OpenAI Release Notes

Workspace agents help teams get more done together across tools. They can own entire workflows on their own, follow team processes, and be shared across your team so people can build once and use together.

We’ve also added new admin controls and visibility:

• Agent builders can set safeguards on which actions agents can take for each app enabled in their workspace.
• Business, Enterprise, and Edu admins can view workspace agent activity and usage in the admin console.

We’ve extended the free period for workspace agents until July 6, 2026. Credit-based pricing will begin on that date.

Original source

Today we’re beginning to roll out a more capable and scalable system for synthesizing memory, developed to tackle the staleness, correctness, and scalability challenges that we observe when memory is applied to the hundreds of millions of users and multi-year time horizons in ChatGPT.

Memory is what helps ChatGPT learn your preferences, projects, and constraints, allowing future conversations to start from shared context rather than from scratch.

Over the last two years, memory has grown into a critical part of the ChatGPT experience, helping ChatGPT better understand your context so it can help you accomplish meaningful goals over time. This is central to making ChatGPT more useful: knowing you, helping you, and doing more for you.

This update is available to Plus and Pro users in the US today, and will roll out to additional countries and Free and Go users over the coming weeks.

How memory has evolved

Memory first launched in April 2024 (also known as saved memories). The feature let you ask ChatGPT to remember information and carry it forward into future chats.

Saved memories were only written during the conversation and relied on strong cues to decide when to trigger memory, such as an instruction to "remember I’m traveling to Singapore in July." In practice, interacting with this system could feel like talking to someone who took a few notes, but still forgot everything that wasn’t written down. Saved memories also tend to go stale over time and eventually become incorrect or irrelevant.

In April 2025, we updated ChatGPT’s memory by giving the model the ability to reference chat context outside of the saved memories list; this was done by introducing the first version of dreaming — a method for ChatGPT to automatically curate memories in the background by referencing chat history.

In contrast to saved memories, dreaming leverages a background process that allows ChatGPT to learn from many conversations and synthesize ChatGPT’s memory state in order to always provide the freshest, most relevant context to your conversations. Dreaming also makes it easier for memory to include context that occurs naturally in conversation, without relying on explicit requests to remember something.

Over the last year, dreaming supplemented saved memories to create a step-function improvement in ChatGPT's ability to personalize responses and offset the staleness of saved memories. However, it historically was never sufficient as a standalone memory system.

Today, we are launching a significantly more capable and compute-efficient memory architecture built on top of dreaming.

The memories synthesized by dreaming are reviewable through a summary of them made visible in the memory summary page. From the memory summary, you can quickly glean the highlights of what ChatGPT knows about you, add or update information about yourself, and provide instructions on what topics ChatGPT should bring up and when. If you want to drill down into a particular area to learn more, just chat with the model.

How we evaluate memory

When we think about what "good memory" looks like in ChatGPT, a few things come to mind:

1. Carry forward useful context: You tell ChatGPT something once, and it remembers that information in your subsequent chats.
2. Follow preferences and constraints: If you describe a preference (e.g., you’re vegetarian), then ChatGPT should take actions that are consistent with that preference going forward.
3. Stay current over time: Memory should account for the passage of time. Imagine "The user is planning their birthday party for next Saturday"; eventually, Sunday arrives.

We can evaluate how ChatGPT Plus and Pro memory has improved over time with respect to each of the three memory objectives above. We do this for each of:

1. 2024: Saved memories
2. 2025: Saved memories + Dreaming V0
3. 2026: Dreaming V3

Carrying forward context

When you start a new chat with ChatGPT, you don’t have to introduce yourself from scratch. ChatGPT can save you time and build on prior context, especially for complex, long-running projects.

For example, imagine you’re using ChatGPT to shop for new camera gear that's compatible with your current camera. If you've discussed your camera setup with ChatGPT in the past, you can ask for products that are compatible with "my photography setup" and get tailored recommendations that meet your needs.

The model produces a generic response that leaves the user to do complicated compatibility checks on their own.

The model remembers the user’s camera setup and recommends a compatible product.

We can construct an eval from examples that resemble this where the model is asked to respond to a prompt that requires it to recall factual information about the user. The model is then rewarded if it responds in a way that correctly uses the relevant context. In this evaluation, the new dreaming-based system improves the model's ability to recall relevant facts.

Following preferences

Memory also helps ChatGPT respond in ways that better match your preferences and constraints.

