Frederic Lardinois
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I write about tech. Sr. Editor, AI at The New Stack.
Articles by Frederic Lardinois
Why Nvidia gave OpenShell to the CNCF
Nvidia this week donated OpenShell, its open-source runtime for securing and governing AI agents, to the Cloud Native Computing Foundation. The teams that run it in production already work with Kubernetes and the CNCF’s other projects, says Ali Golshan, Nvidia’s senior director of AI software, who leads the project. The company announced the move on Tuesday at KubeCon + CloudNativeCon North America in Salt Lake City.
AWS had its agents build a free and open emulator for AWS. They now maintain it, too.
AWS on Wednesday launched an emulator for AWS called AWS Emulator. That, by itself, is interesting and may raise some questions about the future of LocalStack. But what’s maybe most interesting is that the emulator was entirely built by a team of agents and will also be maintained by them going forward.
Anthropic launches Fable 5.2 with a price cut and stronger coding scores
On Monday, Anthropic launched Claude Fable 5.2 and Mythos 5.2, the latest versions of its duo of flagship models. Like before, Fable 5.2 will be available on all platforms today, including Amazon Web Services, Google Cloud, and Microsoft Azure, while direct access to Mythos remains limited to organizations in Anthropic’s Cyber and Life Sciences verification programs.
Meta launches Muse Ember to take on Claude Haiku and GPT-6 Luna
Meta on Monday debuted Muse Ember, a smaller, more efficient multimodal member of its Muse model family. The company is clearly taking a similar approach to the other frontier labs, with a family of models that cover everything from focused, high-volume tasks (think OpenAI’s GPT-6 Luna and Anthropic’s Claude Haiku 5.5) to frontier intelligence like OpenAI’s GPT-6 Astra, Anthropic’s Claude Fable 5.1, and, most recently, Meta’s Muse Wonder Full.
Meta’s best AI model now trains the one most of its users get
Starting on Friday, everyone using Meta’s Muse agent and Meta AI gets new models the company trained using Muse Wonder, its frontier model. Subscribers still get Wonder itself for harder tasks. Meta hasn’t named the new models, though we can assume their codenames don’t involve fruits. The company calls them “specialized” versions of its existing ones that were “trained using Muse Wonder.” They also come with two features the company first introduced with Wonder: Active Memory and Active Focus.
OpenAI’s new GPT-6 Cyber is better at hacking and better at staying in its lane
OpenAI on Thursday launched GPT-6 Cyber, the latest release in its series of cybersecurity-focused models. The company ranks GPT-6 Cyber’s ability to identify vulnerabilities and develop exploits as ‘critical,’ up from ‘high’ for its predecessor. Just like with previous Cyber models, GPT-6 Cyber will not be available to all developers but only to “a select group of approved Daybreak Red customers,” OpenAI says.
Raindrop simulates your agent’s world to catch what your changes break
Raindrop wants developers to know what else will change when they edit an agent’s prompt, swap its model, or give it a new tool. The company, which started out as a monitoring startup for agents (“Sentry for agents” was its early motto), is making its Simulations platform available in public beta on Thursday. An agent’s prompt can depend on feature flags, account details, and the user’s plan, says Ben Hylak, Raindrop’s co-founder and CTO.
Can agent standards keep up with the companies building them?
Mazin Gilbert, executive director of the Linux Foundation’s Agentic AI Foundation, left Google earlier this year to lead the new AAIF, and he recently shared with The New Stack a truth central to its mission: The AAIF has to move faster than its members.
OpenAI built itself a new Git backend, too
OpenAI on Monday detailed how it built a new Git backend for its monorepo to power the ever-increasing number of commits its developers and their agents now create. Pando, as the team calls the new backend, cut push latency by nearly 5x, the company says, and it currently serves close to a petabyte of Git data per day at OpenAI. OpenAI is obviously an early adopter of agentic coding tools.
“I don’t think the world needs a new GitHub”: What GitHub’s leaders really think about their new rivals
At its annual Universe ’26 conference in San Francisco this week, GitHub took to the question of the platform’s stability head-on. The code-hosting company spent a significant part of the event’s keynote to talk about the investments it is making. That includes adding 4 million cores and 160 petabytes of storage, along with a full rearchitecting of its backend infrastructure.
