terminal
howtonotcode.com
Codex logo

Codex

Ai Tool

Codex converts natural language prompts into code for developers.

article 36 storys calendar_today First seen: 2026-02-03 update Last seen: 2026-03-03 open_in_new Website menu_book Wikipedia

Resources

Links to check for updates: homepage, feed, or git repo.

home Homepage

Stories

Showing 1-20 of 36

Agent-first SDLC: from pilots to production

Agent-first development is moving from hype to execution, and teams that redesign workflows, codebases, and governance around AI agents are starting to ship faster while hiring now expects AI fluency by default. OpenAI’s internal playbook outlines concrete practices like making an agent the tool of first resort, maintaining AGENTS.md, exposing internal tools via CLI/MCP, and writing fast tests to keep agents productive and safe ([OpenAI team thread recap](https://threadreaderapp.com/thread/2019566641491963946.htmladar guide](https://www.techradar.com/pro/how-to-take-ai-from-pilots-to-deliver-real-business-value)[^2]). Urgency is rising with accelerating model capability and massive 2026 AI capex, and leadership signals that AI literacy is now table stakes for hiring ([Nate’s Substack](https://natesnewsletter.substack.com/p/the-two-career-collapses-happening)[^3]; [Cisco CEO remarks](https://www.webpronews.com/chuck-robbins-blunt-career-playbook-why-ciscos-ceo-says-the-rules-of-getting-hired-have-fundamentally-changed/)[^4]). [^1]: Practical blueprint for agent-first workflows (agents captain, AGENTS.md, skills, tool access via CLI/MCP, fast tests, quality bar). [^2]: Execution framework to scale beyond pilots with governance, integration, and business alignment. [^3]: Context on accelerating AI capability and investment signaling near-term impact pressure. [^4]: Market signal that AI fluency is expected across roles, not just engineering.

calendar_today 2026-02-09
openai codex camunda cisco epoch-ai

Agentic development lands in Xcode, GitHub Actions, and Google APIs

Agentic development is moving from proofs to practice across core tooling, with Xcode 26.3 adding in-IDE agents and MCP, GitHub piloting agentic workflows in Actions with guardrails, and Google introducing APIs that make assistants stateful and documentation-accurate. Apple’s latest Xcode adds deeper agent capabilities and first-class MCP integration, enabling Claude/Codex-style agents to plan, run builds/tests, and verify via Previews within the IDE [InfoQ](https://www.infoq.com/news/2026/02/xcode-26-3-agentic-coding/)[^1]. GitHub Next’s experimental Agentic Workflows bring locked-down, event-driven agents to CI using a CLI that compiles natural language into read-only, sandboxed Actions [Amplifi Labs](https://www.amplifilabs.com/post/css-scope-hits-baseline-github-agentic-workflows-oss-trust-tools)[^2]; meanwhile, Google’s Developer Knowledge API with an MCP server and the new Interactions API push assistants toward on-demand, canonical retrieval and managed, stateful steps for deep research [DevOps.com](https://devops.com/google-launches-developer-knowledge-api-to-give-ai-tools-access-to-official-documentation/)[^3] [Towards Data Science](https://towardsdatascience.com/the-death-of-the-everything-prompt-googles-move-toward-structured-ai/)[^4]. [^1]: Adds: release details on agent behaviors, MCP via mcpbridge, and verification in Xcode 26.3. [^2]: Adds: overview of GitHub Agentic Workflows model, guardrails, and repo automation scenarios. [^3]: Adds: specifics on the Developer Knowledge API, freshness guarantees, and MCP server integration. [^4]: Adds: explanation of Google’s Interactions API for stateful, tool-orchestrated agent flows.

calendar_today 2026-02-09
xcode anthropic claude-agent claude-code openai

Claude Opus 4.6 adds agent teams, 1M context, and fast mode; GPT-5.3-Codex counters