Imagine that you’re planning a trip to Singapore. Two months before your trip, you ask ChatGPT to help with an itinerary. ChatGPT already knows from past travel planning that you enjoy wildlife photography, prefer hotels with strong AC, and enjoy a quiet dinner over a crowded bar.

The model produces a generic response that is more touristy, doesn't help with hotel booking, and largely ignores the user's interests.

The model produces a response that is personalized to the user’s interests in wildlife photography, quiet dinners, and their priorities when booking a hotel.

Preferences can take several forms:

1. Instructions for how ChatGPT should respond ("don't bring up Stan again").
2. Your personal preferences or constraints ("I’m vegetarian").
3. Implicit preferences that shape what’s relevant to you ("I live near San Francisco" → local options should be tailored to this area).

In developing the new memory system, we improved ChatGPT’s ability to apply relevant preferences from past conversations. Following the "I’m vegetarian" example above, we can evaluate whether the model correctly leverages memory to produce vegetarian-friendly dining options when a vegetarian user asks for meal prep suggestions.

Staying current over time

Time doesn’t stop when your chat ends.

Traditional memory systems can become stale. For example, you tell ChatGPT "I’m in Singapore and need a dinner recommendation for tonight." Then, time passes, your trip ends, and you wonder why ChatGPT still thinks you’re in Singapore.

With dreaming, memories are automatically updated as time passes, allowing ChatGPT to revise its memory from "You’re going to Singapore in July" to "You went to Singapore in July 2026" when the trip ends. Then, when you’re back home, ChatGPT can again provide recommendations that are tailored to your home location and time zone.

The model thinks the user is still in Singapore.

The model provides responses that are relevant to the user’s home location.

In our memory evaluations, we measure whether ChatGPT can correctly respond to prompts where the passage of time materially affects the correct answer or recommendation. Dreaming provides a substantial lift in this area:

A more scalable foundation for the future

At OpenAI, our mission is to ensure that artificial general intelligence benefits all of humanity.

While dreaming-based memory has been available to Plus and Pro users for some time, we are only now able to offer Free users a version that meets our quality bar and is practical to serve at scale. Recent improvements reduced the compute required to serve dreaming to Free users by approximately 5x, making it possible to begin rolling out dreaming to Free users over the coming weeks and to increase memory capacity for Plus and Pro users.

Looking ahead, dreaming now provides us with a shared memory foundation for all users. This update represents our most capable memory system yet, and we’ll continue improving it.

To learn more about this release and memory user controls, visit our Memory FAQ.

Original source

We’ve upgraded memory so ChatGPT can better keep your context up to date, helping responses stay more relevant. This makes memory more useful by reducing stale or contradictory saved memories and helps ChatGPT better understand your preferences, goals, and ongoing work. You can review the memories that ChatGPT may use to personalize responses through sources or in your memory summary.

Memories are now updated automatically, with ChatGPT keeping track of the details it determines are most important so it can continue building on the context you’ve already shared. If you prefer to revert to the legacy saved memories system, go to Settings > Memory > Saved memories.

This update is rolling this out to Plus and Pro users in the US today. To access it on iOS or Android, update your ChatGPT app to the latest version. We’ll expand to Free and Go plans and additional countries over the next few weeks. Users will receive an in-product notice when the update becomes available to them. For Plus and Pro users, ChatGPT can also remember more useful context, with twice as much memory capacity.

Original source

Lockdown Mode is now available to all logged-in users across account types and workspaces. It is an optional opt-in advanced security setting that limits access to the web and external services to help reduce the risk of data exfiltration from prompt injection attacks.

When Lockdown Mode is on, ChatGPT restricts network-enabled capabilities such as live web browsing, deep research, agent mode, file downloads, and some web-derived image support. Personal users can turn it on from Settings > Security. Workspace admins can configure access for members through workspace settings and role-based access controls.

Learn more: Lockdown Mode

Original source

New features

• Added activity insights and share cards to the Profile section. You can review Codex usage highlights and save a profile card; sharing is available on consumer ChatGPT plans.

Performance improvements and bug fixes

• Improved Computer Use startup readiness and appshot error reporting.
• Fixed browser and review UI issues, including fullscreen browser composer controls, hex color swatches, terminal scrollbar alignment, and animated diff stat alignment.
• Expanded onboarding with more role choices so Codex can tailor first-run suggestions more accurately.
• Additional performance improvements and bug fixes.

Original source

Bringing greater intelligence grounded in real scientific workflows for the life sciences industry.

