• Vercel Sandboxes are now generally available

    Vercel Sandboxes are now generally available, providing an ephemeral compute primitive for safely executing untrusted code.

    It lets teams run AI agent-generated outputs, unverified user uploads, and third-party code without exposing production systems.

    Each sandbox runs inside Firecracker microVMs, isolated from your infrastructure, so code running in a sandbox is blocked from accessing environment variables, database connections, and cloud resources.

    Sandboxes are in production use by teams including v0, Blackbox AI and RooCode.

    To bootstrap a simple Node.js application that creates a Vercel sandbox, use the code below:

    import { Sandbox } from '@vercel/sandbox';
    const sandbox = await Sandbox.create();
    await sandbox.runCommand({
    cmd: 'node',
    args: ["-e", 'console.log("Hello from Vercel Sandbox!")'],
    stdout: process.stdout,
    });
    await sandbox.stop();

    Or get started with the CLI by opening an interactive shell:

    npx sandbox create --connect

    Explore the documentation to get started, and check out the open-source SDK and CLI.

  • cubic joins the Vercel Agents Marketplace

    Cubic-darkCubic-dark

    The Vercel Agents Marketplace now includes cubic, an AI code reviewer that that deploys thousands of AI agents to find and fix bugs in your PRs and codebase.

    Most code review tools only see what changed. cubic sees how those changes connect to everything else. It learns from your team’s past reviews and gets better over time.

    Key capabilities include:

    • Catching bugs, regressions, and security vulnerabilities in PRs and existing codebases; continuously running 1000s of agents

    • Identifies senior engineers on your team and learns from their comment history

    • Applying fixes automatically through background agents

    With cubic handling the first pass, teams spend less time on manual review and more time merging changes. Custom coding standards get enforced across repositories, helping keep code consistent as teams scale.

    Get started with cubic or explore the Vercel Agents Marketplace to discover more tools.

    Marketplace Team

  • Assistloop joins the Vercel Agents Marketplace

    Assist-darkAssist-dark

    AssistLoop is now available in the Vercel Marketplace as an AI-powered customer support integration.

    The integration connects natively with Vercel, so adding AI-driven customer support takes minutes. With AssistLoop, teams can:

    • Install AssistLoop with minimal setup using an Agent ID

    • Add AI-powered support directly to Next.js apps

    • Train agents on internal docs, FAQs, or knowledge bases

    • Customize the assistant to match your brand

    • Review conversations and hand off to human support when needed

    This integration fits naturally into existing Vercel workflows, with unified billing, automatic environment variables, and no manual configuration. Teams can ship AI-powered support faster without managing separate dashboards or complex setup.

    AssistLoop automatically injects NEXT_PUBLIC_ASSISTLOOP_AGENT_ID into your project environment. Add the widget script to your site:

    widget.tsx
    import Script from 'next/script'
    <Script
    src="https://assistloop.ai/assistloop-widget.js"
    strategy="afterInteractive"
    onLoad={() => {
    window.AssistLoopWidget?.init({
    agentId: process.env.NEXT_PUBLIC_ASSISTLOOP_AGENT_ID,
    });
    }}
    />

    AssistLoop automatically injects NEXT_PUBLIC_ASSISTLOOP_AGENT_ID into your project environment. Just add the widget script to your site:

    Link to headingGet started

    Deploy the AssistLoop Next.js template from the Marketplace to see it in action.

    Marketplace Team

  • Skew Protection now supports prebuilt deployments

    Skew Protection can now be used with vercel deploy --prebuilt deployments.

    For teams building locally and uploading with --prebuilt, you can now set a custom deploymentId in your next.config.js:

    next.config.js
    module.exports = {
    deploymentId: process.env.GIT_SHA || 'my-deployment-id',
    }

    This ID is written to routes-manifest.json and used by Vercel for skew protection routing. You control the ID lifecycle, using the same ID across multiple prebuilt deployments or updating it when deploying new versions.

    This feature enables Skew Protection support for the specific workflow of building applications locally and then uploading them to Vercel.

    Learn more about Skew Protection.