Anthropic’s Claude Opus 4.6 ships multi-agent coding, a 1M-token context window, and a 2.5x fast mode, while OpenAI’s GPT-5.3-Codex brings faster agentic coding with strong benchmark results. DeepLearning.ai details Opus 4.6’s long-context, agentic coding gains, new API controls, and Codex 5.3’s speed and scores, plus pricing context [Data Points: Claude Opus 4.6 pushes the envelope](https://www.deeplearning.ai/the-batch/claude-opus-4-6-pushes-the-envelope/)[^1]. AI Collective highlights Claude Code’s new multi-agent “agent teams,” Office sidebars, and head-to-head benchmark moves versus OpenAI, while Storyboard18 confirms a 2.5x “fast mode” rollout for urgent work [Anthropic’s Opus 4.6 Agent Teams & OpenAI’s Codex 5.3](https://aicollective.substack.com/p/the-brief-anthropics-opus-46-agent)[^2] and [Anthropic rolls out fast mode for Claude Code](https://www.storyboard18.com/digital/anthropic-rolls-out-fast-mode-for-claude-code-to-speed-up-developer-workflows-89148.htm)[^3]. [^1]: Roundup covering features, benchmarks, and pricing for Opus 4.6 and GPT‑5.3‑Codex. [^2]: Newsletter with details on "agent teams," 1M-context performance, Office integrations, and comparative benchmarks. [^3]: Report on the 2.5x faster "fast mode" availability and target use cases.

calendar_today 2026-02-09
anthropic claude-opus-46 claude-code openai gpt-53-codex

Codex 5.3 vs Opus 4.6: agentic speed vs long‑context depth

OpenAI's GPT-5.3 Codex and Anthropic's Claude Opus 4.6 arrive with distinct strengths—Codex favors faster agentic execution while Opus excels at long-context reasoning and consistency—so choose based on workflow fit, not hype. Independent hands-on comparisons report Codex 5.3 is snappier and stronger at end-to-end coding actions, while Opus 4.6 is more reliable with context and less babysitting for routine repo tasks, with benchmark numbers and capabilities outlining the trade-offs in real projects ([Interconnects](https://www.interconnects.ai/p/opus-46-vs-codex-53)[^1], [Tensorlake](https://www.tensorlake.ai/blog/claude-opus-4-6-vs-gpt-5-3-codex)[^2]). Opus adds agent teams, 1M-token context (beta), adaptive effort controls, and Codex claims ~25% speed gains and agentic improvements, underscoring a shift toward practical, multi-step workflows ([Elephas](https://elephas.app/resources/claude-opus-4-6-vs-gpt-5-3-codex)[^3]). [^1]: Adds: Usability differences from field use; Opus needs less supervision on mundane tasks while Codex 5.3 improved but can misplace/skip files. [^2]: Adds: Concrete benchmarks (SWE Bench Pro, Terminal Bench 2.0, OSWorld) and scenario-based comparison for UI/data workflows. [^3]: Adds: Feature deltas (Agent Teams, 1M context, adaptive thinking) and speed claims/timing details across both launches.

calendar_today 2026-02-09
openai anthropic gpt-53-codex claude-opus-46 claude-code

Agentic coding enters IDEs, CI, and docs with MCP and stronger guardrails

Agentic coding is moving into mainstream tooling as Xcode 26.3, GitHub Actions pilots, and new Google offerings converge on guarded, MCP-compatible agents across IDEs, CI, and authoritative docs. Xcode 26.3 expands integrated agentic coding for Claude and Codex, adds Model Context Protocol support, and lets agents verify UI via Previews for iterative fixes and planning.[^1] GitHub Next is piloting Agentic Workflows for Actions with strict defaults, while Google advances an agent‑first stack via Antigravity and a Developer Knowledge API plus MCP server that enables assistants to retrieve official docs at runtime.[^2][^3][^4] [^1]: https://www.infoq.com/news/2026/02/xcode-26-3-agentic-coding/ — Details on Xcode 26.3 agent capabilities, MCP support, and verification via Previews. [^2]: https://www.amplifilabs.com/post/css-scope-hits-baseline-github-agentic-workflows-oss-trust-tools — Newsletter coverage of GitHub Agentic Workflows and safety guardrails. [^3]: https://antigravity.im/ — Independent guide outlining Google Antigravity’s agent‑first IDE and multi‑agent orchestration. [^4]: https://devops.com/google-launches-developer-knowledge-api-to-give-ai-tools-access-to-official-documentation/ — Overview of Google’s Developer Knowledge API and MCP server for authoritative documentation retrieval.