We’re introducing a new model update to our GPT‑Rosalind series purpose-built for life sciences research at enterprise scale. It combines GPT‑5.5’s agentic coding and tool-use capabilities with stronger model intelligence in core drug-discovery domains such as medicinal chemistry and genomics, while advancing performance across broader life sciences analysis, design, and experimental workflows.

Progress in life sciences depends on synthesizing data and evidence across scales and modalities: molecules, genes, pathways, and living systems. In our evaluations, the updated GPT‑Rosalind shows broad performance gains on research tasks from biology experts, complex medicinal chemistry queries, quantitative biology, and wet lab troubleshooting.

GPT‑Rosalind is now available in research preview to eligible organizations globally through our trusted-access deployment structure.

Improving performance on scientifically-valuable tasks

In order to measure and continuously improve the real-world impact of GPT‑Rosalind, we designed LifeSciBench, an externally expert-judged benchmark focused on foundational aspects in life sciences research. Unlike existing benchmarks that evaluate a single component of model performance or biological domain in isolation, LifeSciBench takes an end-to-end view of scientifically valuable work by drawing tasks from six workflow areas central to life sciences research: evidence handling, analysis, design and optimization, scientific reasoning, validation and operations, and translation and communication. We use this benchmark to align progress with the needs and realities of life sciences research.

GPT‑Rosalind leads performance across scientifically-valuable tasks identified by industry and academic experts.

Evidence Handling example and detailed candidate response with regulatory conclusion and rubric criteria & grades are included, highlighting key evaluation points and areas for improvement.

Stronger scientific reasoning

Medicinal chemistry

GPT‑Rosalind achieves industry-leading performance in medicinal chemistry, a field focused on turning molecules into useful drugs. We designed MedChemBench to reflect realistic medicinal chemistry workflows, evaluating multimodal chemical structure understanding; structure-activity relationship (SAR); prediction of drug potency, toxicity, and absorption, distribution, metabolism, excretion (ADME); multiparameter lead-optimization decision-making; and retrosynthesis. GPT‑Rosalind out-performs GPT‑5.5 at 27.5% vs. 25.1% on MedChemBench, while using 7.2% fewer tokens.

Genomics and quantitative biology

On GeneBench, our agentic evaluation on long horizon, end-to-end analysis in genomics and quantitative biology, GPT‑Rosalind uses 31% fewer tokens than GPT‑5.5 while achieving a higher accuracy of 21.6% vs. 20.4%. GeneBench assesses agentic performance on long-horizon quantitative tasks: based on realistic scientific data, can an agent plan valid analysis, QC, modeling, and corrections to arrive at decision-relative answers? Included problems span a variety of domains, including functional genomics, spatial transcriptomics, proteomics, epigenomics, and applied genetics.

Assisting real-world lab work

We introduce a new evaluation to test GPT‑Rosalind’s ability to help scientists conducting lab work in the real world. LabWorkBench tests the model's ability to link perturbations to experimental outcomes in real wet lab protocols used by scientists, for the purposes ranging from troubleshooting to optimization. The data used by LabWorkBench are proprietary and thus uncontaminated. GPT‑Rosalind scores 63.2% vs. GPT‑5.5 at 55.8%, while using 5.3% fewer tokens.

From reasoning to executed workflows

We built the Life Sciences Research and Life Sciences NGS Analysis plugins to extend the increased intelligence of GPT‑Rosalind with a practical execution layer for repeatable scientific workflows. Together, these plugins bring sourced evidence retrieval, biological interpretation, and bioinformatics execution into the same workspace, helping researchers connect external evidence with internal omics analyses while preserving artifacts and provenance. All users can now access both plugins through Codex. Qualified GPT‑Rosalind enterprise users can additionally use GPT‑Rosalind to power these plugins.

To better leverage Codex as a dynamic workbench for scientists, we added interactive viewers for biologically native file types. The initial set of sequence, alignment, and structure viewers are designed to keep scientists close to the evidence as GPT‑Rosalind reasons across a workflow and directly answer follow-up questions using the active viewer in-context.

The demo shows these capabilities in action, orchestrated by GPT‑Rosalind, following a scientist investigating a liquid tumor biopsy to identify mutations and molecular changes that could inform treatment.

Expanded access for trusted organizations

We are expanding access to the GPT‑Rosalind series to eligible organizations globally. GPT‑Rosalind will be available in research preview through our trusted-access deployment structure for organizations conducting legitimate scientific research with clear public benefit, strong governance and safety oversight, and controlled access with enterprise-grade security.