    Brooke Mosby

  • Vercel Agent investigations now available in Slack

    Anomaly alerts proactively monitor your application for usage or error anomalies. When we detect an issue, we send an alert by email, Slack or webhook. Vercel Agent investigates anomaly alerts to find out what's happening in your logs and metrics to help you identify the root cause.

    With our updated Slack integration, investigations now appear directly in Slack alert messages as a threaded response. This eliminates the need to click into the Vercel dashboard and gives you context to triage the alert directly in Slack.

    This feature is available for teams using Observability Plus. 10 investigations are included at no additional cost for Observability Plus subscribers.

    Learn more about Vercel Agent investigations.

    +2

    Julia S, Fabio B, Timo L, Malavika T

  • Tag-based cache invalidation now available for all responses

    Vercel's CDN now supports tag-based cache invalidation, giving you granular control over cached content across all frameworks and backends.

    Responses can now be tagged using the Vercel-Cache-Tag header with a comma-separated list of tags as a new cache organization mechanism to group related content and invalidate it together, rather than just purging your entire cache when content changes.

    This complements existing headers that cache responses on Vercel's CDN, like Cache-Control, CDN-Cache-Control, and Vercel-CDN-Cache-Control and exposes the same underlying technology that powers Next.js Incremental Static Regeneration (ISR) to any framework or backend.

    We recommend Next.js applications continue using Incremental Static Regeneration (ISR) for built-in cache tagging and invalidation without managing cache headers manually.

    Link to headingHow it works

    After a response has a cache tag, you can invalidate it through dashboard settings, the Vercel CLI, the Function API, or the REST API.

    Vercel's CDN reads Vercel-Cache-Tag and strips it before sending the response to the client. If you apply cache tags via rewrites from a parent to a child project, and both projects belong to the same team, cached responses on the parent project also include the corresponding tags from the child project.

    This is available starting today on all plans at no additional cost. Read the cache invalidation documentation to learn more.

  • Introducing the vercel api CLI command

    vercel@50.5.1 adds a new api command, giving direct access to the full suite of Vercel APIs from your terminal.

    The api command provides a direct access point for AI agents to interact with Vercel through the CLI. Agents like Claude Code can access Vercel directly with no additional configuration required. If an agent has access to the environment and the Vercel CLI, it inherits the user's access permissions automatically.

    List available APIs with vercel api ls, build requests interactively with vercel api, or send requests directly with vercel api [endpoint] [options].

    Get started with npx vercel@latest api --help.

  • Trinity Large Preview is on AI Gateway

    You can now access Trinity Large Preview via AI Gateway with no other provider accounts required.

    Trinity Large Preview is optimized for reasoning-intensive workloads, including math, coding tasks, and complex multi-step agent workflows. It is designed to handle extended multi-turn interactions efficiently while maintaining high inference throughput.

    To use this model, set model to arcee-ai/trinity-large-preview in the AI SDK:

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    const result = streamText({
    model: 'arcee-ai/trinity-large-preview',
    prompt:
    `Implement a long-context reasoning benchmark with ingested documents,
    multi-step analysis, and generate conclusions.`
    })β€‹β€‹β€‹β€‹β€Œο»Ώβ€ο»Ώβ€‹β€β€‹β€β€Œβ€ο»Ώο»Ώβ€Œο»Ώβ€‹β€β€Œβ€β€β€Œβ€Œβ€β€Œο»Ώβ€Œβ€β€β€Œβ€Œβ€ο»Ώβ€β€‹β€β€‹β€β€‹ο»Ώβ€β€β€‹β€β€‹β€β€Œβ€β€‹ο»Ώβ€Œβ€ο»Ώο»Ώβ€Œβ€ο»Ώβ€β€Œο»Ώβ€Œβ€‹β€Œβ€β€Œβ€Œβ€Œβ€ο»Ώβ€β€Œο»Ώβ€Œβ€‹β€Œβ€β€Œβ€β€Œο»Ώβ€Œβ€Œβ€Œβ€ο»Ώβ€‹β€‹β€ο»Ώβ€β€Œβ€β€‹ο»Ώβ€Œβ€ο»Ώο»Ώβ€Œβ€ο»Ώβ€Œβ€‹β€β€‹β€β€‹β€ο»Ώβ€‹β€‹β€β€‹β€β€Œβ€β€β€‹β€Œο»Ώβ€‹β€β€Œβ€β€Œβ€Œβ€Œβ€β€Œβ€β€‹β€β€‹β€β€‹ο»Ώβ€β€β€‹β€β€‹β€β€Œβ€β€β€‹β€Œο»Ώβ€Œβ€‹β€Œο»Ώβ€Œβ€‹β€Œο»Ώβ€‹β€‹β€Œο»Ώβ€‹ο»Ώβ€‹ο»Ώβ€β€β€‹β€ο»Ώο»Ώβ€‹β€ο»Ώο»Ώβ€Œβ€β€‹β€Œβ€Œο»Ώβ€‹β€‹β€Œο»Ώβ€‹β€‹β€‹β€ο»Ώβ€β€Œβ€β€‹ο»Ώβ€Œβ€ο»Ώο»Ώβ€Œβ€ο»Ώβ€β€Œο»Ώβ€Œβ€‹β€Œβ€β€Œβ€Œβ€Œβ€ο»Ώβ€β€Œο»Ώβ€Œβ€‹β€Œβ€β€Œβ€β€Œο»Ώβ€Œβ€Œβ€Œβ€ο»Ώβ€‹β€‹β€ο»Ώβ€β€Œβ€β€‹ο»Ώβ€Œβ€ο»Ώο»Ώβ€Œβ€ο»Ώβ€Œβ€‹β€ο»Ώο»Ώβ€Œο»Ώβ€‹ο»Ώβ€Œο»Ώβ€‹β€‹β€Œβ€β€‹β€Œβ€Œβ€β€‹ο»Ώβ€Œβ€β€Œβ€Œβ€Œο»Ώβ€‹ο»Ώβ€‹β€ο»Ώο»Ώβ€Œβ€β€Œβ€Œβ€‹ο»Ώβ€Œβ€Œβ€‹ο»Ώβ€‹ο»Ώβ€‹ο»Ώβ€β€‹β€‹ο»Ώβ€‹β€β€Œβ€β€β€‹β€Œβ€β€‹ο»Ώβ€Œο»Ώβ€Œβ€‹β€‹ο»Ώβ€Œο»Ώβ€‹ο»Ώβ€Œβ€‹β€Œο»Ώβ€‹ο»Ώβ€Œβ€β€β€Œβ€‹β€ο»Ώο»Ώβ€Œβ€β€Œβ€Œβ€Œβ€ο»Ώβ€β€Œο»Ώβ€Œβ€β€Œβ€β€β€Œβ€Œο»Ώβ€‹β€β€Œβ€ο»Ώο»Ώβ€Œβ€ο»Ώβ€β€Œβ€ο»Ώβ€Œβ€Œβ€