calendar_today 2026-02-09
xcode anthropic claude-agent claude-code openai

OpenAI’s GPT-5.3-Codex rolls out to Copilot with faster, agentic workflows

OpenAI's GPT-5.3-Codex is a 25% faster, more agentic coding model built for long-running, tool-driven workflows and is now rolling out across Codex surfaces and GitHub Copilot with stronger cybersecurity guardrails. OpenAI positions the model for multi-step coding and broader "computer use" with SOTA benchmark results and notes early versions helped build and operate itself [Pulse 2.0](https://pulse2.com/openai-reveals-gpt-5-3-codex-a-faster-agentic-coding-model-built-for-long-running-work/)[^1] and [AI-360](https://www.ai-360.online/openai-launches-gpt-5-3-codex-extending-agentic-coding-and-real-time-steering/)[^2]. GitHub confirms GPT-5.3-Codex is GA in Copilot (Pro/Business/Enterprise) across VS Code, web, mobile, CLI, and the Coding Agent with an admin-enabled policy toggle and gradual rollout [GitHub Changelog](https://github.blog/changelog/2026-02-09-gpt-5-3-codex-is-now-generally-available-for-github-copilot/)[^3], while OpenAI channels have it now with API access "soon" and a new Trusted Access for Cyber pilot [Pulse 2.0](https://pulse2.com/openai-reveals-gpt-5-3-codex-a-faster-agentic-coding-model-built-for-long-running-work/)[^1] and [ITP.net](https://www.itp.net/ai-automation/openai-launches-gpt-5-3-codex-the-new-era-of-ai-powered-coding-and-beyond)[^4]. [^1]: Adds: Core capabilities, benchmark highlights, safety posture, availability across Codex app/CLI/IDE/web, and NVIDIA GB200 NVL72 infra. [^2]: Adds: Real-time steering in extended runs and cybersecurity classification/pilot context for enterprise adoption. [^3]: Adds: Concrete Copilot GA details, supported surfaces, plans, rollout, and admin policy enablement. [^4]: Adds: Additional context on broader professional task coverage and API timing.

calendar_today 2026-02-09
openai gpt-53-codex openai-codex-app github github-copilot

Opus 4.6 Agent Teams vs GPT-5.3 Codex: multi‑agent coding arrives for real SDLC work

Anthropic's Claude Opus 4.6 brings multi-agent "Agent Teams" and a 1M-token context while OpenAI's GPT-5.3-Codex counters with faster, stronger agentic coding, together signaling a step change in AI-assisted development. Opus 4.6 adds team-based parallelization in Claude Code, long‑context retrieval gains, adaptive reasoning/effort controls, and Office sidebars, with pricing unchanged [Data Points](https://www.deeplearning.ai/the-batch/claude-opus-4-6-pushes-the-envelope/)[^1] and launch coverage framing initial benchmark leads at release [AI Collective](https://aicollective.substack.com/p/the-brief-anthropics-opus-46-agent)[^2]. OpenAI’s GPT‑5.3‑Codex posts top results on SWE‑Bench Pro and Terminal‑Bench 2.0 and helped debug its own training pipeline [Data Points](https://www.deeplearning.ai/the-batch/claude-opus-4-6-pushes-the-envelope/)[^3], while practitioners surface Claude Code’s new Auto‑Memory behavior/controls for safer long‑running projects [Reddit](https://www.reddit.com/r/ClaudeCode/comments/1qzmofn/how_claude_code_automemory_works_official_feature/)[^4] and Anthropic leaders say AI now writes nearly all their internal code [India Today](https://www.indiatoday.in/technology/news/story/anthropic-says-ai-writing-nearly-100-percent-code-internally-claude-basically-writes-itself-now-2865644-2026-02-09)[^5]. [^1]: Adds: Opus 4.6 features (1M context), long‑context results, adaptive/effort/compaction API controls, and unchanged pricing. [^2]: Adds: Agent Teams in Claude Code, Office (Excel/PowerPoint) sidebars, 1M context, and benchmark framing at launch. [^3]: Adds: GPT‑5.3‑Codex benchmarks, 25% speedup, availability, and self‑use in OAI’s training/deployment pipeline. [^4]: Adds: Concrete Auto‑Memory details (location, 200‑line cap) and disable flag for policy compliance. [^5]: Adds: Real‑world claim of near‑100% AI‑written internal code at Anthropic, indicating mature SDLC use.

calendar_today 2026-02-09
anthropic openai claude-opus-46 claude-code gpt-53-codex

LLM-to-Docker in Local Dev: Use a Broker Pattern

A community question on letting OpenAI Codex control a local Docker environment highlights the need to mediate LLM-driven container actions through a safe, auditable broker instead of direct access. An OpenAI Community thread asks how to enable Codex-to-Docker connectivity in a local setup and surfaces the integration challenge for teams experimenting with LLM-guided container workflows [How to allow Codex connection to Docker in local environment?](https://community.openai.com/t/how-to-allow-codex-connection-to-docker-in-local-environment/1373567#post_1)[^1]. [^1]: Adds: Shows real-world demand and the core question teams face when wiring LLM suggestions to local Docker actions.

