In 2025, AI agents that write, test, and propose code have moved from toy demos to practical developer tools. The recent update announcement of Claude Code on the web exemplifies this. Which, in short, means you will now be able to access the Claude Code agent on the web, effectively. So, what does it mean for you and/or your team? Read on to learn about the Claude Code web release and how it compares to OpenAI Codex.
Note: if you’re after a more in-depth comparison, consider reading this.
What is Claude Code on the web?
Anthropic announced “Claude Code on the web” as a research preview on October 20, 2025. The short version: it brings Anthropic’s Claude Code agent experience out of the terminal and into a cloud-hosted, browser- and mobile-accessible interface that can connect to GitHub repos, run tasks in isolated environments, and create PRs automatically — all while exposing real-time progress and steering controls to the user. The company positions this as a way to delegate many routine coding tasks (bug fixes, small feature work, tests, repository mapping questions) and to run multiple tasks in parallel from a single interface.
Two aspects of the announcement stand out and form the backbone of Anthropic’s pitch: (1) parallel, cloud-hosted execution, and (2) security-first sandboxing and Git proxying. By running each task in its own isolated environment, Anthropic enables Claude Code to spin up multiple sessions across different repositories without the user having to open terminals or manage local environments; each session reports progress and can be steered mid-flight. This parallelism is explicitly marketed as a productivity multiplier for backlogs and routine work.
Learn: How to install Claude Code CLI
Security and isolation are central to the release messaging. Anthropic emphasizes that every Claude Code task runs in a sandbox with both filesystem and network restrictions, and that Git operations are mediated through a secure proxy so the agent only touches repositories it’s authorized to—reducing the risk of credential leakage or unintended lateral network access. The company also documents the ability to customize network rules (for example, allowing npm downloads when tests must run) and points to a deeper engineering write-up about their runtime and sandboxing implementation. That engineering material explains how the runtime constrains the agent’s bash tool, enforces filesystem boundaries, and issues alerts if the model tries to access resources outside the sandbox.
The product is positioned as complementary to existing Claude Code workflows: teams that want local CLI-driven interactions can keep using that interface, while the web view adds convenience, mobile access, and an easier way to orchestrate multiple cloud sessions. Anthropic is making the preview available to Pro and Max subscribers (research preview), and points users to documentation and an engineering blog for the sandboxing details. In short: Claude Code on the web is a cloud-first, sandbox-centric, repo-connected agent experience designed to be safe, observable, and easy to steer.
Finally, Anthropic’s release also signals a broader intent: making agentic programming accessible in more contexts (browser, mobile) while leaning heavily on runtime isolation and policy surfaces to reduce attack surface and make autonomous actions auditable. Their public docs and engineering blog are explicit about the sandboxing primitives and the trade-offs they make to let agents run more autonomously while keeping risk in check.
How OpenAI Codex Compares
OpenAI’s Codex has a more layered history. The original Codex (announced August 10, 2021) was a model family derived from GPT-3 and fine-tuned on large quantities of public source code; it powered early code generation products such as GitHub Copilot and was explicitly marketed as a system that translates natural language into code across many languages. That original Codex emphasized code synthesis, explanation, refactoring, and transpilation capabilities and was primarily exposed via APIs and integrations in editors/IDEs.
Over time, OpenAI’s product strategy evolved. The original Codex models were deprecated in March 2023 as OpenAI moved toward GPT-class models (GPT-3.5, GPT-4, and now GPT-5, which you can try here) for code tasks. OpenAI reintroduced the Codex name in a new form: a cloud-based software-engineering agent and an accompanying open-source Codex CLI that can run locally. The 2025 Codex agent (announced in a May 16, 2025, update and subsequent product pages) is explicitly designed to run parallel tasks in the cloud, operate in repository-preloaded sandboxes, run tests, propose PRs, and be steered mid-task—features that overlap strongly with what Anthropic describes for Claude Code on the web.
OpenAI also released a Codex CLI (April 16, 2025) as an open-source local agent, and later product updates moved Codex toward general availability with SDKs and Slack integrations.
So functionally, OpenAI’s modern Codex and Anthropic’s Claude Code share many high-level design choices: cloud sandboxes for running code, task parallelism, the ability to interact with repositories and produce PRs, and a focus on observability and developer control. But how do they differ in practice?
