Dozens of former Apple employees now working at OpenAI have been put on notice after Apple reportedly sent legal letters ordering them to preserve documents and communications relevant to its trade secrets lawsuit against OpenAI.
The Financial Times reports that “around 40” employees have been targeted with these letters, which repeat Apple’s claim that its confidential information might have been exfiltrated, alleging “trade secret misappropriation and breach of contract.” The letters also require them to arrange to meet with Apple’s lawyers.
The underlying lawsuit
This comes on the heels of Apple’s explosive lawsuit against OpenAI in which Apple accused the AI company (and former Apple Vice President Tang Tan) of extensive coordinated data theft. Tan was at Apple for 24 years and is now Chief Hardware Officer at OpenAI.
Apple’s lawsuit is defined by claims OpenAI took a range of steps to pry confidential Apple data from existing Apple employees, including using information such as internal project code names, to gain even more knowledge during interviews. The company says the evidence it has presented so far is only the “tip of the iceberg” concerning OpenAI’s approach.
The lawsuit requests that OpenAI be prevented from using any Apple information during the development of its hardware. Apple is also seeking damages and suing two former employees for breach of contract for violating their employment agreements.
The letters are significant. They represent formal directives that require former Apple staff to preserve documents, messages, emails, and other communications that could be relevant to the case. The demand reflects Apple’s belief that the alleged misuse of confidential information could be more widespread across the competing company. What’s critical is that orders of this kind override any standard data destruction policy and deletion of the requested information becomes a legal offense.
Why this matters beyond the protagonists
In making its move, Apple shows this is not a dispute about just one or two hires, but an attempt to constrain the movement of intellectual property between the two firms. With AI hardware emerging as the next major battleground in tech, the case could become a defining one; whatever resolution is eventually reached could define the extent to which former employees can carry experience and knowledge between competing firms. The case might also define what the line is between experience and knowledge and the sharing of trade secrets.
This is important, because modern hardware development relies on far more than just finished designs. Product design leans into supplier relationships, manufacturing assumptions, physics, extensive prototyping, and product-roadmap priorities. If courts treat those accumulated insights as protectable secrets, hiring between major technology companies could become far more legally sensitive.
The Jony Ive question
The case comes as Apple prepares to combat OpenAI in hardware. Its competitor is now working with legendary former Apple designer Jony Ive. Ive is not named in the litigation, but Apple will be keen to find out whether confidential product knowledge, design processes, or supply-chain insights have travelled with former staff into OpenAI’s device work.
Ultimately, for Apple, it’s about protecting its many blueprints for whatever hardware the company expects will come after the iPhone.
For its part, OpenAI has refuted Apple’s lawsuit, arguing that it is “not aware of any evidence” that the lawsuit has merit. “We have no interest in other companies’ trade secrets,” said OpenAI spokesperson Drew Pusateri. “We remain focused on building innovative technology that empowers people everywhere.” The company’s lawyers also claim it did respond to Apple’s initial inquiries on the matter.
What’s at stake
The significance of Apple’s newly-shared communication preservation orders is that if discovery uncovers evidence supporting Apple’s claims, the case could complicate OpenAI’s hardware plans and create unwelcome scrutiny ahead of any future public offering.
China has created an international organization to set standards and introduce regulation for AI, inviting 28 other countries to join — but the US, a leading AI powerhouse is not part it.
The World Artificial Intelligence Cooperation Organization (WAICO) was established by 29 countries, including China, Russia and Brazil, at a ceremony in Shanghai, China, on July 16. Notably absent are the US, the European Union and its member states, the UK, Japan and South Korea.
WAICO has been some years in development and has been designed to set some universal guidelines in AI. Researchers say WAICO differs in three ways from other initiatives to create global AI organizations: membership open to any sovereign state, there is no regime-type test for entry, and its agenda is built around development and the global capability divide.
The signing ceremony to create WAICO comes just days after Demis Hassabis, CEO of Google DeepMind, called on the US to take a lead in global AI regulation. “The US is well-positioned to take the first step in developing such a framework. It could establish a new Standards Body modelled on a federally overseen public-private partnership or self-regulatory organization, much like the Financial Industry Regulatory Authority (FINRA), with a board that includes independent leading technical experts and open-source representatives,” Hassabis wrote.
This is Apple’s biggest US procurement deal so far, but it won’t be the last; when it announced the arrangement, Apple confirmed it is, “working with the administration and businesses across the US to help create an end-to-end silicon supply chain in America.”
That statement implies that the 15 billion chips Broadcom will produce won’t be the only processors in Apple devices to carry tiny little “Made in the USA” slogans. Broadcom is making custom silicon components and wireless connectivity technologies such as RF/wireless chips (Wi-Fi, Bluetooth, cellular, FBAR filters) and ASIC work, rather than application processors. But they are still chips for Apple devices.
TSMC doubles down
That’s why it is significant that TSMC confirmed plans to extend its own manufacturing in America. It already has a $165 billion US commitment; now, it is investing an additional $100 billion in four more chip plants — including one dedicated to churning out the company’s most advanced 2nm (and smaller) processors.
“We believe this investment will help to further foster the development of the US semiconductor ecosystem, strengthen the supply chain, and support an increasing number of high-tech, high-paying jobs in the United States,” CEO C.C. Wei told analysts.
TSMC has also confirmed plans to invest in packaging facilities for processors, which is basically the process where memory, processor, and networking nodes can all be combined and packaged on the chip. That sort of packaging is needed to make the final SoC chip. That means TSMC factories in the US will be able to churn out the advanced processors used in Apple’s current and, presumably, future devices.
The bill so far
That’s three investments — in processor manufacturing, packaging, and Broadcom radios and chips — all of which are strategically important to Apple devices. TSMC makes the brains, Broadcom brings the connectivity. Total value so far: $295 billion, around 1.5 times Apple’s annual revenue in the Americas.
It isn’t all about Apple. TSMC has other clients, and Apple is no longer the company’s biggest customer thanks to the drive to AI. But it is still an important one. That means at least some of TSMC’s newly invested US manufacturing capacity will be dedicated to making chips for Apple. The open question is how much US-manufactured chips will cost in contrast to those made elsewhere.