calendar_today 2026-02-07
openai codex docker containers security

Shortlist GPT-5.3-Codex–compatible AI coding assistants

A regularly updated SourceForge list highlights AI coding assistants that integrate with GPT-5.3-Codex, with filters to help teams shortlist tools by deployment, support, and pricing. See the curated comparison of GPT-5.3-Codex–compatible assistants, including entries like JetBrains Junie, and use the filters to match enterprise constraints and environments ([SourceForge list](https://sourceforge.net/software/ai-coding-assistants/integrates-with-gpt-5.3-codex/))[^ 1]. [^ 1]: Adds: curated, regularly updated catalog of GPT-5.3-Codex–integrated coding assistants with examples (e.g., JetBrains Junie), filters (deployment, support, pricing), and basic feature descriptions.

calendar_today 2026-02-07
jetbrains-junie jetbrains gpt-53-codex sourceforge gpt-5-3-codex

OpenAI recommends GPT-5.3-Codex as the default agentic coding model

OpenAI now recommends GPT-5.3-Codex as the default Codex model, signaling a step-up in agentic coding and reasoning for real-world engineering. The official Codex Models page highlights GPT-5.3-Codex as the most capable, with GPT-5.2-Codex as predecessor and a smaller GPT-5.1-Codex-mini option for cost-sensitive tasks [OpenAI Codex Models](https://developers.openai.com/codex/models/)[^1]. An anecdotal report describes spending $10,000 to automate research with Codex, indicating emerging large-scale usage patterns [Practitioner report](https://links.tldrnewsletter.com/J7poJAf substantial Codex-driven automation and spend.

calendar_today 2026-02-07
openai codex gpt-53-codex gpt-52-codex gpt-51-codex-mini

OpenAI ships GPT-5.3-Codex into IDEs, terminals, web, and a macOS app

OpenAI launched GPT-5.3-Codex, a faster coding model now embedded in IDEs, the terminal, web, and a macOS app, with early claims it assisted in building itself. OpenAI details ~25% faster runs, stronger SWE-Bench/Terminal-Bench results, and broad distribution via CLI, IDE extensions, web, and a new macOS app in the announcement [Introducing GPT‑5.3‑Codex](https://openai.com/index/introducing-gpt-5-3-codex/)[^1]. Coverage notes all paid ChatGPT plans can access it now, API access is coming, and the team used Codex to debug, manage deployment, and evaluate results during its own development [TechRadar report](https://www.techradar.com/pro/openai-unveils-gpt-5-3-codex-which-can-tackle-more-advanced-and-complex-coding-tasks)[^2], with additional workflow and positioning details on distribution and SDLC scope [AI News Hub](https://www.chatai.com/posts/openai-pushes-codex-deeper-into-developer-workflows-with-gpt-5-3-codex-release)[^3]. [^1]: Adds: Official feature, performance, and distribution overview. [^2]: Adds: Access paths (paid ChatGPT plans), benchmarks, and "built itself" context. [^3]: Adds: Deeper coverage of IDE/CLI/macOS integration, speedup figure, and API timing.

calendar_today 2026-02-07
openai gpt-53-codex chatgpt codex-macos-app gpt-5-3-codex

Hands-on: Claude Opus 4.6 nails non‑agentic coding; GPT‑5.3 Codex lacks API

A 48-hour hands-on found Claude Opus 4.6 delivering perfect non-agentic coding results while GPT‑5.3 Codex looks strong in benchmarks but still lacks API access for validation. In this test-run, Opus 4.6 hit 100% across 11 single-shot coding tasks (including 3D layout, SVG composition, and legal-move chess) and contradicted popular benchmark narratives, while Codex couldn’t be reproduced due to no API access yet per this report [I Spent 48 Hours Testing Claude Opus 4.6 & GPT-5.3 Codex](https://medium.com/@info.booststash/i-spent-48-hours-testing-claude-opus-4-6-gpt-5-3-codex-004adc046312)[^1]. [^1]: Adds: hands-on results, examples, benchmark context, and note on GPT‑5.3 Codex API unavailability.

calendar_today 2026-02-07
claude-opus-46 gpt-53-codex anthropic openai terminal-bench

Codex 0.95–0.96 ship async compaction, rate-limit signals; MassGen adds Codex backend