Novo Nordisk is leveraging frontier AI capabilities to help researchers analyze complex datasets, uncover useful patterns, and test hypotheses more quickly. GPT‑Rosalind’s stronger biological understanding will help teams connect evidence across literature, genomics, transcriptomics, sequence, structure, and experimental results, making it easier to move from data to clearer research decisions.

We are also now offering an OpenAI managed workspace for qualified organizations without an Enterprise account.

What’s next

The updated GPT‑Rosalind is the next step in our broader commitment to building AI systems that can help accelerate scientific discovery while ensuring that advanced biological capabilities are deployed with appropriate safeguards. We will continue improving the model’s biological reasoning, expanding support for tool-heavy and long-horizon research workflows, and working with qualified organizations across regions to evaluate real-world impact.

This also means applying life sciences AI to high-impact public-benefit work, from drug discovery and translational medicine to public health, preparedness, and biodefense. Through Rosalind Biodefense and our trusted-access deployment model, we aim to put frontier biological capabilities in the hands of the researchers, institutions, and defenders working to improve human health and strengthen societal resilience.

We will continue building GPT‑Rosalind to become a more capable partner across the full life cycle of scientific research, helping scientists move more quickly from the right questions to clearer evidence, better experiments, and ultimately new treatments for patients.

Original source

New Features

• TUI controls now support F13-F24 keybindings, paste in searchable menus, and a compact reasoning-only status/title item (#25329, #25400, #25504).
• Enterprise/admin flows now show monthly credit limits and can apply cloud-managed config bundles, including EDU workspaces (#24812, #24617, #24619, #24620, #24622, #25963).
• Remote-control clients can start pairing and list or revoke controller grants through app-server v2 RPCs (#25675, #25785).
• Plugin workflows gained machine-readable codex plugin list --json output and cached remote catalog suggestions (#25330, #25457).
• Hosted web and image tools are available in more code-mode flows, with standalone web searches able to run in parallel (#25176, #25702, #25890, #25923).
• Multi-agent v2 keeps runtime choice with each thread and exposes cleaner follow-up and metadata defaults for spawned agents (#25266, #25636, #25720, #25721, #25722, #25841, #26114).

Bug Fixes

• Cancelling a submitted prompt before visible output now restores the draft, attachments, and collaboration mode for editing (#25316).
• Slash-command filtering and footer shortcut hints now reset or render according to the current UI state (#25492, #25625).
• Platform reliability improved for macOS app launches and Windows SQLite startup, thread resume, and sandbox setup refreshes (#25485, #25490, #25509, #25949).
• Plugin loading preserves app manifest order, deduplicates local/remote curated installs, and treats malformed skills fields as warnings (#25491, #25681, #25717, #25782).
• Permission requests and approvals now carry environment identity, and managed MITM proxying exports readable CA bundles to child commands (#25850, #25858, #25862, #22668).
• Local session history is safer for compressed rollouts, renamed titles, pathless side-chat reloads, and stack-heavy startup/config rebuilds (#25087, #25624, #25661, #25814, #25844, #25847).

Documentation

• Added app-server docs and generated schema updates for monthly credit limits, remote-control RPCs, and environment-scoped permission approvals (#24812, #25675, #25785, #25862).
• Moved repo review rules and contributor conventions into AGENTS.md, including Rust test-module layout and Python 3 compatibility guidance (#25682, #25690, #25738).

Chores

• Root formatting and Justfile workflows are more complete and Windows-aware (#24983, #25165, #25683).
• Rust CI and release workflows use the git CLI for Cargo fetches to avoid intermittent libgit2/submodule failures (#25644, #25775).
• Python SDK releases now publish runtime wheels from the SDK workflow and pin to a glibc-compatible runtime package (#25906, #25907).
• Bazel CI’s BuildBuddy wrapper was reintroduced with Windows-safe process handling and validation (#25915).
• Shared prompts, context fragments, and skills plumbing moved into dedicated crates/extension paths to reduce codex-core coupling (#25151, #25953, #25959, #26106, #26122, #26167).

Changelog

Full Changelog:

rust-v0.136.0...rust-v0.137.0

Original source

Build and deploy internal websites and apps with ChatGPT Sites

ChatGPT Sites is now available in preview for ChatGPT Business workspaces with Codex access. Available as a plugin, teams can ask Codex to create, iterate on, and deploy lightweight full-stack JavaScript/TypeScript web apps for internal workspace use, with hosted site URLs, Sign in with ChatGPT access and data & file storage storage, while keeping access workspace internal.