It’s bigger than two deals
These aren’t the only chip-focused partnerships Apple has made domestically. Apple’s American Manufacturing Program (AMP) launched in August 2025 as part of a $600 billion four-year US investment commitment. TSMC and Broadcom were both named AMP partners, but they weren’t alone, and some arrangements have already been announced:
GlobalFoundries is bringing mixed-signal chip manufacturing to make advanced ICs for Face ID.
Texas Instruments expanded production for analog/power chips.
Samsung is making a new chip-making process at its Austin, TX fab, described by Apple as having “never been used before anywhere in the world.”
Applied Materials is making chip manufacturing equipment under AMP.
Bundle all these deals together and it’s crystal clear that Apple’s $600 billion investment is at least in part focused on the technologically advanced components on which its devices are built. These components also have the advantage in being incredibly small, which means they are easy and cheap to ship for final assembly at increasingly automated final production locations worldwide.
So, is it coming home?
That’s the strategy: keep the high-value, hard-to-automate work — and the jobs it requires — in America, while leaving final assembly flexible enough to go wherever that makes sense now or in the future. Is Apple bringing manufacturing home? Partially, in that the bits that matter the most — brains and networking— are coming back, even if assembly is not.
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Google DeepMind CEO Demis Hassabis is pushing for the US AI industry to self-regulate, with the support of government, as a starting point for an international creating shared international standards. In a blog post, he called for a focus on artificial general intelligence (AGI) and national security.
But it is precisely that focus on national security that may make the results of such an effort, assuming it happens, less than palatable outside of the US.
“The rapid progress we’re seeing in AI requires a new approach to testing frontier AI model capabilities that is dynamic, adaptable, and rigorous,” Hassabis wrote. “The US is well positioned, given its economic and technical standing, to take the first step in developing such a framework. It could establish a new Standards Body modelled on a federally overseen public-private partnership or self-regulatory organization, much like the Financial Industry Regulatory Authority (FINRA), with a board that includes independent leading technical experts and open-source representatives.”
He noted, however, that the funding would need to be substantial, and would most likely come from industry, to allow the new body to attract world-class technical talent and obtain the necessary compute resources for large-scale testing.
Hassabis proposed that the organization “be responsible for developing assessment protocols and working with appropriate federal agencies and the US National Labs to conduct testing in areas relevant to national security,” and that AI vendor participants be encouraged to adopt best practices such as publishing model cards with technical details, maintaining strong internal cybersecurity, vetting key personnel, and providing sufficient resourcing for safety and security research.
DeepMind was involved in an earlier US government initiative evaluating AI safety, alongside Microsoft and xAI (now SpaceXAI) working with the Center for AI Standards and Innovation (CAISI), a division of the US Department of Commerce. It allowed CAISI to conduct pre-deployment evaluations and targeted research to “better assess frontier AI capabilities and advance the state of AI security.”
The rest of the world may have concerns
Analysts and consultants were mixed about the move, with most expressing concerns about whether an industry-focused group would prioritize the public’s best interests.
“Self-regulation is not viable because it implies everyone is able to regulate themselves and will do so in line with the best interests of the public. Most tech vendors don’t have the capacity to self-regulate. They would just prefer a set of rules within which they can operate,” said Gartner VP analyst Nader Henein. “For-profit organizations are required to do what is best for their shareholders, and external regulation ensures that those organizations are never in a conflict of interest where they have to choose between what is good for their shareholders and what is good for the public.”
And, said Sanchit Vir Gogia, chief analyst at Greyhound Research, given the international nature of AI models, an effort coordinated by the US government might alienate other countries.
“National security is the proposal’s accelerator in Washington and its poison pill abroad: the framing that opens the only gate available at home invites foreign capitals to read the institution as an instrument of American strategy,” he pointed out.
“The map is already plural,” he said. “Brussels switches on enforcement powers over general-purpose models [starting in August 2026], London runs the AI Security Institute, and Beijing licenses on its own terms. California and New York have legislated for frontier models at home. The durable route is shared technical evidence with sovereign enforcement, sealed through mutual recognition rather than deference, with India and the other major non-Western markets holding authorship rather than seats.”
Gogia added that the rules enacted by even such a group may not address all of the key concerns of enterprise IT. A US government effort along the lines that Hassabis is proposing would result in testing that “sits close to intelligence and industrial policy, and those functions will not stay neatly separated. A model can pass every catastrophic-risk test and still fail the enterprise on privacy, reliability, and liability,” he noted.
Walmart’s former director of cybersecurity Steven Eric Fisher, who is now an independent cybersecurity consultant, said he found the proposal “well-intentioned, but it addresses a highly polarized topic at a time when commercial interests carry unprecedented political influence, which is not always applied benevolently.”
He added, “an exclusive US standard that is not globally respected or enforceable would likely fail to achieve its core purpose and would place US companies at a competitive disadvantage.”
Aman Mahapatra, chief strategy officer for Tribeca Softtech, a New York City-based technology consulting firm, said that a deep dive into how FINRA operates today is illustrative of what IT leaders can expect from this effort, assuming the industry adopts that model.
“When the CEOs of the five companies that would be regulated are also the primary drafters of the standards, the standards will reflect those companies’ interests. FINRA has an independent board, but the operational reality is that member firm perspectives dominate the working groups that write the actual rules,” he said. “There is no reason to expect an AI equivalent to work differently, and every reason to expect it to work worse, because AI standardization is happening faster than any industry has ever attempted to standardize itself, and speed is the enemy of independent oversight.”
Carmi Levy, an independent technology analyst, was even more emphatically opposed to the Hassabis proposal.
“Asking Big Tech companies to self-police is analogous to allowing foxes to guard the henhouse. It hasn’t worked to date, and it won’t work going forward. Expecting these organizations to somehow change their ways at this point in time represents the height of naïve thinking,” Levy said. “The framework proposed by Demis Hassabis is a self-serving roadmap for an industry bent on racing to the AI horizon regardless of the harms caused along the way. It is impossible to quantify the dangers to broader society should frameworks allowing self-regulation become the norm.”
Some love the proposal
An almost completely opposite stance came from Yuri Goryunov, CIO of consulting firm Acceligence, who applauded the proposed move.
“This is one of the rare setups where industry self-regulation has a real shot, and enterprise IT should be enthusiastically rooting for it,” he said. “It fails when harms are externalized, such as in social media content moderation. Or when the overseer outsources judgment to the overseen, such as the FAA’s delegation to Boeing before the 737 MAX. It works when everyone in the industry shares the catastrophic downside.”