GitHub saw 7.4B commits in September, adding 4M CPU cores and 160 PB of storage to keep up
GitHub is seeing unprecedented demand and is updating its core infrastructure to keep pace. In August, GitHub said it was seeing 2.9 billion commits per month, up from 1.4 billion in April. At its GitHub Universe conference on Wednesday, the company announced that it is now seeing 7.4 billion commits per month. To put that into perspective, developers pushed 65 million monthly commits to the platform in 2024.
Nvidia launches a promptable transcription model
Nvidia on Wednesday launched Nemotron 3.5 Transcribe, its latest multilingual transcription model. The new open-weight model, the company says, ranks first on Hugging Face’s Open ASR open model leaderboard for English, with an average word error rate of 5.33%, and also sits at the top of two speaker-attribution benchmarks. But what’s maybe even more interesting is that this is a promptable transcription model.
Ex-GitHub CEO launches a GitHub rival that reinvents the pull request
Entire, the startup founded by former GitHub CEO Thomas Dohmke, on Monday launched its GitHub alternative that replaces the traditional pull request model with a new agentic code review system called Trails. The company has been launching parts of its platform since it announced a $60 million seed round in February. Early on, Dohmke occasionally noted he wasn’t planning to compete with GitHub.
OpenAI donates Open Responses, its spec for a common LLM API, to the Agentic AI Foundation
OpenAI on Thursday announced that it is donating the Open Responses API specification to the open source Agentic AI Foundation (AAIF). In addition to Open Responses, OpenSandbox, Anthropic’s Agent Skills, and HuggingFace’s OpenEv framework for agent environments are also joining the AAIF. The join other AAIF projects like the MCP and A2A protocols, AGENTS.md (also from OpenAI), the open source AI agent goose, agentgateway, and Agent Router.
Google turns the infrastructure behind Gemini’s agents into a cloud service
Announced on Thursday at the Linux Foundation’s AGNTCon+MCPCon in San Jose, Agent Compute Engine will become available in preview to Google Cloud users later this year. It will provide every AI agent with a hardware-isolated microVM that combines the speed of containers with the security of a sandbox. The idea of agent sandboxes is anything but new, of course. Startups like E2B and Daytona offer them to developers (and support them on any cloud), as does AWS with Bedrock AgentCore.
Nvidia wants AI factories built in real factories
Nvidia wants new AI capacity to show up at the data center fully built. At its GTC Berlin conference on Wednesday, the company introduced DSX POD, a reference design for shipping containers that partners fill with Vera Rubin racks, networking, and liquid cooling before they leave the factory. Installing and wiring up racks in a conventional data center can take months, Nvidia says.
Nvidia bets open models can give enterprise AI agents the context they’re missing
Every enterprise company is currently trying to figure out how to have its AI tools work with its data. Meanwhile, every major enterprise vendor that works with those enterprises (think SAP, Microsoft, Salesforce, Workday, etc.) is making a claim on becoming the central hub for managing and securing that data. But what about the companies that want to do it themselves?
Running local AI models on Microsoft’s Surface Laptop Ultra: What we found
Microsoft is positioning the new Surface Laptop Ultra as an alternative to Apple’s MacBook Pros for creatives and developers — and especially AI developers. Built on Nvidia’s N1X-based RTX Spark platform, with a Blackwell RTX GPU with up to 6,144 cores, a CPU with up to 20 cores, up to 128GB of unified memory, and a price that undercuts Apple, it’s a tempting alternative if you want to run local AI models and also want to have a powerful machine for editing videos and gaming on the go.
Vercel adds always-on workers to run more of your backend
Vercel is giving developers more options for running their backends on its platform. At its Ship conference in San Francisco on Thursday, the company introduced Daemons, a new service for continuously running background workers, and made its Python support generally available. It also made Drives, its persistent storage for AI agents, generally available. Daemons, which is now in public beta, lets developers deploy a container and specify how many instances should run in each region.
Meta ships Muse Spark Open, its answer to China’s best open-weight models
Meta on Thursday launched Muse Spark Open, a new 816B open model (with 42B active parameters) that the company argues is the “most capable US open-weight model to date.” The new model is available through the APIs of Baseten, Fireworks AI, Groq, Modal, Nebius, OpenRouter, and Together AI. And since it’s an open model, you can also download the weights from Amazon SageMaker AI, Google Cloud Model Garden, Hugging Face, and Microsoft’s Foundry Model Catalog.