Admins and owners can manage enablement and access through workspace settings and RBAC. For Business workspaces, ChatGPT Sites is enabled by default, and can be managed from Workspace settings > Permissions & Roles.

Admins and owners can disable created sites from Workspace settings > Sites.

Learn more: Codex Sites developer guide.

Role-specific plugins in Codex

Role-specific plugins are rolling out in Codex for supported ChatGPT Business workspaces. This first set includes Sales, Data Analytics, Product Design, Creative Production, Investment Banking, and Public Equity Investing. These plugins package role-specific skills, app integrations, starter prompts, and workflow guidance so teams can use Codex for sales prep, analytics and dashboards, prototypes, creative assets, and financial research.

This launch also adds 66 single-app plugins that expand the integrations available in Codex, including tools such as Databricks, Salesforce, Hex, and Clay. Users can add available plugins from the Codex plugin directory, and Codex can help them complete setup. Workspace admins control the underlying app permissions in workspace settings; if a required app is not enabled, the related plugin may not be available.

Learn more: Plugins in Codex.

Active account session controls

We’re rolling out Active sessions, a new security feature in ChatGPT that helps users review sessions associated with their account and sign out of sessions they don’t recognize.

Availability:

This feature is not available for accounts linked to an organization’s SSO sign-in, including SAML or OIDC. This can apply even if the organization does not require SSO for every sign-in, or if the user signed in another way for their current session.

Users with access can now:

• Review first-party OpenAI sessions from Settings > Security > Active sessions, with available details such as device, app, approximate location, sign-in time, trusted-device status, and whether it is the current session.
• Log out of individual sessions or all sessions from Active sessions

Active sessions shows sessions known through session management, including ChatGPT, Codex, and API Platform sessions where available. It does not manage third-party app sessions, connected apps, Sign in with ChatGPT sessions used only for third-party services, or Codex CLI sessions.

Learn more: Managing active sessions in ChatGPT.

Original source

Active account session controls

We’re rolling out Active sessions, a new security feature in ChatGPT that helps users review sessions associated with their account and sign out of sessions they don’t recognize.

Users can now:

• Review first-party OpenAI sessions from Settings > Security > Active sessions, with available details such as device, app, approximate location, sign-in time, trusted-device status, and whether it is the current session
• Log out of individual sessions or all sessions from Active sessions

Active sessions shows sessions known through session management, including ChatGPT, Codex, and API Platform sessions where available. It does not manage third-party app sessions, connected apps, Sign in with ChatGPT sessions used only for third-party services, or Codex CLI sessions.

Learn more: Managing active sessions in ChatGPT

Original source

New role-specific plugins, Sites, and annotations help teams do more with Codex.

More than 5 million people now use Codex every week. Codex started as a tool for software development, but it's increasingly useful for more kinds of work. Non-developers—including analysts, marketers, operators, designers, researchers, investors, and bankers—make up about 20% of overall Codex users⁠ and are growing more than 3x as fast as developers.

Today, we’re introducing new ways to do more of your work with Codex: plugins that adapt Codex to your role and tools, annotations that help you refine the result in place, and a preview of the ability to create interactive websites and apps you can share with your workspace using a URL.

Inside OpenAI, non-technical teams use Codex to build internal apps, prepare executive materials, create dashboards, and turn creative briefs into work that reflects brand and design constraints. At Zapier, teams use Codex to pull knowledge from tools like Slack, Google Docs, and Coda, then turn that context into postmortems, incident response plans, and feature tickets. At NVIDIA, researchers are using Codex to speed up experiment workflows, from finding research ideas to writing scripts for machine learning infrastructure.

Make Codex work the way your team does

Codex is most useful when it works the way your team does: connected to the tools you use and ready to create the materials you need.