He suggested, however, that the best precedent here isn’t FINRA, it’s INPO, the Institute of Nuclear Power Operations, which the nuclear industry created within months of the 1979 Three Mile Island partial reactor meltdown “on the logic that an accident anywhere is an accident everywhere. INPO peer-reviews every US plant, its evaluations move insurance premiums, and it sits on top of the NRC’s statutory floor. That is a public-private stack very close to what Hassabis is describing. Frontier AI has the same structure: one lab’s catastrophic failure brings regulation down on all of them.”
For enterprise CIOs and other IT executives, Goryunov said, that model has the potential for being a big win.
“Today, every enterprise duplicates the same AI diligence of red-teaming, eval suites, governance committees and each does so with less information than any certifying body would have,” Goryunov said. “A credible standards regime does for AI what UL did for electrical equipment and SOC2 did for cloud: it converts an unknowable risk into a procurable product and gives boards a defensible standard of care. That’s not red tape. That’s peace of mind with an audit trail.”
However, Mahapatra said, “the countervailing view is that the alternative to industry-led standards is probably not thoughtful legislation. It is probably no standards, or state-by-state fragmentation, or the current pattern of ex-post enforcement actions where regulators surface concerns years after harm has already occurred.”
Thus, he noted, “Hassabis is making the reasonable argument that imperfect fast standards are better than perfect slow ones, and there is genuine merit to that view for topics like agent identity, evaluation methodology, and interoperability, which are exactly the areas OpenClaw is also targeting.”
When Apple sued OpenAI last week, the argument it made was that former employees had stolen Apple data and then used it to benefit OpenAI.
The technical details — an employee used “a rare, previously unknown authentication bug to access Apple’s shared network folders” — are interesting. But the larger story is Apple’s ridiculous attempt to stop its people from using anything they learned at Apple in other jobs.
“Hiring managers don’t mind some files being brought into the org during onboarding, but suddenly take umbrage when that same employee exits with some files later on,” said Mike Wilkes, enterprise CISO at Aikido Security. “Legal should be equally concerned about both events.”
The lawsuit focused on Chang Liu, an employee who had been recruited to work at OpenAI after working at Apple for eight years as a Senior System Electrical Engineer. The full text of the filing depicts a comedy of errors by Apple, offering the perfect “do not do” list of handling employee resignations — especially when they’re going to a direct competitor.
“When Apple contacted Mr. Liu to sign Apple’s confidentiality reminder, schedule an exit interview, and confirm that he had returned his devices and complied with other exit procedures, Mr. Liu did not respond.” And “after leaving Apple, Mr. Liu failed to return an Apple-issued work laptop that he had previously authenticated to Apple’s network.”
First, typical procedure for handling departures is to tie the return of all equipment and the signing of documents to any final payments. With Apple, that is likely to be a large amount of money. The lawsuit does not say whether Apple exerted any financial pressure on their employee for compliance.
But in terms of equipment with high-level access, why weren’t all privileges revoked, both for the employee and any and all company-issued devices? Did they not maintain a remote-wipe capability for these devices? Although remote-wipe is usually used when devices are missing or stolen, it should work as well when a departing employee refuses to return company equipment.
According to Apple, Liu apparently had help at Apple from Tang Yew Tan, who was supposedly also interviewing with OpenAI. “While employed by OpenAI, [Liu] accessed and used his former colleague’s Apple-issued work computer that was authenticated to Apple’s network, without Apple’s authorization.”
Apple tried to make much of this Liu’s fault. Legally, yes, there might be liability there; still, Apple made itself look as if it couldn’t protect its own data. “Upon discovering that he had this unauthorized access to Apple’s systems, [the former employee] did not report it, return his stolen Apple-issued work laptop or delete the program that allowed the access.”
Really, Apple? Your data-protection plan relies on ex-employees to “delete the program that allowed the access”? I’m not so sure you didn’t bring some of this data-leakage on yourselves.
This gets worse: “Over several weeks, while developing hardware for OpenAI, Mr. Liu surreptitiously accessed and downloaded dozens of Apple’s confidential hardware-related files, including voluminous, detailed information about unreleased products, engineering presentations, technical specifications, and proprietary project data.”
Setting aside the issue of privileges, access, and unreturned equipment that apparently had its own privileges, that statement points to massive data exfiltration from Apple systems. Even if it is coming from a current employee, why didn’t that raise any red flags?
Let’s get back to the broader implications. When professionals move from one company to another, they — of course — are bringing their experience and knowledge with them. Can Apple reasonably tell them that they can’t do so? Isn’t that experience and knowledge exactly why another company would want to hire them?
Now, to be sure, stealing diagrams and product spec sheets is a clear violation. Let’s say Apple spent a lot of money on some hardware research projects. A member of that technical team would learn an awful lot, all on Apple’s dime.
But is it fair and reasonable for Apple to say that the former employee can’t leverage that knowledge at his or her next job?
This brings us back to the point Wilkes made: If Apple is going to try to prevent any former employee from leveraging on-the-job experience, then it should instruct all new employees not to use anything they learned in a previous job.
That would be ridiculous. Companies pay for experienced talent because of that experience. Why pay for expertise if you insist employees not leverage any of it?
Then there’s the amorphous nature of knowledge. So, it’s wrong to take detailed diagrams and spec details and hand them over to a new employer. But what if that worker heading out the door memorizes the documents (photographic memory) a day before resigning? Is a person prohibited from using something from memory?
There’s also the fruit-of-the-poisonous tree legal argument. Even if a former employee doesn’t directly use stolen data, what if their knowledge leads to other money-saving insights for the new employer?
Given that Apple hires as many specialists as it loses to rivals, wouldn’t it make sense to leverage everything your workforce knows and then let new employers do the same? But before you do that, Apple, tighten your exiting employee tech controls.
Then maybe you wont’t have to file lawsuits like this down the road.
The partnership, a first of its kind for the artificial intelligence company, will use the prediction market’s data to power some search results about the soccer tournament.
The lovefest from Musk’s conservative fans completely overlooks the unscrupulous tactics behind his immense wealth
For 12 glorious days in June, Elon Musk experienced something nobody else in the history of humankind has ever experienced: trillionaire status.
