OpenAI releases analysis preview GPT-5.3-Codex-Spark for ChatGPT Professional customers
GPT-5.3-Codex-Spark is a light-weight model of the corporate’s coding mannequin, GPT-5.3-Codex, that’s optimized to run on ultra-low latency {hardware} and might ship over 1,000 tokens per second.
It’s the first final result of the corporate’s just lately introduced partnership with Cerebras so as to add 750MW of extremely low-latency AI compute. OpenAI says the explanation it’s being launched as a analysis preview is to offer builders with the chance to begin benefiting from this partnership whereas the corporate continues ramping up Cerabras in its information facilities.
“Codex-Spark is our first mannequin designed particularly for working with Codex in real-time—making focused edits, reshaping logic, or refining interfaces and seeing outcomes instantly. With Codex-Spark, Codex now helps each long-running, bold duties and getting work executed within the second. We hope to be taught from how builders use it and incorporate suggestions as we proceed to increase entry,” OpenAI wrote in a submit.
GitHub begins technical preview for Agentic Workflows
GitHub Agentic Workflows enable builders to explain the result they need in plain Markdown, add it as an automatic workflow to their repository, and have that be executed as a coding agent in GitHub Actions.
Agentic Workflows run as commonplace GitHub Actions workflows that may have extra guardrails for sandboxing, permissions, management, and assessment. Moreover, they assist quite a lot of coding agent engines, together with Copilot CLI, Claude Code, or OpenAI Codex.
“The usage of GitHub Agentic Workflows makes totally new classes of repository automation and software program engineering doable, in a approach that matches naturally with how developer groups already work on GitHub,” GitHub wrote in a submit.
Google provides Automated Opinions to Conductor within the Gemini CLI
Conductor is a Gemini CLI extension that helps convey extra improvement context into the terminal, and the brand new Automated Assessment characteristic generates a post-implementation report after the agent completes its coding duties. Findings are categorized by severity (low, medium, and excessive) in order that builders can prioritize the place to iterate first.
“This stage of element ensures that “agentic” improvement doesn’t imply ‘unsupervised’ improvement. As a substitute, it creates a workflow the place the AI offers the labor and the developer offers the high-level architectural oversight, backed by automated verification,” Google wrote in a weblog submit.
Moreover, Google introduced that Gemini CLI extensions will now have the ability to outline settings that the consumer shall be prompted to offer when putting in an extension. By offering issues like API keys, base URLs, and undertaking identifiers upfront, customers will hopefully have fewer configuration errors to troubleshoot when working with the Gemini CLI, the corporate defined.
Google upgrades Gemini 3 Deep Suppose mode
In keeping with Google, the upgraded mannequin options enhancements throughout math and programming reasoning, in addition to particular scientific domains like chemistry and physics. It obtainable for Google AI Extremely subscribers within the Gemini app, and for choose researchers, engineers, and enterprises within the Gemini API for the primary time.
“We up to date Gemini 3 Deep Suppose in shut partnership with scientists and researchers to sort out powerful analysis challenges — the place issues usually lack clear guardrails or a single appropriate answer and information is commonly messy or incomplete. By mixing deep scientific data with on a regular basis engineering utility, Deep Suppose strikes past summary concept to drive sensible functions,” Google wrote in a submit.
GitHub Copilot testing for .NET is now usually obtainable
Now obtainable in Visible Studio 2026 v18.3, the testing characteristic permits builders to generate unit assessments inside their IDE. The corporate added new capabilities to coincide with this GA launch, together with deeper IDE integration, extra pure prompting, and new methods to invoke the testing expertise.
The group plans to focus subsequent on getting it to deal with extra superior testing requests, which can contain addressing necessities like permitting builders to make clear intent, affirm assumptions, and assessment proposed plans earlier than producing assessments.
“Normal availability is a vital milestone, however it’s not the tip of the journey. We proceed to run consumer research and collect suggestions to grasp how builders use GitHub Copilot testing for .NET in real-world situations, particularly as requests develop in dimension and complexity,” Microsoft wrote in a weblog submit.
Anthropic raises $30 billion in Collection G funding
This newest funding spherical was led by GIC and Coatue; co-led by D. E. Shaw Ventures, Dragoneer, Founders Fund, ICONIQ, and MGX; and had participation from 30 different buyers. As of this spherical, Anthropic is now valued at $380 billion post-money.
In its announcement, Anthropic additionally revealed that its run-rate income is now $14 billion, and it has grown by 10x yearly since its first funding spherical three years in the past.
“Whether or not it’s entrepreneurs, startups, or the world’s largest enterprises, the message from our clients is identical: Claude is more and more changing into important to how companies work,” mentioned Krishna Rao, chief monetary officer of Anthropic. “This fundraising displays the unbelievable demand we’re seeing from these clients, and we’ll use this funding to proceed constructing the enterprise-grade merchandise and fashions they’ve come to rely on.”