Plugins help Codex work with the tools, context, and workflows your team already uses. Today, we’re launching six new role-specific plugins that make Codex useful for more kinds of knowledge work, no coding required:

• Each plugin bundles the relevant apps, skills, instructions, and workflows. Together, they include 62 popular apps and 110 skills.
• The data analytics plugin helps analysts and business teams answer questions with data. They can explore product and business data, explain why key metrics changed, and create reports and dashboards using tools like Snowflake, Databricks Genie, Hex, and Tableau, with more coming soon.
• The creative production plugin helps marketing and creative teams turn a brief into assets they can review. Teams can create campaign boards, make and refine display ad variations, and produce product lifestyle shots or ecommerce-ready image sets with tools like Figma, Canva, Shutterstock, Picsart, and Fal.
• The sales plugin helps sales teams bring customer context into the work that moves deals forward. Sales teams can find high-priority accounts and signals, prepare for customer meetings, complete follow-ups, update customer records, build close plans, and review deals at risk using tools like Salesforce, HubSpot, Slack, Outreach, Clay, Rox, and Actively.
• The product design plugin is built for turning early ideas into prototypes teams can review. Teams can explore product directions, audit user flows, prototype from a live URL, and make static screenshots interactive, with work that can be carried forward in tools like Figma and Canva.
• The public equity investing plugin helps investors make sense of market and company information. They can review earnings, compare companies, track signals, and assess whether an investment thesis is strengthening or weakening using information from Moody’s, Daloopa, Datasite, FactSet, LSEG, S&P, PitchBook, and Hebbia.
• The investment banking plugin helps bankers turn research and diligence into client-ready materials. They can prepare pitch materials, analyze comparable companies and transactions, and turn diligence into recommendations using trusted data.

Plugins work out of the box. Teams can also adapt them to their workflows or build and share custom plugins for their own systems and processes.

More role-specific plugins are coming soon, including Corporate Finance, Private Equity Investing, Marketing Strategy, Strategy Consulting, and Legal. And this is just the start: we’re building toward an open ecosystem where partners can create and deploy their own plugins directly in Codex and ChatGPT.

Share your work with sites

Starting in preview for business and enterprise customers, Codex can now create and share interactive, hosted websites and apps.

Sites are a new kind of canvas for your ideas. Codex can take your ideas, analysis, and plans and turn them into dashboards, planners, review workspaces, project boards, galleries, and lightweight tools. Today, sites can be shared with anyone in your workspace via URL, giving teams a shared place to explore work, contribute input, track progress, and make decisions together.

Ask Codex to create a site for an upcoming customer review, and it’ll generate an interactive webpage with the relevant product updates, open questions, usage trends, and next steps for that account. Ask it to build a scenario planner from a financial model, so leaders can compare assumptions instead of reading through tabs in a doc. Ask it to turn launch materials into a living hub where teams can find the latest messaging, milestones, owners, and decisions. Then ask Codex to keep the site up to date as details change.

Instead of adapting work to the limits of a single tool or file, teams can create sites that fit the work. And sites aren’t static. They can also help track progress for a major project, help guide customer service reps, or act as a repository for your team’s creative briefs.

We’re also working with early partners including Vercel, Wix, Base44, Replit, Lovable, Figma, Webflow, and Emergent as we build towards a sites partner ecosystem.

Refine your work with annotations

Developers already use annotations in Codex to refine code, Markdown files, and websites Codex creates. With annotations, you point to the exact part you want to refine and tell Codex what needs to change. That way of working now extends to content you create, like documents, spreadsheets, and slides.

Select the navigation bar in a site and ask Codex to update the font. Highlight a claim in an investment thesis and ask Codex where it came from. Mark a chart on a slide and ask for a clearer label. Codex focuses the update on the part you selected, so you can refine your work without starting over or reworking the parts you already like. Annotations make Codex more useful after the first draft, when the work needs judgment, feedback, and iteration.

Availability and getting started

Role-specific plugins are rolling out in Codex in supported regions. You can install them from the Codex plugin directory and Codex will help get you set up. Codex can also help you customize a plugin. For Business and Enterprise workspaces, admins can control⁠ (opens in a new window) underlying app permissions in workspace settings.

Sites are rolling out in preview for Business and Enterprise teams through the Codex app. Enterprise admins can enable sites⁠ (opens in a new window) in admin settings.

Explore more stories about how teams use Codex, or get in touch with our team to get started.

Original source

ChatGPT Sites is now available in preview for eligible ChatGPT Enterprise and Edu workspaces.

Available as a plugin, users can ask Codex to create, iterate on, and deploy lightweight full-stack JavaScript/TypeScript web apps with hosted site URLs, Sign in with ChatGPT access, and data/file storage, while keeping access workspace-internal.

ChatGPT Sites is default off for Enterprise/Edu workspaces - admins and owners can manage enablement and access through workspace settings and RBAC. ChatGPT Sites can be enabled from Workspace settings > Permissions & Roles. Admins and owners can disable published sites from Workspace settings > Sites.

For build, deployment, storage, access, and limitation details, see the Codex Sites developer guide.

Original source