Did all those zeros make Musk happy? Did the army of children he has sired love him more? Did he find inner peace? We’ll never know because Musk was dragged back to being a boring old billionaire last Wednesday, after shares in Tesla and SpaceX plunged amid a broader tech sell-off.
The experimental app, internally called “Arena,” would be independent of Facebook and Instagram. It could compete for attention with Polymarket and Kalshi, the biggest prediction markets.
The app would be independent of Meta's other social media offerings, although sources told the NYT that those social sites could direct users to engagement with the app.
The US government decision to force Anthropic to close down its latest and greatest AI models, Fable 5 and Mythos 5, was only the next step in a burgeoning battle between AI providers and ignorant politicians.
Anthropic was on top of the world. Its Mythos 5 LLM had everyone excited. (If you believe the hype, it was kind of scary, too.) Even Anthropic CEO Dario Amodei admitted — or boasted? — that Mythos would bring an “enormous increase in the amount of vulnerabilities, in the amount of breaches” to us all. But with that fear came the promise of more AI power than ever.
Then, the roof caved in.
On June 12, the US Commerce Department used its export-control powers to demand that Anthropic cut off access to its Fable 5 and Mythos 5 models for all foreign nationals, citing national security concerns and fears of jailbreaks. After figuring out it had no way to do that, Anthropic pulled both of its newest frontier AI models offline worldwide.
Just what an AI company needs! All other Claude models, like the Opus and Sonnet series, remain online. But, come on, AI sales are all about the newest and most powerful models.
Of course, this isn’t the first time US President Donald J. Trump and company have tried to put a spoke in Anthropic’s wheels. Back in February, Anthropic refused to give Defense Secretary Pete Hegseth the power to use its models to spy on American citizens and to power autonomous weapons.
This go-around, it wasn’t because Anthropic refused to kowtow to Trump’s officials. It was, they say, out of fear that these new models could be used to attack American interests.
Mind you, no one in Trump’s regime has the tech chops to know just how dangerous, or not, any AI model is. As I recently noted, Trump’s AI executive order has no teeth. Nor, more to the point, is there anyone in the administration with a clue about AI.
Specifically, at the Department of Commerce, neither Commerce Secretary Howard Lutnick nor William Kimmitt, undersecretary of commerce for international trade, knows a thing about AI. Just what we need, more political hacks deciding tech policy.
So, how did they discover that Fable and Mythos were theoretically a danger to the US? Good question. According to The Wall Street Journal, it was Amazon CEO Andy Jassy who told the Trump administration that Fable was untrustworthy. Guess what? AWS offers its own full cloud AI stack, starting with Amazon Bedrock for foundation models, Amazon SageMaker for training and deployment, and a growing set of agentic AI tools and services.
In other words, Amazon is not a neutral party; it’s a competitor. Funny, that.
Sure, Amazon also has partnerships with Anthropic. But, in case you haven’t noticed, all the big AI companies are in bed with each other. That doesn’t stop them from fighting. What’s heating this up is that the AI companies are no longer offering flat-rate subscriptions and are replacing them with far more expensive, token-based pricing schemes.
Armed with this information, Commerce gave Anthropic 90 minutes to fix its “problem.” Right. AI development is fast, but it’s not that fast. In addition, according to Anthropic, officials haven’t spelled out exactly what’s wrong. They only know that Commerce claims there was a “narrow, non‑universal jailbreak” in Fable.
That’s it. That’s all.
Anthropic has also observed, with reason, that similar jailbreaks are possible on other leading models, like OpenAI’s GPT‑5.5. Those others, however, haven’t been hammered with comparable export controls.
The AI and security experts who do have an AI clue believe Commerce is behaving stupidly. (You won’t get any argument there from me.) For example, in an open letter, “On Transparent AI Cyber Protections,” they said Commerce’s directive “has taken the best models away from defenders, created market uncertainty, and risked America’s AI leadership without any real risk to justify it,” warning that pulling capabilities “away from defenders without a good reason when our adversaries are rapidly advancing is dangerous.”
Exactly so.
Besides, as Alex Zenla, co-founder and CTO of security company Edera, observed, Fable’s capability to identify insecure code sections is the baseline for any model you’d trust to write secure code. The same capability exists in GPT-5.5, Opus, Sonnet, and Kimi 2.7 — it’s not unique to Fable. Pulling Fable from defenders doesn’t remove the capability from the threat landscape. It just removes it from the people trying to build safer systems.”
This is not about AI safety or security.
What this is really about is opening a new front in Trump’s war against the liberal-leaning Anthropic. Mind you, Anthropic isn’t really liberal. This has more to do with Anthropic not following in other tech firms’ groveling to Trump.
However, Trump doesn’t seem to realize that by essentially shutting down Anthropic’s biggest move to date, he’s also telling the world that they can’t rely on American AI companies down the road. Sure, in the short run, this hurts Anthropic. In the long run, it’s going to be another reason for Europe and other countries — taking digital sovereignty seriously — to avoid doing business with any American tech company.
In the meantime, Anthropic and Trump administration officials are in tense talks over whether, and under what safeguards, the models could return to the marketplace. Commerce indicates it might allow a narrower relaunch if jailbreak issues are resolved and additional controls are in place — whatever those might be.
Since it’s really all about massaging Trump’s ego, I’m not feeling terribly optimistic. Just ask Israeli Prime Minister Benjamin Netanyahu how well letting Trump set the terms of engagement goes. It’s not pretty.
With the market capitalization of AI companies soaring, US Senator Bernie Sanders is looking to give the American people a piece of the action.
The veteran senator for Vermont has introduced the American AI Sovereign Wealth Fund Bill, aiming to give the public a 50 percent ownership in the largest AI companies in the US. It’s a timely move with both OpenAI and Anthropic preparing for the imminent IPOs.
Sanders is not the only one pondering such a move. As the bill notes, OpenAI has proposed the creation of a “Public Wealth Fund” giving citizens a stake in “AI-driven economic growth,” while Anthropic has proposed a sovereign wealth fund to “shape the sector’s behavior.” President Trump’s advisors are also contemplating the possibility of the government grabbing a stake in major AI corporations, according to media reports.
Sovereign wealth funds are not a new idea: Many administrations across the world have implemented them, notably Norway which has about $2 trillion in its wealth fund.