Nvidia squeezed a 74B agent model into 24GB so it can run on your laptop
Nvidia on Thursday announced a few new additions to its Nemotron family: Nemotron 3.5 Super VL, a 120B vision-language model for enterprise agents and two small Bolt models (Nemotron 3.5 Bolt 74B-A9B 24GB and Nemotron 3.5 Bolt E4B 4GB) for running coding, research, and conversational workloads locally.
Gemini 4 Argon debuts with a unified 1M input/output token limit
Gemini 4 Argon debuts with a unified 1M input/output token limit On Tuesday, Google made Gemini 4 Argon, the company’s new flagship model, available to developers on the paid tier of the Gemini API through Google AI Studio, as well as in several of the company’s other developer and consumer tools. Google announced the model on September 30.
Workday goes headless, opening its HR and finance data to outside AI agents
Workday is opening up its platform and allowing developers to build their own HR and finance agents in Claude Code, Cursor, and other tools, as long as those agents follow the same rules as the people using them.
Workday is using TypeSafe’s Jev to build user interfaces on the fly
Workday on Tuesday made Sana, its AI assistant, the new home screen for its HR, finance, and IT software. If you’re not an HR pro, that may not be all that exciting for you, but the way the team built this is maybe one of the most interesting use cases of Jev, TypeSafe’s decision model. Workday is building the user interface on the fly — and all of that is managed by Jev.
Claude can now build your dashboards
A month after OpenAI gave ChatGPT Work a data agent that builds dashboards, Anthropic on Thursday shipped its own version. Claude Dashboards, now in beta, lets users build live dashboards to see the exact queries pulling the data and export those dashboards to popular business intelligence tools. Dashboards connects to enterprise data sources such as Snowflake, Databricks, Amazon Redshift, and ClickHouse, among others.
Anthropic launches Haiku 5.5 at a much lower price
Anthropic on Wednesday launched Claude Haiku 5.5, the first new version of its smallest and most affordable model in nearly a year. That’s Anthropic’s third 5.5 model in a month, though what’s still missing is Fable 5.5. That model, however, will likely go through a much longer review process, so it’s no surprise its launch is taking a bit longer. Like with previous iterations, the company describes Haiku 5.5 as its “fastest and most efficient model,” but this time, it is also much cheaper.
SAP acquires TechWolf to feed more context into its HR agents
SAP on Tuesday announced that it has agreed to acquire TechWolf, a Belgian AI company that maps what employees work on and which skills they use, to feed that data to the HR agents in SAP SuccessFactors. SAP announced the deal at its Connect conference in Las Vegas. The two companies didn’t disclose terms, and SAP expects the acquisition to close in the fourth quarter, pending regulatory approval. It’s worth noting that TechWolf already had a long-running partnership with SAP.
“There is just not a room for error”: SAP is putting its AI agents in the back office
Earlier this year, at its Sapphire conference, SAP outlined its plans for an “Autonomous Enterprise” run in large part by AI agents. This week at Connect in Las Vegas, the company is focusing on how it is actually putting those agents in front of business users. While Sapphire caters to IT, Connect targets the line-of-business practitioners who run finance, procurement, HR, and supply chain operations day to day.
AWS launches a local answer to TypeSafe’s Jev decision model
AWS on Thursday launched Strands Decider 2B, its take on decision models like Jev, Kev, imajev, Laya, and others. TypeSafe’s Jev kicked off the current wave of decision models a few weeks ago, and the major AI vendors are now bringing out their own versions. OpenAI on Tuesday, for example, launched its Decisions API as a limited preview.
Gemini 4 Argon is here: It’s great, and you can’t have it yet
Google on Wednesday announced Gemini 4 Argon, the company’s long-awaited flagship model, and it looks like it was worth the wait. Across most benchmarks, Gemini 4 Argon beats OpenAI’s and Anthropic’s top models, sometimes by a wide margin, though where it trails, it can trail by as much as 10 points.
