Changelog

TypeSafe’s Jev model is now available through Netlify’s AI Gateway with zero configuration required.

Install @typesafe-ai/sdk and use it directly in your Netlify Functions — no API keys to create, no provider config, no base URLs to wire up. AI Gateway handles credentials automatically, and usage is billed to your Netlify credits like every other model in the gateway.

Jev is TypeSafe’s first “System One” model, and it works differently from the chat models you’re used to. Instead of generating prose, you send it your program state along with a set of typed questions, and it returns typed answers with calibrated probabilities. There are three question primitives: choice picks one option from a set, score rates against ordered levels, and noul returns a yes/no probability between 0 and 1. Answers are constrained to the options you declare, so there’s no JSON parsing or schema coercion on your end.

Every question in a request is evaluated in parallel against the same state, which means batching a dozen questions into one call costs little more than asking one. State and questions share a budget of roughly 32,000 tokens — about 150,000 characters of English text — and TypeSafe reports end-to-end response times of 70–500ms, making Jev a good fit for classification, routing, extraction, scoring, and guardrail checks on the request path. The SDK defaults to the jev-latest alias, currently jev-1.13.0, and requires Node.js 20 or newer.

Here’s a Function that routes an incoming contact form submission to sales, support, or spam:

import type { Config, Context } from "@netlify/functions";
import { choice, TypeSafeClient } from "@typesafe-ai/sdk";

export default async (req: Request, context: Context) => {
  const client = new TypeSafeClient();

  const { answers } = await client.systemOne({
    state: await req.json(),
    questions: {
      team: choice("Route this contact form submission", {
        sales: null,
        support: null,
        spam: null,
      }),
    },
  });

  return Response.json({
    team: answers.team.choice,
    requestId: context.requestId,
  });
};

export const config: Config = { path: "/api/route", method: "POST" };

The choice helper declares the three possible destinations up front, so answers.team.choice comes back as one of them and nothing else, which makes the response safe to branch on directly. Each answer also carries a probability distribution and a confidence value, so you can act on high-confidence decisions and escalate the rest to a human.

Learn more in the AI Gateway documentation and the TypeSafe documentation.

DeepSeek V4.1 Flash is now available through OpenRouter on Netlify’s AI Gateway with zero configuration required.

Use the OpenRouter SDK directly in your Netlify Functions without managing API keys or authentication. AI Gateway handles everything automatically. Here’s an example using DeepSeek V4.1 Flash:

import { OpenRouter } from '@openrouter/sdk';

export default async () => {
    const client = new OpenRouter();

    const response = await client.chat.send({
        chatRequest: {
            model: 'deepseek/deepseek-v4.1-flash',
            messages: [{ role: 'user', content: 'How can AI improve my coding?' }],
            maxTokens: 400,
        },
    });

    return Response.json(response);
};

DeepSeek V4.1 Flash is available across Background Functions, Scheduled Functions, and Edge Functions. You get automatic access to Netlify’s rate limiting and authentication infrastructure.

Learn more in the AI Gateway documentation and OpenRouter documentation.

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.

Sharing your Netlify projects is now faster with built-in social media share buttons.

When you’re ready to show off what you’ve built, you can share your project directly to X, LinkedIn, Reddit, Facebook, or Bluesky. Choose your preferred platform and Netlify opens a ready-to-publish post with your project link, so you can reach your community with fewer steps.

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.

Agent Runners can now scope ambitious prompts for new projects to create a partial working project and provide next steps within the available credit budget.

Previously, a brand new project could use up its credit budget before the agent finished for ambitious prompts, leaving the run marked Cancelled partway through.

Now, your agent scopes the work more intelligently. It builds out part of the project and shares a plan for next steps, so you can preview a working version within your new project credit budget instead of the run stalling out.

Learn more in Make changes with Agent Runners.

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.