Sanders’ proposal would give the public a direct ownership stake in the largest AI companies, but, he said, it wasn’t just about the wealth. “The foundation of AI is based on the collective knowledge of humanity and the creative work of tens of millions of people. The American people must have the ability to slow it down and make sure that AI benefits humanity, not just the richest people on the planet. That’s precisely what this legislation does,” he said.
As AI shifts from output-generating large language models (LLMs) to armies of agents taking actions on their own, there is a growing threat that failures could affect system reliability.
Temporal, a Bellevue, WA firm founded in 2019, hopes to solve that problem by stabilizing AI and long-running computing processes through “durable execution,” a technology that reliably resurrects failed computing processes on other hosts. If a machine crashes in the middle of agentic AI transactions, the company resurrects the function on a different host so it can continue exactly where it left off. Temporal says its durable execution process comes with a 100% durability guarantee.
The company was solving these kinds of distributed-systems problems long before the generative AI (genAI) rush, and today it powers infrastructure from Coinbase to Airbnb to OpenAI.
For IT decision-makers, Temporal’s offerings promise to bring reliability to AI operations — especially in regulated industries. Co-founder Samar Abbas spoke recently with Computerworld about his company’s technology, AI reliability, execution and what IT leaders need to keep in mind when evaluating and deploying agentic AI.
How did Temporal come to be a backbone powering AI system? “OpenAI recently announced we power many of their products underneath the cover — that’s where Temporal comes in.
“A couple of years ago, as LLMs got smarter, use cases were about generating outputs. Now, the industry is moving into agentic solutions, where AI isn’t just generating outputs, it’s taking actions. The longer these systems run, the more tools they invoke and the more value they create.
“They’re evolving into a whole army of agents coordinating to get complex tasks done. This starts to look like distributed systems. We become that execution authority, the reliability backbone for those agentic systems to get their tasks done from A to Z.”
What is Temporal doing in the backend to keep them stable? “It’s a new paradigm for building applications, we call that durable execution. If you write a function and a failure happens, you lose all of your state. When a machine crashes, we maintain the state. We seamlessly resurrect that function on a different host and continue executing exactly where it left off, without you as a developer writing a single line of code.
“It’s not just a cache, it’s an operating system guaranteeing execution in the presence of failure. We provide 100% durability guarantees behind it. People can use it for mission-critical use cases like transcribing doctor conversations, where even losing one [word] has big implications.”
Did this challenge exist before AI? “My co-founder and I have been at it pretty much our entire careers, spanning almost three decades. We’ve been solving this problem of distributed systems, at Amazon, Microsoft and then Uber, before starting Temporal. We are definitely pre-AI.
“As more workloads move to cloud and become distributed, it introduces this class of failures. This is the fifth time I’m building this system. I built simple workflow, then [a] durable task framework at Azure, then Cadence at Uber, now Temporal. The company is roughly seven years old, but the code base is over 10 years old, because we started at Uber and it’s been running in production ever since.”
And now you tackle that same problem at AI scale? “The funny thing is, especially with AI, that same problem is now at such a massive scale, it’s gone on steroids, with agentic systems coming online and doing real work. We’ve been powering every Coinbase transaction, every Snap story, every Airbnb booking, every Yum Brands order — KFC, Pizza Hut, Taco Bell.
“A couple of years ago, it looked like we’d over-invested in the scale and reliability of the platform. Then AI showed up in such a big way that now I’m asking the team: how do we scale another 10x, 100x, even 1000x? These agents are hitting the market in a way we couldn’t have imagined.”
Can you give a concrete example of that 100% guarantee? “When you’re moving money — debit or credit — imagine a failure happens after you’ve debited an account. Temporal guarantees execution of the entire function from start to finish, in the presence of all sorts of failures. At the end of the day, we’re in the business of selling reliability.
“Developers today spend 80% of their time building resiliency into their systems by working with low-level primitives like queues, databases, retry mechanisms and durable timers, and stitching them together. What we provide eliminates that. And that reliability is exactly what’s becoming critical as enterprises move agents into production.”
Why should CIOs and other IT leaders care about AI reliability? “These agents are now real, no longer prototypes or [proofs of concept]. They’re doing meaningful work in those organizations. Reliability and durability weren’t on the radar for CIOs 12 months ago. Now, it’s the blocker. Especially in regulated industries, if a transaction gets left in the middle, it has real regulatory concerns.
“That’s what’s holding them back from transitioning into the AI stage. It comes up in pretty much every conversation, in the first 10 minutes I’m talking to a CIO.”
CW: Where do the hardest problems sit today? “Security, governance, identity, authorization, authentication. This is where majority of the problems exist, and the ecosystem is so immature. Even things like MCP, I see organizations struggling to implement MCPs to build these agents. This is an area ripe for innovation and a lot of work, including here at Temporal.”
What skills should developers and CIOs build for the AI age? “The biggest skill now is that developers need to be more product focused. Product-minded engineers are the ones who will thrive, because the whole software development flow, writing code by hand, debugging by hand, testing it, is going to look completely different. The job of an engineer is now building the system that builds the system.
“Two things are happening in this AI world. First, a lot more engineers are coming into the fold, because companies like Replit or Lovable are making software development approachable for people who haven’t been professionally trained. Second, there’s going to be a lot more applications written than ever before. The problem space is shifting toward how we run all those applications safely and reliably, with all the guardrails. That’s where the industry is headed.”
Andy Burnham has won Makerfield – and the bond market is watching closely. Gilt yields surged when his name was first floated as leader, and they have already climbed even higher as he closes in on Number 10.
For generations, technology export controls referred to the transfer of code to other countries. But that no longer works, as the latest Anthropic fight with the US Commerce Department makes clear.
On Friday, Anthropic announced that it had received instructions from Commerce “to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees. The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance. Access to all other Anthropic models will not be affected.”
What the Commerce letter says is that Anthropic needs a license to export Fable 5 and Mythos 5 (a “deemed export“), listing four circumstances in which that license would be required: “The sending or taking of the model out of the United States in any manner; The sending or taking of the model from one foreign country to another in any manner; Retransferring the model within a single foreign country; or the release of the model to a ‘foreign person’ in the United States or a foreign country.”
Restricts capabilities not code
Although moving a model has historically meant transferring the code, most experts argue that the definition has changed for all SaaS deployments, and could now be interpreted as referring to any access to the models.