OpenAI’s Codex app/server shipped 0.95–0.96 with v2 async thread compaction, websocket rate‑limit signaling, expanded skill loading/remote catalogs, shell parallelism, state‑DB correctness, telemetry, and Linux sandbox groundwork ([0.95.0](https://github.com/openai/codex/releases/tag/rust-v0.95.0)[^1], [0.96.0](https://github.com/openai/codex/releases/tag/rust-v0.96.0)[^2]). MassGen now offers a Codex backend with local/Docker modes to orchestrate multi‑agent workflows and MCP tooling ([MassGen v0.1.47](https://github.com/massgen/MassGen/releases/tag/v0.1.47)[^3]). Expect workflow differences vs IDEs—Codex is positioned as an agentic assistant, not a full IDE—and note a Windows PowerShell 5.1 ANSI‑encoding issue affecting Cyrillic output ([video](https://www.youtube.com/watch?v=ts7yQdfBW_U&pp=ygURQ3Vyc29yIElERSB1cGRhdGU%3D)[^4], [forum thread](https://community.openai.com/t/incorrect-cyrillic-rendering-in-codex-agent-on-windows-due-to-powershell-5-1-default-ansi-encoding/1356123#post_5)[^5]). [^1]: Release notes: skills loading and remote catalogs, macOS `codex app` CLI, shell parallelism, Git safety hardening, TUI improvements, Linux sandbox groundwork. [^2]: Release notes: `thread/compact` async RPC, websocket `codex.rate_limits` event, `unified_exec` enablement, state DB-first thread listing, telemetry. [^3]: MassGen adds a Codex backend (local/Docker), native tool architecture, and a quick start to try Codex workflows. [^4]: Explains Codex app’s agentic workflow vs IDEs like Cursor and how to use it effectively. [^5]: Documents Windows PowerShell 5.1 ANSI encoding causing Cyrillic rendering issues and workaround considerations.

calendar_today 2026-02-04
openai codex massgen cursor claude-code

Sam Altman: Move Fast on AI Agents or Fall Behind

OpenAI CEO Sam Altman urged enterprises to rapidly adopt AI "workers" and agentic tooling, warning that organizations not set up for this shift will be at a major disadvantage and should expect some work and risk in rollout ([TechRadar coverage](https://www.techradar.com/pro/companies-that-are-not-set-up-to-quickly-adopt-ai-workers-will-be-at-a-huge-disadvantage-openai-sam-altman-warns-firms-not-to-fall-behind-on-ai-but-notes-its-going-to-take-a-lot-of-work-and-some-risk)[^1]). He highlighted accelerating model capability and agent patterns (e.g., tools with computer/browser access) as key to productivity gains and predicted substantial improvement in model quality by 2026. [^1]: Adds: Summary of Altman's remarks on enterprise AI adoption urgency, agentic automation potential (computer/browser access), and expected model improvements.

calendar_today 2026-02-04
openai chatgpt codex cisco ai-agents

Claude Code 2.1.x lands practical speedups and governed multi‑agent workflows

Anthropic pushed a rapid series of Claude Code 2.1 updates (v2.1.26–v2.1.31) that cut RAM on session resume, add page‑level PDF reads, support MCP servers without dynamic registration, enable PR‑based session bootstraps, and ship many reliability fixes [Reddit summary](https://www.reddit.com/r/ClaudeAI/comments/1qvgdc5/claude_code_v21262130_what_changed/)[^1] and [official v2.1.31 notes](https://github.com/anthropics/claude-code/releases/tag/v2.1.31)[^2]. Practitioners also highlight 2.1’s skill hot‑reload, lifecycle hooks, and forked sub‑agents as a foundation for governed, observable multi‑agent workflows—positioning Claude Code as a lightweight "agent OS" for real projects [deep dive](https://medium.com/@richardhightower/build-agent-skills-faster-with-claude-code-2-1-release-6d821d5b8179)[^3]. [^1]: Adds: community changelog for v2.1.26–30 covering performance, MCP, GitHub/PR workflows, and PDF handling. [^2]: Adds: official v2.1.31 fixes (PDF lockups, sandbox FS errors, streaming temperature override, tool routing prompts, provider labels) and hard limits (100 pages, 20MB). [^3]: Adds: perspective on skill hot‑reload, lifecycle hooks, and forked sub‑agents enabling governed multi‑agent patterns.

calendar_today 2026-02-04
claude-code anthropic mcp-model-context-protocol github slack

OpenAI ships Codex macOS app: multi-agent command center with git worktrees and skills

