Netlify Release Notes

Agent Runners are now better at completing their work when a run has less credits remaining than the task requires. If you are close to running our of credits during a run, the agent will start focusing on delivering the most useful result it can with the credits it has left. It finishes work already in progress, leaves the project in a working state, and provides a clear summary of what it completed. Previously, an ambitious task could end abruptly before the agent wrapped up, leaving partial changes and little explanation. Now, you’re more likely to get a working result you can use right away, or a solid, clearly documented starting point for your next run. This improvement applies automatically to every agent and model available in Agent Runners. There’s nothing to enable or configure. Learn more in Make changes with Agent Runners and how credits work.

You can now connect repositories hosted on Cursor Origin to Netlify, so every Git push deploys an updated version of your project at a preview URL or a production URL. Netlify supports Cursor Origin with continuous deployment, meaning that once your codebase’s repo is connected, Netlify will automatically:

• Build and deploy your project with every git push
• Build Deploy Previews for your pull requests
• Send deploy notifications to your pull request comments on Cursor Origin so you can check preview URLs there

Requirements Cursor Origin uses OAuth authentication, so connecting a repo works much like our existing Azure DevOps support: the Cursor user who authenticates needs access to the Cursor Origin codebase that owns the repository. To use Cursor Origin with Netlify, you do not need a specific pricing plan with Netlify. Support scope Note that features outside of continuous deployment, such as Agent Runners and the Netlify Drawer, are not supported at this time. Get started To learn more, check out these docs:

• Get started Cursor Origin
• Link your repo to your Netlify project
• Deploy a new project to Netlify from your Cursor Origin repo

OpenAI’s ChatGPT Images 2.5 models are now available through Netlify’s AI Gateway and Agent Runners with zero configuration required. Use gpt-image-2.5-flare or gpt-image-2.5-sunburst to generate images for your applications. Use the OpenAI SDK directly in your Netlify Functions without managing API keys or authentication. AI Gateway handles everything automatically. Here’s an example using the gpt-image-2.5-flare model: import OpenAI from 'openai'; const ai = new OpenAI(); export default async (req, context) => { const response = await ai.images.generate({ model: 'gpt-image-2.5-flare', prompt: 'A golden retriever working at a laptop in a sunny startup office', size: '1024x1024', quality: 'low', output_format: 'jpeg', output_compression: 80 }); const imageBuffer = Buffer.from(response.data[0].b64_json, 'base64'); return new Response(imageBuffer, { status: 200, headers: { 'content-type': 'image/jpeg', 'cache-control': 'no-store' } }); }; Both ChatGPT Images 2.5 models are available across standard Functions, Background Functions, Scheduled Functions, Edge Functions, and Agent Runners. You get automatic access to Netlify’s caching, rate limiting, and authentication infrastructure. Learn more in the AI Gateway documentation and Agent Runners documentation.

OpenAI’s GPT-6 Astra model is now available through Netlify’s AI Gateway and Agent Runners with zero configuration required. Use the OpenAI SDK directly in your Netlify Functions without managing API keys or authentication. AI Gateway handles everything automatically. Here’s an example using GPT-6 Astra with the Responses API: import OpenAI from 'openai'; export default async () => { const openai = new OpenAI(); const response = await openai.responses.create({ model: 'gpt-6-astra', input: 'Give a concise explanation of how AI works.', }); return Response.json(response); }; GPT-6 Astra is also available across Background Functions, Scheduled Functions, and Edge Functions. You get automatic access to Netlify’s caching, rate limiting, and authentication infrastructure. Learn more in the AI Gateway documentation and Agent Runners documentation.

Google’s Gemini 3.8 Flash model is now available through Netlify’s AI Gateway and Agent Runners with zero configuration required. Use the Google GenAI SDK directly in your Netlify Functions without managing API keys or authentication. The AI Gateway handles everything automatically. Here’s an example using the Gemini 3.8 Flash model: import { GoogleGenAI } from '@google/genai'; export default async () => { const ai = new GoogleGenAI({}); const response = await ai.models.generateContent({ model: 'gemini-3.8-flash', contents: 'How can AI improve my coding?' }); return Response.json(response); }; Gemini 3.8 Flash is available for all Function types and Agent Runners. You get automatic access to Netlify’s caching, rate limiting, and authentication infrastructure. Learn more in the AI Gateway documentation and Agent Runners documentation.

Anthropic’s Claude Fable 5.1 model is now available through Netlify’s AI Gateway and Agent Runners with zero configuration required. Use the Anthropic SDK directly in your Netlify Functions without managing API keys or authentication. The AI Gateway handles everything automatically. Here’s an example using the Claude Fable 5.1 model: import Anthropic from '@anthropic-ai/sdk'; export default async () => { const anthropic = new Anthropic(); const response = await anthropic.messages.create({ model: 'claude-fable-5-1', max_tokens: 4096, messages: [ { role: 'user', content: 'How can AI improve my coding?' } ] }); return new Response(JSON.stringify(response), { headers: { 'Content-Type': 'application/json' } }); }; Claude Fable 5.1 is available for all Function types and Agent Runners. You get automatic access to Netlify’s caching, rate limiting, and authentication infrastructure. Learn more in the AI Gateway documentation and Agent Runners documentation.