“This is not just about data sovereignty anymore. It is about capability sovereignty, where governments want to control who has access to frontier AI capabilities, irrespective of who built it, where it is hosted, or who worked on it,” said Valence Howden, advisory fellow at Info-Tech Research Group.
“The reference to deemed exports is important, because traditionally that would apply to code, technology, or technical knowledge being transferred,” he said. “In this case, the thing crossing borders is not necessarily the model itself, but it is access to the capability. That is a significant shift, and signals the real intent behind the AI arms race. The focus is moving from controlling the technology to controlling access to the outcomes the technology can produce.”
Mark Rasch, a former federal prosecutor who specializes in legal technology issues, agreed. “I don’t need to have the code physically resident in order to take advantage of the capabilities of that code. Today, the location of the code is irrelevant.”
Practical challenges
There are two practical issues involved. The first is that a large part of Anthropic’s workforce is not US citizens, and some of them have direct access to the code for these models.
But the potentially more daunting issue is that today it is difficult, if not impossible, to identify the citizenship of any AI user, which might force companies to assume that everyone might be unauthorized.
In fact, said Yuri Goryunov, CIO of consulting firm Acceligence, “there is no way to check citizenship through an API call. Besides, three-quarters of Americans don’t have passports.”
Consultant Brian Levine, executive director of FormerGov, added that the issue will make life difficult for CIOs even if the Commerce position is viewed as dubious.
“Regardless of the strength of Commerce’s position, once it issues an ‘Is Informed’ letter, every unlicensed interaction with a foreign person becomes a potential violation, and the safest move is often to halt access until a licensing path exists,” he said.
This means that enterprise CIOs need to approach AI contracts with the knowledge that any government can now declare the product legally unavailable, with no notice.
Sovereignty has climbed the stack
Howden said that this shift will force CIOs to strongly consider non-US AI models such as France’s Mistral or even China’s DeepSeek, “to reduce the concentration risk attached.”
“There are hundreds out there that are very good. It is very easy to sit in the bubble of the four or five we know,” Howden said. “Enterprise CIOs think it’s a much more limited market than it really is.”
Sanchit Vir Gogia, chief analyst at Greyhound Research, said that enterprise executives now need to take the significant import rule changes into account when selecting AI models.
“The harder truth is that sovereignty has climbed the stack,” he said. “The wall no longer stands around the database, it now stands around the intelligence layer itself. Under the export-control frame, it covers the release of controlled technology or code to a foreign person, including one standing inside the United States. The border follows the person, not the parcel. Code is part of the doctrine, but it is not the whole of it.”
He added, “the difficulty is that the cited rules speak of technology and code, while the letter reaches for the model itself. A hosted model hands the user no weights and no code. It hands them inference, and inference is a capability, not a file.”
Ultimately, Gogia said, Anthropic’s decision to cut off model access to everyone immediately “was a rational answer to an impossible instruction. A frontier model can now vanish for reasons unconnected to uptime, price or performance. The same models that help secure systems can be withdrawn at the moment defenders most need them.”
In recent years, forests have emerged as pivotal players in global climate mitigation efforts, representing one of the most promising nature-based climate solutions available today. These ecosystems sequester approximately 31% of anthropogenic carbon dioxide emissions annually, providing a critical buffer against the accelerating pace of climate change. However, the reliability of forest carbon credit systems—mechanisms designed to monetize and incentivize carbon sequestration efforts—has come under intense scrutiny. A groundbreaking study published in the journal Biological Diversity unveils deep-rooted methodological flaws that cast profound doubt on the environmental integrity of current carbon credit frameworks, signaling a crisis of confidence across global carbon markets.
The rigorous analysis, spearheaded by environmental scientists from Yangtze University and Beijing Normal University, meticulously dissects the complex architecture of forest carbon credit systems and identifies four principal structural weaknesses that collectively undermine their trustworthiness. Foremost among these is the use of subjective assessments of additionality, a core concept requiring that credited emissions reductions would not have occurred in the absence of the project. Present carbon credit models predominantly rely on static historical baselines to calculate additionality, yet only an alarming 6% of REDD+ credits—credits allocated under the United Nations’ Reducing Emissions from Deforestation and Forest Degradation program—provide robust empirical evidence to substantiate genuine additional carbon mitigation.
Beyond the critical challenge of additionality, the permanence of carbon sequestration—signifying the long-term retention of carbon stock in forest biomass—is grossly overestimated by current standards. This overestimation is particularly precarious in light of escalating ecological disturbances linked to climate change including wildfires, prolonged droughts, pestilence outbreaks, and inadvertent carbon leakage where forest degradation shifts to unmonitored regions. The failure to appropriately incorporate these growing risks into permanence calculations means that many credited projects likely exaggerate their true contribution to climate mitigation, presenting an illusory picture of impact.
The study further reveals that leakage accounting—the assessment and adjustment for project-driven emissions displacement—is critically underdeveloped. Prevailing methodologies apply a modest average leakage deduction of only 7%, a figure that starkly contrasts with empirical findings suggesting leakage rates ranging from 10% to a staggering 70%. Such systemic under-accounting inflates the perceived net climate benefits of these forest projects, enabling an artificially optimistic valuation of carbon credits within international markets and undermining carbon trading integrity.
Compounding these shortcomings are the conspicuous omissions of biophysical impacts such as albedo and evapotranspiration effects in carbon accounting. Forest ecosystems substantially influence Earth’s energy balance through their reflectance properties and water cycling functions. Neglecting these elements obscures the true net climate impact, as alterations in surface albedo can significantly offset the cooling benefits gained from carbon sequestration, thereby diluting the overall effectiveness of forest-based interventions in climate regulation.
The collective failure to address these intertwined issues has deep ramifications not only for the credibility of carbon markets but also for biodiversity conservation and community well-being, which are often marginalized in project implementation. Insufficient local community involvement and opaque benefit-sharing arrangements risk alienating indigenous stakeholders, raising social equity concerns, and jeopardizing the sustainability and durability of mitigation efforts.
In response to these multifaceted challenges, the research team advocates for a transformative overhaul of forest carbon credit systems through a data-driven, science-based, and integrative accounting framework. Central to this reform is the replacement of static baselines with dynamic monitoring systems that leverage high-frequency remote sensing technologies alongside advanced machine learning algorithms. This approach enables objective, continuous, and quantitative assessments of additionality, dramatically enhancing transparency and scientific rigor in credit issuance.