OpenAI introduced the macOS-only Codex app as a "command center" to run multiple coding agents in parallel, isolate work via git worktrees, and extend workflows with a new Skills system—plus a limited-time inclusion with ChatGPT Free/Go and doubled rate limits for paid plans ([OpenAI blog](https://openai.com/index/introducing-the-codex-app/?_bhlid=b040462c226c34eb9531cc536689e69b976397a7)[^1]). Developer docs confirm Apple Silicon support today, a Windows/Linux waitlist, and that API-key sign-in may limit features like cloud threads ([Codex app docs](https://developers.openai.com/codex/app/)[^2]). Reporting adds competitive context against Anthropic’s Code Cowork/Claude Code and notes model guidance (use GPT‑5.2‑Codex for coding) and multi-agent monitoring aimed at centralizing team workflows ([Fortune](https://fortune.com/2026/02/02/openai-launches-codex-app-to-bring-coding-models-to-more-users-openclaw-ai-agents/)[^3]). [^1]: Adds: official product details on multi-agent orchestration, git worktrees, Skills, and rate limit changes. [^2]: Adds: confirms macOS-only (Apple Silicon), Windows/Linux waitlist, and API-key limitations for cloud threads. [^3]: Adds: market context vs Anthropic, enterprise adoption, model recommendations, and multi-agent monitoring pitch.

calendar_today 2026-02-03
openai codex-app gpt-52-codex chatgpt anthropic

Choosing Cursor, Windsurf, or Claude Code for backend workflows

The AI coding stack is bifurcating: IDE-first agents like [Cursor](https://serenitiesai.com/articles/cursor-ai-vs-windsurf-vs-claude-code-2026)[^2] and Windsurf emphasize editor-native control, while [Claude Code](https://rajsarkar.substack.com/p/part-4-cursor-vs-claude-code-two)[^1] is terminal-native and architected for agentic, repo-wide plans and execution—pick based on your team’s primary locus of work (editor vs CLI). Near-term shifts matter: rumors of Anthropic’s Sonnet 5 and OpenAI’s upcoming Codex updates could change cost/throughput and tool hooks, but balance vendor claims against independent evidence that AI boosts can inhibit skills formation and may be uneven across experience levels ([Handy AI](https://handyai.substack.com/p/anthropic-preps-sonnet-5-while-openai)[^3], [ITPro](https://www.itpro.com/software/development/anthropic-research-ai-coding-skills-formation-impact)[^4], [Futurum](https://futurumgroup.com/insights/100-ai-generated-code-can-you-code-like-boris/)[^5]). [^1]: Adds: hands-on analysis contrasting IDE vs CLI mental models and Claude Code’s agentic loop. [^2]: Adds: feature/pricing comparison and trade-offs across Cursor, Windsurf, and Claude Code. [^3]: Adds: rumor timeline on Sonnet 5 and OpenAI Codex/GPT-5.3 rollouts that could shift capabilities. [^4]: Adds: Anthropic fellows’ study showing productivity gains can inhibit skills formation, especially when delegating fully. [^5]: Adds: reality check contrasting 100% AI-code claims with broad empirical findings on actual gains and reliability.

calendar_today 2026-02-03
cursor windsurf claude-code anthropic openai

OpenAI Codex ships macOS app with parallel agents, Plan mode, and higher limits

OpenAI released a macOS Codex app that runs parallel agent threads for long‑running work with built‑in Git/worktrees, skills, automations, and temporarily higher rate limits across app/CLI/IDE for paid tiers ([Codex changelog](https://developers.openai.com/codex/changelog/)[^1]). The latest release enables Plan mode by default, stabilizes personality config, supports loading skills from .agents/skills, and surfaces runtime metrics for diagnostics ([v0.94.0 release](https://github.com/openai/codex/releases/tag/rust-v0.94.0)[^2]). OpenAI is positioning Codex for autonomous, multi‑threaded, complex tasks vs. Claude Code, citing 1M monthly users and 20x growth since August, while community reports mention a large context window (unconfirmed) ([Sources newsletter](https://sources.news/p/openai-takes-aim-at-anthropics-coding)[^3], [Reddit thread](https://www.reddit.com/r/OpenAI/comments/1qu7hii/openai_just_massdeployed_codex_to_every_surface/)[^4]). [^1]: Official feature overview and rate-limit details. [^2]: Release notes (Plan mode default, skills folder support, personality, metrics). [^3]: Press briefing recap with positioning vs. Claude Code and usage stats. [^4]: Community summary noting "trinity" surfaces and context-size claim (unverified).

calendar_today 2026-02-03
openai codex chatgpt anthropic claude-code
Next