Microsoft Fabric is where AI agents learn how the business works
Microsoft is turning Fabric, its integrated data platform, into the place enterprise agents go to learn how a company works, whether that’s what happened last quarter or what’s happening on the factory floor right now. On Tuesday, at its FabCon and SQLCon data conference in Barcelona, Spain, Microsoft outlined the next step in its vision for how the products that make up Fabric can simplify all of this information gathering.
OpenAI answers TypeSafe’s Jev with a Decision API built on Luna
With the sudden rise of TypeSafe’s Jev, decision models have become incredibly popular, so it’s not surprising that OpenAI is also announcing its take on this model type at its annual DevDay conference on Tuesday. The company’s new Decisions API is based on the company’s Luna model — the smallest and most affordable model in its current lineup.
OpenAI halves $200 plan allowance, launches $500 plan
OpenAI halves $200 plan allowance, launches $500 plan On Tuesday, OpenAI introduced a new $ 500-per-month Pro plan that gives subscribers the highest included usage of the company’s subscription plans. The new plan includes 25x the usage allowance of ChatGPT Plus and provides access to its Ultrafast tier for GPT-6 Astra — which promises to generate tokens at up to 8x the standard speed in Codex. Ultrafast for GPT-6.1 Sol is coming soon.
OpenAI’s new GPT-6.1 Sol undercuts its own Astra flagship
OpenAI on Tuesday launched GPT-6.1 Sol, the newest version of its workhorse model, only a week after launching GPT-6 Sol.
Anthropic launches Claude Sonnet 5.5 with near-Opus performance at half the price
Anthropic on Monday launched Claude Sonnet 5.5, the latest version of its workhorse model and the second model in the Claude 5.5 family (after Opus 5.5, which launched last week). A new version of Claude Haiku, the smallest and most affordable model in the family, is on the roadmap and will launch “in the coming weeks.” The new Sonnet model, Anthropic says, generates output more than 30% faster than its predecessor, Sonnet 5, while lowering the cost per task by up to 30%.
Nvidia launches Open Agent Safety Platform to lock down rogue AI agents
OpenAI, Anthropic, Meta, and Google have all recently disclosed that their models broke out of their test environments and reached real systems. Nvidia’s response, announced Monday, is a runtime that locks agents into kernel-enforced sandboxes and a watchdog on its own silicon that can shut them down.
OpenAI releases GPT-6 Sol and Luna — and cuts token prices in half
OpenAI on Tuesday released GPT-6 Sol and Luna, which will complement the flagship GPT-6 Astra model in OpenAI’s lineup. As of now, there is no GPT-6 Terra. The headline news here is that OpenAI cut the price per million input/output tokens by half or more, compared to the previous version. GPT-6 Sol will cost $2/$10 per million input/output tokens (vs. $4/$20 for GPT-5.6 Sol), and GPT-6 Luna will come in at $0.10/$0.50 (vs. $0.20/$1.20).
Harness rebuilt its Git repository for nonstop AI agent traffic
As one of Harness’s field CTOs, Martin Reynolds spends much of his time asking engineering leaders one question with no easy answer. It’s how they’re keeping up with all the pull requests their coding agents now produce. One of them recently answered with two words, “we’re not,” and explained that his team’s threshold for pushing code into production had dropped, Reynolds tells The New Stack.
OpenAI launches GPT-6 Astra and says welcome to the “AGI era”
OpenAI on Thursday launched GPT-6 Astra, its newest flagship model. The company describes it as “the world’s most intelligent and aligned model,” and as far as the benchmarks go, that seems about right. During a press briefing ahead of the launch, OpenAI President Greg Brockman took things a bit further than the benchmarks, though. After acknowledging that AGI remains a “gray, fuzzy thing,” he suggested future observers might look back at Astra as the model that marked its arrival.
Nvidia PAIR lets you put your idle Macs and PCs to work for AI agents
Nvidia’s bet on open models and local AI has been taking shape for a while now. Its acquisition of Hugging Face will only accelerate that, but on the product level, too, the company is making some headway in getting more potential users to run AI models on their machines.
Google ships its third Gemini Flash model in six weeks
Google hasn’t released a Gemini Pro model in a while, but on Wednesday, the company launched yet another set of Gemini Flash and Flash Cyber models. Even though Gemini 3.7 Flash is only three weeks old (and this is Google’s third Flash release in six weeks), the new Flash model often outperforms it by quite a margin, especially on agentic coding tasks and agentic computer use. Like before, Flash 3.8 will be available at $0.75/$3.75 per million input/output tokens.