Addressing permanence requires the establishment of a comprehensive three-tier risk management architecture comprised of prevention, buffering, and insurance mechanisms. This tiered system proactively mitigates disturbances by integrating biodiversity conservation as a mandatory compliance criterion rather than considering it a supplemental benefit, thus embedding ecosystem resilience at the heart of carbon project governance.
Transparency and standardization are equally emphasized through the call for stringent Monitoring, Reporting, and Verification (MRV) protocols. The use of cutting-edge technologies such as Light Detection and Ranging (LiDAR) and environmental DNA (eDNA) is prescribed to ensure precise biomass and biodiversity assessments. Additionally, mandatory disclosure of datasets and verification methodologies aims to foster independent third-party audits, enhancing accountability and stakeholder confidence in carbon accounting practices.
Sociopolitical dimensions are also addressed, with the framework highlighting the critical necessity of formalized community governance structures and the institutionalization of Free, Prior, and Informed Consent (FPIC) procedures. These mandates ensure that forest-dependent communities retain decision-making power and equitable access to the socioeconomic benefits derived from carbon sequestration projects, thereby reinforcing local stewardship and long-term project viability.
While the introduction of these rigorous standards is expected to contract the overall volume of carbon credits issued—reflecting a more conservative and realistic accounting of mitigation gains—the resultant credits will embody higher integrity and trustworthiness. This qualitative transformation is paramount for forest carbon credits to evolve from contested commodities susceptible to skepticism into robust and reliable assets underpinning credible global climate governance.
The implications of this research are profound. By embedding scientific rigor and standardized risk management, forest carbon credits can realize their full potential as durable climate mitigation tools while simultaneously safeguarding biodiversity and respecting community rights. This paradigm shift promises to restore confidence among stakeholders, catalyze more effective climate finance mechanisms, and advance global efforts to stabilize the Earth’s climate system.
Ultimately, this work underscores a crucial message: nature-based climate solutions like forests must be governed by scientifically sound and socially just frameworks. Only through such commitment to transparency, accuracy, and inclusivity can these natural assets deliver genuine and lasting contributions to the fight against climate change.
Subject of Research: Not applicable Article Title: Restoring Trust: Rebuilding the Forest Carbon Credit System Through Scientific Rigor News Publication Date: June 17, 2026 Web References: http://dx.doi.org/10.1002/bod2.70026 References: Chen, Xiaoqian, and Shaokun Li. 2026. “Restoring Trust: Rebuilding the Forest Carbon Credit System Through Scientific Rigor,” Biological Diversity: 1–5. Image Credits: Xiaoqian Chen, and Shaokun Li Keywords: Environmental sciences, Carbon emissions, Biodiversity conservation, Climate change mitigation, Risk management, Deforestation, Community ecology, Albedo, Resource policy, Environmental economics, Sustainable development, Land use, Climate change adaptation, Forestry, Carbon, Environmental policy, Environmental impact assessments, Environmental management, Remote sensing, Forest ecosystems
There’s no shortage of agentic AI tools out there that offer to perform online tasks on your behalf, if only you’ll give them all your passwords and credit card details. The trouble starts when those agents don’t know when to stop — or when others don’t know to stop them.
In Estonia, the country’s AI Council has plans to change that, proposing to issue government-backed digital identities for AI agents that spell out what powers a person or company is willing to delegate to them.
“In the future, AI will increasingly perform digital operations on behalf of a person, company, or institution,” said Estonian Prime Minister Kristen Michal in a news release. “To do this, it must be clear who is acting, on whose behalf, with what rights, and who is responsible.”
He supported the AI Council’s proposal to create a digital identity for AI agents that will define agents’ rights and enable them to act in a verifiable and auditable manner.
The ID could, the council suggests, show whether an agent is only allowed to view data, create or edit documents, or make payments, and if so, up to what limit.
First mover advantage
There’s no telling when the plan will come to fruition — although Michal is keen for his country to take the lead.
“If we act quickly and wisely, Estonia will become the first country in the world to create an official digital identity for AI agents,” he said.
Estonia is already a leader in the use of digital identities for humans. Estonians can use their national digital ID cards for voting, signing documents, accessing medical and tax records. The country also offers foreigners the option of applying for “e-residency,” a digital identity enabling them to create a company in Estonia and digitally sign all related documents online as they interact with the country’s widely digitized administrative processes.
Michal created the AI Council in January, calling on Estonian startups, investment funds, industry and research institutions to systematically implement AI across the country’s industry, education, healthcare, and energy sectors.
For many, including European Union policy makers, increased use of open source software is a key part of the answer, offering an alternative to proprietary platforms from a handful of large US vendors.
That’s the view of Frank Karlitschek, CEO of Nextcloud, the German software vendor that bills itself as an open-source alternative to software suites from the likes of Microsoft and Google.
Nextcloud CEO Frank Karlitschek speaking at the German software company’s Nextcloud Summit 2026.
Nextcloud
Karlitschek founded the company in 2016, forking OwnCloud’s open-source file-sharing software. Since then, Nextcloud has expanded its products to include a range of productivity and collaboration tools that organizations can install and run on their own servers or access via cloud providers.
More recently, Nextcloud helped develop the Euro-Office application suite, which launched last week as an open source alternative to Microsoft Office and others, and continues to build out its Nextcloud Hub with AI assistant and agent features. The company now says revenues are growing at between 50% to 100% year over year.
Computerworld spoke to Karlitschek at Nextcloud Summit about momentum around digital sovereignty, the European Commission’s Tech Sovereignty Package proposals, and how Nextcloud hopes to evolve in the coming years.
The following interview was edited for length and clarity.
When Nextcloud launched, there was a big push in Europe away from on-premise software towards US cloud providers. How have attitudes towards open source and awareness of alternatives providers changed since then? “I’ve been doing open source since the ‘90s; at the time it was mostly for a nerdy audience — a very small group of people who really care about software and being in control. The sovereignty part was always there. It’s the core idea behind open source that you can understand what the software is doing, you can deploy it wherever you want, you can study it and change it, and so on.
“At the time, it was very niche, and since then it’s really growing and growing. There are certain points in time that really accelerated the growth; something like the Snowden revelations, for example, or the whole discussion about GDPR and certain legislation. And then, of course, the current geopolitical situation.