Claude Code on the web vs OpenAI Codex — head-to-head
1) Execution model: cloud sessions vs local CLI
Both companies now offer hybrid approaches: Anthropic’s web release emphasizes cloud-hosted sessions (with an existing CLI workflow remaining available), while OpenAI deliberately ships both a cloud Codex agent and a local open-source CLI (Codex CLI) so developers can choose local execution for privacy and latency reasons or cloud execution for scale and parallelism. The practical effect: if your org demands on-prem/local-only runs, OpenAI’s open-source CLI may be attractive; if you want a tightly managed cloud sandbox with direct browser access, Claude Code’s web preview is built for that workflow.
2) Sandboxing and security controls
Both vendors foreground sandboxing and restricted network access. Anthropic’s communications and engineering blog emphasize filesystem and network restrictions, and a secure Git proxy for repository operations—allowing fine-grained domain whitelisting (e.g., npm) and alerts when the agent attempts out-of-scope actions. OpenAI’s Codex agent similarly runs tasks in preloaded virtual sandboxes and presents audit trails and steering controls; OpenAI’s public materials also mention admin tooling (SDKs, Slack integration, and admin controls in GA releases). Both sides appear to recognize that autonomy without containment is unsafe—so sandboxing is a shared priority, though the specific runtime design and verification tooling will likely differ.
3) Openness and developer control
OpenAI’s 2025 moves included releasing a Codex CLI as open-source and offering a Codex SDK, which signals a tilt toward giving developers more direct control over agent behavior and deployment. Anthropic’s Claude Code remains a managed Anthropic offering (now with a web front end), available via Pro/Max plans. For teams that want to fork, self-host, or extensively customize agent code and runtimes, OpenAI’s open-source CLI could be a plus. For teams that prefer a managed, tightly controlled cloud experience with Anthropic handling infra and upgrades, Claude Code on the web provides convenience.
4) Model and behavioral differences
Underlying model families differ philosophically and technically. Anthropic’s Claude family is trained and fine-tuned under Anthropic’s safety-oriented research and uses techniques (e.g., Constitutional AI and behavior-shaping training) focused on guardrails and reduced undesired outputs. OpenAI’s Codex lineage began as a GPT-3 derivative; by 2025 it’s tied into OpenAI’s GPT series and product ecosystem (Codex as an agent is powered by recent model snapshots tuned for coding). These training and alignment differences can produce different default coding styles, verbosity, and safety behaviors. Which produces fewer hallucinations, better tests, or cleaner PRs will vary by task and dataset; empirical evaluation by teams will still be necessary.
5) Ecosystem and integrations
OpenAI’s Codex name carries historical weight thanks to GitHub Copilot and a broad ecosystem of editor integrations and community tooling. The 2025 Codex GA materials emphasize Slack integration and SDKs for embedding agents into workflows. Anthropic, while newer in large-scale enterprise integrations, focuses on the developer experience around Claude and links its Code offering into Claude Developer Platform, enterprise plans, and cloud partners (e.g., Bedrock/Vertex AI connectors). Choice of vendor may therefore hinge on the integrations your team needs today (IDEs, internal tooling, Slack, enterprise SSO, cloud vendor compatibility).
6) Availability, pricing, and product posture
Anthropic’s web release is explicitly a research preview available to Pro and Max subscribers—designed to collect feedback and iterate. OpenAI’s Codex has navigated a lifecycle from early-2021 API play, through deprecation of legacy Codex models in 2023, to a 2025 resurgence as a cloud agent and local CLI. OpenAI has started rolling Codex to Pro/Enterprise users and announced GA features later in 2025. For procurement teams, that timeline matters: one vendor is pushing a managed preview while the other is offering both managed cloud and open-source local options with a movement toward GA features.
The Bottom Line
Anthropic’s Claude Code on the web pushes agentic coding into a managed, security-focused cloud with tight sandboxing and Git controls. OpenAI’s Codex takes the opposite route. It pairs cloud agents with open-source tools, giving teams more freedom and reach. Both are chasing similar ideas like task isolation, pull request generation, and parallel execution, but their intent differs. Anthropic is building for containment and trust; OpenAI is building for flexibility and scale. The real question for teams isn’t which is more advanced, but which aligns with their values: control or autonomy, compliance or velocity. If control and autonomy are what you need, perhaps consider options such as Bind AI, your all-in-one, AI-powered coding assistant. Learn more here.