Anthropic’s Fable 5.1 is a bit cheaper, a bit smarter, and refuses a lot less
On Tuesday, Anthropic launched the latest versions of its flagship Fable and Mythos models. Anthropic promises that the updated models will offer stronger performance at a lower cost, largely because the company is reducing cache read pricing.
Meta just beat OpenAI and Google at real-time transcription
Meta’s Superintelligence Labs on Tuesday launched Muse Voice Transcribe, a new real-time speech recognition model that, on some benchmarks, outperforms virtually every other comparable model for real-time speech processing. Meta’s lab describes the model as its first “real-time audio perception model.” With Muse Spark, the company also recently shipped another speech-to-text capable model, though not one that specializes in this use case.
Google’s new forecasting model beats everyone. You can’t use it at work (yet).
On Monday, Google launched TimesFM-3, a 330-million-parameter time-series forecasting model trained on over a trillion real-world and synthetic data time points. The new model is now available on Hugging Face under a non-commercial license. Large language models are great at predicting the next word. For businesses, time-series forecasting models essentially try to do the same thing, but for data. Over the last few years, there’s been a lot of work in building better forecasting models.
Z.ai’s GLM-5.3 goes open weight, but its new license aims at hyperscalers
Earlier in August, Z.ai, the Chinese AI lab behind the viral ox-alpha model that turned out to be GLM-5.3-Flash, launched its flagship GLM-5.3 model. On Friday, the company made the model’s weights available on Hugging Face, which Nvidia may soon own. Several third-party inference services already host it and make it available on services like OpenRouter, which Stripe will soon own.
This duck will teach you reinforcement learning — and pick up your socks
You could have a mechanical duck waddling through your home before Christmas. Hugging Face‘s Pollen Robotics on Thursday opened pre-orders for the Microduck, a $399 (introductory) bipedal duck-adjacent robot that can walk, waddle, and use roller-skates(!), with a beak to pick up objects. And when it falls, it can get back up, too. The company expects to make the first deliveries of the Microduck before Christmas. It’s available in North America and Europe.
Anthropic’s Claude now has a browser of its own
Anthropic is giving Claude its own browser. As the company announced on Wednesday, Claude on the desktop (Mac, Windows, and Linux) now has access to a built-in Chromium-based browser in Cowork that allows it to surf the web right where you’re already doing your work. This finally puts Anthropic’s Claude desktop app in line with OpenAI, which recently gave up its ambitions to build Atlas, its stand-alone browser, and instead added it to its ChatGPT desktop app.
Anthropic’s Claude now has a browser of its own
Business Technology 1 day ago Salesforce just put its entire CRM inside Claude — and says you’ll never need its app again VentureBeat - Michael Nuñez • 1d Salesforce and Anthropic announced Tuesday a sweeping expansion of their partnership, called Claudeforce, that pushes the world's largest customer relationship management platform directly inside Claude — a tacit acknowledgment that the future of enterprise software may not involve enterprise … Technology 7 hours ago Bill Gates Warns...
Z.ai’s GLM-5.3-Flash is cheap, good, and served on Chinese chips
Z.ai's GLM-5.3-Flash is cheap, good, and served on Chinese chips Ox-alpha, the stealth model that quickly became the most popular model on OpenRouter in the last few days, is actually Z.ai’s GLM-5.3-Flash, a 320 billion-parameter hybrid model (with 18 billion active parameters) that the team specifically trained for ultra-low-cost inference. On Wednesday, Z.ai unmasked the stealth model and made its weights available on Hugging Face under the MIT license.
IBM’s new Granite 4.2 models add reasoning and stay dense
On Tuesday, IBM launched the latest family of its open-weight Granite large language models (LLMs). Weighing in at 3 billion, 8 billion, and 30 billion parameters, IBM is taking a very different approach to model building from some of the competition here, with dense, decoder-only reasoning models that it pre-trained from scratch. Many recent models have moved from all-attention Transformers toward hybrid Mamba/attention architectures, including Nvidia’s Nemotron 3 family.
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