“I personally find it interesting that it grew from something that is just interesting for software developers, and now it’s on the geopolitical stage. I have meetings with big politicians who really care about it now, and I personally find it interesting that it’s increasingly understood by — I wouldn’t say the mainstream, but more and more people.
“At the beginning of Nextcloud, we mostly talked with IT managers looking for a solution; they care about how it works, the price and other things. But now we are also talking with the C-level people. It’s part of an overall strategy of a company, to say, ‘Hey, we need to look into the dependencies, we want to have a solution that fits into the strategy of the company.’
“In the past, it was like a commodity – it’s just some software, who cares? Now, it’s really part of the company strategy. That’s really interesting.”
There’s been a lot of interest around digital sovereignty over the past couple of years. To what degree is this translating into action, with organizations migrating away from US cloud providers? “The interest is gigantic. Everybody’s talking about it, we have so many contacts and people coming to us. Not everybody is doing it — a lot of people are just exploring and seeing what the options are.
“Obviously, we hope that this will translate into actions in a few months. At the moment, it’s a lot of talking and exploring the options. As a company, we are also growing a lot in customer base. But the interest in this space is even bigger; we see it as the beginning of a funnel.
‘In defense we see a lot of interest, then also everything around education is very important for us, then other regulated markets like the healthcare, for example. Finance is an interesting one.”
A lot of the conversations around digital sovereignty are tied to the current geopolitical situation and even the US administration. Do you see demand for sovereign technology as a structural change or are some organizations holding back to see how the situation improves in the future? “I see it as a long-term trend. If you look at the IT budgets and projects in the ‘90s, it was some something unimportant. It was, of course, important that the printer works and the fax machine works, but it was not definitely not strategic for the company.
“And then in 2000, the whole cloud trend came up, and there was the big hope that this will save money. It was always the narrative with cloud computing that you can just outsource it and save money and it’s great.
“Nowadays, people realize that it’s not something that you can just ignore. I wouldn’t say that everything comes back on premise, but people care about it now. They understand it’s not just a commodity, like water, or electricity that comes out of the wall and you don’t care what’s behind it. People realize that it’s something that has an impact on the future of an organization, from a vendor lock-in perspective, from a cost perspective, from an industry espionage perspective, and competitiveness. With open source, you’re more flexible. So, I think the trend that this is all more strategic and important for the future, this will go on.”
The European Commission recently published its Tech Sovereignty Package, including its open source strategy. Are these proposals sufficient to address the concern around digital sovereignty and support the open source ecosystem in Europe?
“It’s great, I really like it. I was actually surprised they listened so well. But now the real challenge is to actually do it; this still needs to happen. The description of the problem and a possible solution, this is all very good. I’m surprised, I’m happy about it, but to put this into actually binding law, this still needs happen.”
Would you like to see any changes to the current proposals before they’re gets passed into legislation? “At the moment, they have these four different risk levels, and the most critical one — No. 4 — is one where they accept only open source and European solutions. This is the highest risk level, but this is only for 1% of the market. I hope that it’s better understood that more than 1% should care about this more.
“If you have something which is completely not critical, maybe doesn’t possess any personal data at all — sure, it’s totally fine [to use non-EU suppliers]. But if you have GDPR requirements, espionage protection, no vendor lock-in, and so on, then there should be more of that [the highest requirement level].”
US firms have attempted to address European customers’ concerns in different ways, with sovereign marketed cloud services and joint ventures with European providers. Microsoft 365 Local is designed to run on premise. Where do you draw the line between what’s actually a sovereign solution and what some call ‘sovereignty washing? “Sovereignty has different dimensions, of course. But if you look at the problem of the CLOUD Act alone, which gives foreign agencies full access to the data here, then the whole idea that it’s enough to have European data centers — that’s not enough. It’s clearly written in the CLOUD Act, that even with [European] data centers, or subsidiaries, it still applies.
“Microsoft tries to find a solution there with its Delos idea; a company that is owned by SAP — a German company — and Microsoft delivers only the software. But even then, you have this dependency, because software needs updates and software security updates. And if they’re not available, or if someone puts a backdoor into the software, which is possible, then you still have a problem.
“So, they’re trying really, really hard to find a way around the problem, but it’s not easy for them.”
To look ahead a bit in terms of the product strategy, there were announcements for Nextcloud Hub this week around AI agents, and the program to work with independent software vendors. What do these say about Nextcloud’s future? “The overall product strategy will not change so much; it’s about having state-of-the-art collaboration software — but with a lot more control, security and safety — that’s open source and independent where you host it. So this will always stay, but of course, there’s some additional factors that come into play now, like the AI impact that we see and want to leverage with our agent strategy.
“We’ve had this for one and a half years already, but we are expanding that. In the future, you might still use an interface in a classic way that you open documents and type in text and so on. But there are also a lot of operations that can be automated in the future with AI. And this is something we really invest a lot into.
“Another aspect of AI is how easy it is to build custom software around it. The coding models are getting better all the time, which means there will be more and more custom business software. This is what we want to capture with our ISV program. Software development will become easier, but you don’t want to deploy just random software in your company, you want to have something that is tested, certified and secured, and that somebody’s accountable for it. This can be something we can provide at Nextcloud.”
Editor’s note: NextCloud paid for Matthew Finnegan’s travel and hotel costs for NextCloud Summit 2026, but had no editorial role in the creation of this story.
Lawmakers have failed to extend a surveillance law that allows US intelligence agencies to monitor targets abroad without a warrant.
Congress rejected a vote to extend Section 702 of the Foreign Intelligence Surveillance Act to July 2, which means, for a few days at least, some surveillance will be put on hold, for the first time since the Act was passed in 2008. The next possible chance for a vote will be June 28.
This has significance for CISOs because they need to be aware of how communication between the US and other countries is being monitored. The Act permits US intelligence agencies to collect texts and emails sent to and from foreigners living outside the US without a warrant — and when those communications are to or from an US citizen, it allows them to scoop them up too.
“For too long, the FBI has been able to piggyback on a major national security tool as an unconstitutional backdoor way of reading Americans’ communications,” Electronic Frontier Foundation Senior Policy Analyst Matthew Guariglia wrote in article about the renewal vote this week.
It is uncertain what will happen next. Some commentators expect things will proceed as if the Act had been extended, possibly through an executive order. However, the industry may well revolt against this and we could see some tech providers take legal action.
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