Netlify now creates a Deploy Preview for every pull request in a GitHub stack when the stack ultimately targets your project’s production branch (usually main). You can review and share each layer of a larger change before it merges. A GitHub stacked pull request showing a successful Netlify Deploy Preview check GitHub Stacked Pull Requests help teams split a larger update into smaller, connected pull requests. Each pull request can focus on one step of the work, making changes easier to review and merge in sequence. Previously, Netlify only created a Deploy Preview for the first pull request in your stack while additional pull requests in the stack didn't get their own Deploy Previews. Now, every pull request in the stack gets its own Deploy Preview. There’s nothing new to configure. Create and update your stack in GitHub as usual, and Netlify automatically adds a Deploy Preview to each eligible pull request. Learn More

• Get an overview of GitHub Stacked Pull Requests
• Follow GitHub’s quick start for creating a stack

Agent Runners can now ask you clarifying questions before they start building. When a few details could significantly improve the result, the agent pauses and asks instead of guessing. The clarifying questions UI in an Agent Runners session, asking: What should the tracker dashboard keep track of? How clarifying questions work Say you start with something broad, like “Build a tracker dashboard.” Previously the agent had to make every call for you: what the dashboard should track, whether entries should be editable and saved to a database or live in the code as a read-only placeholder, whether the look should be dark and high-contrast or light, clean, and editorial. Now it can ask, and you can answer directly where the agent run works. Answer, skip, or add your own context Answering questions is always optional so you can answer the ones you have opinions about and skip the rest. Or you can skip all questions and let the agent decide. Finally, you can always add context in your own words alongside your answers. In our testing, even a few quick answers make the first build noticeably sharper and saves credits you’d otherwise spend on course corrections. Once you answer, the run continues as usual: the agent writes the code, works with Netlify’s platform features, and creates a Deploy Preview you can review and iterate on. Learn more Clarifying questions work with every agent and model available in Agent Runners. Try it out and see how to use Agent Runners in our docs.

Private projects on Netlify will now show a pre-launch toolbar so you can share your project for review and run audits using AI checks before you make your project public. Private projects and agent runs require a Credit pricing plan. If you're on a Legacy pricing plan, you will not have access to the pre-launch toolbar. Audits consume credits like any other agent run. For public projects, new projects created on a Free plan on or after August 19, 2026 show a Powered by Netlify badge to all visitors. The badge is configurable for each project through your project configuration settings. To turn the Netlify badge on or off for all visitors of your site:

1. Go to Project configuration > General > Powered by Netlify badge and turn it on or off.

Additionally, any visitor can hide the badge for themselves, and that choice is stored locally on their browser and never reaches Netlify. All projects created before August 19, 2026 have the badge off by default. Users on a Credit-based Personal and Pro plans can also turn the badge on or off per-project. For these plans, the badge is always off by default. Release timeline We’re rolling both overlays out gradually over the next few weeks, so a project that qualifies may not have them yet. Learn more about the pre-launch toolbar and the Powered by Netlify badge in the Netlify documentation.

Google’s Gemini 3.7 Flash model is now available through Netlify’s AI Gateway and Agent Runners with zero configuration required. Use the Google GenAI SDK directly in your Netlify Functions without managing API keys or authentication. The AI Gateway handles everything automatically. Here’s an example using the Gemini 3.7 Flash model: import { GoogleGenAI } from '@google/genai'; export default async () => { const ai = new GoogleGenAI({}); const response = await ai.models.generateContent({ model: 'gemini-3.7-flash', contents: 'How can AI improve my coding?' }); return Response.json(response); }; Gemini 3.7 Flash is available for all Function types and Agent Runners. You get automatic access to Netlify’s caching, rate limiting, and authentication infrastructure. Learn more in the AI Gateway documentation and Agent Runners documentation.

Invitations to join an existing team now show up within your Netlify dashboard, where you can accept or decline them directly without checking your email inbox. Previously, the invitation email was the only way in. If it got buried, filtered, or sent to an address you no longer check, then getting collaboration started with your teammate took a lot longer than it needed to. Now, when you sign in to Netlify with an email address that has a pending invitation, you’ll see it waiting for you. Accept it and you’re on the team immediately. Decline it and it’s cleared out. Either way, you never have to go digging through your inbox. Nothing changes about how invitations are sent. Invitees still receive the same email they always have, and accepting from that link works exactly as before. This is simply a second, more reliable path to the same place. Learn more about inviting and managing teammates in Manage team members in the Netlify documentation.

If your team uses SSO (single sign-on) with an identity provider, you can now sign in with just your email address without using your team ID. Netlify recognizes your domain and sends you straight to your identity provider. Previously, SSO required you to know your Team ID. That meant every new hire had to know and enter a Team ID, and anyone who forgot or didn’t know it was stuck at the login screen. It was a small detail that quietly created support work for the people administering the team. Now the flow is simplified: enter your email, get redirected to whichever identity provider your team has configured, authenticate there, and land back in Netlify. This is live for every team using SSO with an identity provider that lets you use your email address to authenticate. This means your existing SAML setup already carries everything Netlify needs to route people to the right place. Learn more about configuring SAML SSO in the Netlify documentation.