β€Œβ€Œβ€Œβ€ο»Ώβ€β€Œο»Ώβ€Œβ€‹β€Œο»Ώβ€‹ο»Ώβ€‹β€ο»Ώο»Ώβ€Œβ€ο»Ώβ€Œβ€Œβ€β€‹β€Œβ€Œο»Ώβ€‹ο»Ώβ€Œο»Ώβ€Œβ€‹β€Œβ€β€Œβ€Œβ€Œο»Ώβ€‹β€β€‹β€ο»Ώο»Ώβ€Œβ€β€Œβ€Œβ€Œβ€ο»Ώβ€β€Œο»Ώβ€Œβ€‹β€Œο»Ώβ€‹β€β€Œβ€β€β€Œβ€Œβ€β€Œβ€Œβ€Œο»Ώβ€‹ο»Ώβ€‹β€ο»Ώο»Ώβ€‹ο»Ώβ€Œβ€Œβ€Œο»Ώβ€‹β€β€Œβ€Œβ€Œβ€Œβ€Œβ€Œβ€‹β€β€Œβ€‹β€‹β€β€Œβ€‹β€Œβ€β€Œβ€Œβ€β€‹β€Œβ€Œβ€Œο»Ώβ€Œβ€‹β€β€β€Œο»Ώβ€Œβ€Œβ€Œβ€Œβ€Œβ€β€Œβ€Œβ€β€Œβ€Œβ€ο»Ώβ€β€‹ο»Ώβ€‹ο»Ώβ€Œο»Ώβ€Œβ€‹β€Œβ€β€β€‹β€Œβ€‹ο»Ώο»Ώβ€Œβ€‹β€Œβ€β€Œβ€Œβ€β€β€Œβ€β€Œο»Ώβ€Œο»Ώβ€‹β€β€Œβ€‹β€Œβ€Œβ€‹β€ο»Ώο»Ώβ€‹ο»Ώο»Ώο»Ώβ€Œβ€β€Œβ€β€Œβ€ο»Ώο»Ώβ€Œβ€β€‹ο»Ώβ€Œο»Ώβ€Œβ€Œβ€Œο»Ώβ€‹ο»Ώβ€Œβ€β€Œβ€Œβ€Œβ€β€Œβ€‹β€Œβ€‹β€Œβ€β€Œβ€β€β€Œβ€Œβ€β€Œβ€Œβ€Œβ€ο»Ώβ€‹β€Œβ€β€Œβ€‹β€‹ο»Ώο»Ώβ€Œβ€Œβ€β€‹ο»Ώβ€Œβ€ο»Ώο»Ώβ€Œβ€ο»Ώβ€β€Œο»Ώβ€Œβ€‹β€Œβ€β€Œβ€Œβ€Œβ€ο»Ώβ€β€Œο»Ώβ€Œβ€‹β€‹β€β€Œβ€β€Œβ€β€Œβ€β€Œβ€ο»Ώο»Ώβ€Œβ€β€‹ο»Ώβ€Œο»Ώβ€Œβ€Œβ€Œο»Ώβ€‹ο»Ώβ€Œβ€β€Œβ€Œβ€Œβ€β€Œβ€‹β€Œβ€‹ο»Ώβ€‹β€Œβ€ο»Ώο»Ώβ€Œβ€β€‹ο»Ώβ€Œβ€β€‹β€Œβ€Œβ€ο»Ώβ€‹β€Œβ€β€Œβ€Œβ€‹ο»Ώο»Ώβ€Œβ€Œβ€β€Œβ€Œβ€Œβ€ο»Ώβ€β€‹β€ο»Ώβ€Œβ€Œβ€Œβ€Œβ€Œβ€Œβ€Œβ€‹ο»Ώβ€‹β€β€Œβ€β€Œο»Ώβ€‹ο»Ώβ€Œβ€ο»Ώο»Ώβ€Œο»Ώβ€Œβ€Œβ€Œο»Ώβ€‹β€β€Œβ€β€‹ο»Ώβ€Œβ€β€Œβ€Œβ€‹ο»Ώο»Ώβ€Œβ€Œο»Ώβ€Œβ€β€Œβ€β€Œβ€Œβ€Œο»Ώβ€‹β€β€Œβ€β€‹ο»Ώβ€Œβ€β€Œβ€Œβ€Œβ€ο»Ώβ€‹β€‹β€ο»Ώβ€Œβ€Œβ€β€‹ο»Ώβ€Œβ€ο»Ώο»Ώβ€Œβ€ο»Ώβ€β€Œο»Ώβ€Œβ€‹β€Œβ€β€Œβ€Œβ€Œβ€ο»Ώβ€β€Œο»Ώβ€Œβ€‹β€‹β€ο»Ώβ€Œβ€Œβ€ο»Ώβ€‹β€Œβ€β€β€Œβ€Œβ€ο»Ώβ€β€Œβ€β€ο»Ώβ€‹β€β€‹β€β€‹β€ο»Ώβ€‹β€‹β€β€‹β€β€Œβ€β€‹ο»Ώβ€Œβ€ο»Ώο»Ώβ€Œβ€ο»Ώβ€β€Œο»Ώβ€Œβ€‹β€Œβ€β€Œβ€Œβ€Œβ€ο»Ώβ€β€Œο»Ώβ€Œβ€‹β€Œβ€β€Œβ€β€Œο»Ώβ€Œβ€Œβ€Œβ€ο»Ώβ€‹β€‹β€β€‹β€β€‹ο»Ώβ€β€β€Œο»Ώβ€ο»Ώβ€‹β€β€‹β€β€Œβ€β€Œβ€Œβ€Œβ€β€Œβ€‹β€Œβ€β€β€Œβ€Œο»Ώβ€Œβ€‹β€Œβ€ο»Ώο»Ώβ€Œο»Ώβ€‹β€β€Œβ€‹β€β€Œβ€Œβ€ο»Ώβ€β€Œο»Ώβ€Œβ€‹β€Œβ€β€Œβ€Œβ€Œο»Ώβ€‹β€β€Œβ€β€Œβ€β€Œβ€β€‹β€Œβ€Œβ€β€‹ο»Ώβ€Œβ€β€Œβ€Œβ€‹β€β€‹β€β€‹ο»Ώβ€β€β€Œο»Ώβ€ο»Ώβ€‹β€β€‹β€β€Œο»Ώβ€Œο»Ώβ€Œβ€β€β€Œβ€Œβ€β€Œβ€‹β€Œβ€β€Œο»Ώβ€Œβ€β€Œβ€Œβ€Œο»Ώβ€Œβ€‹β€Œβ€‹β€β€Œβ€Œβ€β€Œβ€‹β€‹β€β€‹β€β€‹ο»Ώβ€β€β€‹β€β€‹β€β€Œο»Ώβ€‹β€β€Œβ€β€β€Œβ€Œβ€β€‹ο»Ώβ€Œβ€β€β€‹β€Œβ€Œβ€Œβ€‹β€Œβ€β€Œβ€Œβ€Œο»Ώβ€β€‹β€Œο»Ώβ€Œβ€‹β€Œβ€‹β€Œβ€Œβ€Œβ€β€Œβ€‹β€Œβ€β€β€Œβ€Œο»Ώβ€Œβ€‹β€Œβ€ο»Ώο»Ώβ€Œο»Ώβ€‹β€β€‹β€β€‹β€β€‹β€ο»Ώβ€‹β€‹β€β€‹β€β€Œο»Ώβ€Œο»Ώβ€Œβ€β€β€Œβ€Œβ€β€Œβ€‹β€Œβ€β€Œο»Ώβ€Œβ€β€Œβ€Œβ€Œο»Ώβ€Œβ€‹β€Œβ€‹ο»Ώβ€β€Œβ€β€‹β€Œβ€Œβ€ο»Ώβ€Œβ€Œβ€β€Œβ€Œβ€Œο»Ώβ€‹ο»Ώβ€Œο»Ώβ€‹β€‹β€Œβ€β€‹β€Œβ€Œβ€β€‹ο»Ώβ€Œβ€β€Œβ€Œβ€‹β€β€‹β€β€‹ο»Ώβ€β€β€‹β€β€‹β€β€Œβ€β€‹β€β€Œο»Ώβ€Œβ€Œβ€Œβ€β€β€Œβ€Œβ€ο»Ώβ€‹β€Œο»Ώβ€Œβ€‹β€Œβ€β€β€Œβ€Œβ€ο»Ώβ€β€‹β€β€‹β€β€Œο»Ώο»Ώβ€Œβ€‹β€ο»Ώβ€‹β€‹β€β€‹β€β€Œβ€β€Œβ€β€Œβ€β€β€Œβ€Œβ€β€Œβ€Œβ€Œβ€ο»Ώβ€‹β€Œβ€β€Œβ€‹β€Œβ€Œβ€Œβ€‹β€Œο»Ώβ€β€Œβ€Œο»Ώβ€‹β€‹β€Œβ€β€Œβ€Œβ€‹β€β€‹β€β€‹ο»Ώβ€β€β€‹β€β€‹β€β€Œβ€Œβ€‹β€β€Œβ€β€β€Œβ€Œβ€β€‹ο»Ώβ€Œβ€β€β€‹β€Œβ€Œβ€Œβ€‹β€Œβ€β€Œβ€Œβ€Œο»Ώβ€β€‹β€Œο»Ώβ€Œβ€‹β€‹β€β€‹β€β€Œο»Ώο»Ώβ€Œβ€Œο»Ώο»Ώβ€Œ

    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.