarding-emails",
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      "schedule": "0 * * * *"
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    }
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  ]
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}

You can also deploy the Vercel Cron Job template.

Once you deploy, Vercel automatically registers your cron jobs. Learn more in the Cron Jobs documentation.

Recraft models are now available via Vercel's AI Gateway with no other provider accounts required. You can access Recraft's image models, V3 and V2.

These image models excel at photorealism, accurate text rendering, and complex prompt following. V3 supports long multi-word text generation with precise positioning, anatomical correctness, and native vector output. It includes 20+ specialized styles from realistic portraits to pixel art.

To use this model, set model to recraft/recraft-v3 in the AI SDK. This model supports generateImage.

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import { generateImage } from 'ai';
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const result = await generateImage({
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  model: 'recraft/recraft-v3',
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  prompt:
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    `A misty Japanese forest with ancient cedar trees, painted in the style of
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     traditional ukiyo-e woodblock prints with soft indigo and moss green tones.`,
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});

AI Gateway provides a unified API for calling models, tracking usage and cost, and configuring retries, failover, and performance optimizations for higher-than-provider uptime. It includes built-in observability, Bring Your Own Key support, and intelligent provider routing with automatic retries.

Learn more about AI Gateway, view the AI Gateway model leaderboard or try it in our model playground.