The AI Gateway now supports OpenRouter, giving you access to models from providers beyond Netlify's direct integrations (OpenAI, Anthropic, Google Gemini). This partnership opens up models from providers like DeepSeek, Meta, Mistral, Qwen, and xAI, all billed through your existing Netlify credits. Learn more about our OpenRouter partnership through the Netlify blog on open models. Supported models For a full list of models available on OpenRouter, visit OpenRouter's models page. Note that Netlify only allows requests through OpenRouter for model providers that support a Zero Data Retention (ZDR) policy, meaning your prompts and outputs are never stored nor trained on. Models on OpenRouter that do not have any available provider guaranteeing this policy (at the time of your request) are not available via Netlify. Set up OpenRouter for AI Gateway As with the other providers, Netlify automatically injects OPENROUTER_API_KEY and OPENROUTER_BASE_URL into your Netlify Functions, Edge Functions, and Preview Server (unless you've already set your own values for either). You can call an OpenRouter-served model using whichever client you prefer:

• OpenRouter SDK (@openrouter/sdk): pass OPENROUTER_BASE_URL explicitly as serverURL when constructing the client, this is the one exception where the base URL isn't picked up automatically.
• OpenAI SDK : works out of the box, no extra config. Just pass a model ID in OpenRouter notation (e.g. deepseek/deepseek-v4-flash-0731). …

Through a new partnership with OpenRouter, you can now choose OpenCode as an AI agent with Agent Runners. OpenCode allows you to choose many different AI models, including Kimi, DeepSeek, and GLM. Learn more about our OpenRouter partnership through the Netlify blog on open models. Previously, you could only choose Claude, Gemini, or Codex as your AI agent, but now you can choose the OpenCode agent, which offers even more models from different AI providers. Requests made through OpenCode are only routed to model providers with a Zero Data Retention (ZDR) policy, so your prompts and outputs are never stored. AI model selection As part of this release, you can now also specify which model any agent uses with Agent Runners. Previously, Claude, Gemini, and Codex agents all automatically chose a model for the task you prompted with Agent Runners. Agents can still auto-select a model for you, but now you can also choose different models for your agents, with these preferences saved just for you on your device. This means you can experiment with which AI models best fit your needs. To open your AI model options for Agent Runners, select agent near your prompt box. Choosing the best AI model for your needs To help you choose the best AI model for your needs, within Agent Runners you can browse details about each model, including a link to learn more, a visual way to compare cost across all supported models with a 1-5 dot scale, and the option to set an effort level for that model. To…

SolidStart 2 is out, and it deploys to Netlify with no framework-specific adapter to install, a first for full-stack frameworks on Netlify. While SolidStart 1 deployed to Netlify through Nitro under the hood, SolidStart 2 no longer includes Nitro, building directly on Vite’s Environment API instead. The Netlify Vite plugin can now take the server build Vite produces and prepare it for deployment on its own, with no SolidStart-specific Netlify adapter needed in between. How to deploy Install the Netlify Vite plugin: npm install -D @netlify/vite-plugin Then add it to your Vite config with its build support turned on: // vite.config.ts import netlify from '@netlify/vite-plugin'; import { solidStart } from '@solidjs/start/config'; import { defineConfig } from 'vite'; export default defineConfig({ plugins: [solidStart(), netlify({ build: { enabled: true } })], }); That’s the whole setup for a new project. Netlify detects SolidStart and fills in your build settings, and your SSR pages, API routes, server functions, and middleware deploy to Netlify Functions. Prefer to build with Nitro? It became a Vite plugin in Nitro 3 and auto-detects Netlify, so adding nitro() works too. Just remove build.enabled from the Netlify Vite plugin. Either way, vite dev gives you the full Netlify platform emulated right in your dev server without reaching for the Netlify CLI. Already on SolidStart 1? Nothing breaks, and your Nitro netlify preset keeps working. When you’re ready to upgrade, follow the…

Netlify Agent Runners now have a mode selector. Pick Ask and the agent reads, investigates, and answers questions about your project. Build is still the default and works exactly as before. Ask mode is strictly read-only. The agent can’t edit files, run commands, deploy, or change settings. With no build or Deploy Preview, Ask runs are often faster and use fewer credits. It answers with real context: your repository, your project context, and your project’s Netlify Database. Your data is often the fastest way to answer a question about your app, and Ask mode can query it with no risk of a write. A few prompts to steal:

• “How many users are in the database?”
• “Walk me through how authentication is implemented in this project. Which files handle it, and where is the token stored?”
• “Our Largest Contentful Paint is bad on mobile. Read the code and tell me what's most likely responsible.”
• “Plan out how we can migrate to the latest version of Astro.”

Because it’s a mode on the same run, you can switch to Build the moment an answer turns into a task — same run, same context, no re-explaining. Ask mode is available on all agents, Claude Code, Google Gemini, and OpenAI Codex, in Agent Runners today. See the docs on Ask and Build modes.