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If your AI rollout is making people more exhausted, the architecture is wrong. That’s not a provocative claim; it’s the logical conclusion of what the data shows. With 69% of UK businesses implementing AI assistants, these tools have become part of everyday working life.

But deployment without the right operational structure is leaving employees exposed to the harmful effects of ‘AI brain fry’. AI overload is not a failure of the individual, but a failure of system design. And it is the responsibility of technology and business leaders to fix it.

Researchers recently coined the term ‘AI brain fry’ to describe the cognitive fog and loss of concentration that results from excessive oversight and orchestration of AI tools ; i.e. the mental load of managing the systems themselves. The problem - as our own data makes clear - is not that employees are using AI skills too much.

Rather, it is that most UK businesses have deployed AI tools without building the structured ways of working needed to make them productive. The issue does not lie in use alone; it lies in how that use is managed.

The organizations deploying these tools have a duty to ensure they deliver genuine efficiency gains – not a new category of cognitive burden.

The adoption gap is creating more work, not less

Only 31% of businesses are using multi-agent workflows, leaving their employees stuck in a cycle of tedious labor – the kind that AI is supposed to reduce. The majority of UK businesses currently employing AI tools are expecting employees to still do most of the heavy lifting.

Employees are finding themselves writing prompts, manually checking whether the answers are reliable, and interpreting outputs.

This type of work was supposed to be eased by AI. Instead, the tools have made it worse.

The consequence? More admin, not less. Employees who were promised that AI would lighten their workload are instead finding it has added a new layer of tasks including prompt management , output validation, error correction on top of the day job.

Few businesses have moved towards a structured multi-agent workflow where AI systems handle the orchestration burden directly – routing tasks, validating outputs and managing agent-to-agent handoffs without requiring constant human supervision.

That is the architecture that relieves the cognitive load. Without it, employees are not using AI – they are managing it. And there is a significant difference between the two.

Moving towards an ‘adaptive operating model’

UK organizations need to move beyond AI deployment and towards an adaptive operating model. One that is deliberately architected, not organically grown. That means clearly defining which tasks AI can be trusted to handle autonomously, where human judgement remains the critical control point, and how work moves between the two. In practice, this could look like:

AI agents handling first pass research, data synthesis and output drafting. Humans setting direction, making judgement calls and reviewing exceptions, rather than every output.

The distinction between “AI does the work” and “human manages the AI doing the work” is where most current deployments get stuck. To protect employees and exact real productivity , businesses must build in human oversight at the right level – not at every level.

This means developing genuine domain expertise so that employees can interrogate AI outputs critically, not simply accept them. It also means investing in the technical literacy to design workflows that are robust, not just functional. An AI deployment that requires constant human supervision to remain reliable has not been properly engineered.

The organizations that get this right will also be better protected as the employment landscape shifts. With the UK government’s Employment Rights Act 2025 set to reduce the qualifying period for unfair dismissal claims and remove the compensation cap from January 2027, the cost of poorly managed AI-driven workforce change, both in human and legal terms, is rising.

Businesses that have embedded clear human-AI accountability structures will be far better placed than those that have not.

Without making these structural changes, AI adoption will continue to add effort rather than remove it. Thereby accelerating burnout at the very moment businesses are depending on these tools to drive productivity.

Protection and transformation go hand-in-hand

It is entirely possible to realise the productivity potential of AI whilst protecting employees from its cognitive costs. Multi-agent workflows, properly designed, keep humans in the seats that matter - strategy, judgement and decision-making – and had the orchestration burden to the systems built for it.

AI brain fry is not an inevitable side effect of AI adoption. It is a signal that the implementation architecture needs re-thinking. That is a technical and organizational challenge, and it belongs with the people who built the system – not the people using it.

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A change is coming to the codes OB-GYNs use to bill for maternity care services: Starting Jan. 1, 2027, we will shift from a bundled “global obstetric payment” to a fee-for-service model. This change impacts almost every U.S. family with a pregnancy. Under the current system, families receive a bill that does not distinguish the actual prenatal and postpartum costs from labor and delivery, which makes things incredibly confusing for patients.

In fact, the bundled payment’s impacts have been widespread: It has complicated billing for patients and clinicians, limited access to care, cut back the ability to provide patients with more personalized care, and slowed progress in better understanding U.S. maternal health outcomes.

Read the rest…

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Ford’s plant in Spain has been operating at less than a quarter of its capacity.

Geely is expected to build the electric EX2 hatch alongside the Ford Kuga.

Other Chinese brands are heading to Spain, including Chery and BAIC.

Following several months of talks, it’s been revealed that Geely has reached an agreement with Ford to build vehicles at an assembly line currently sitting idle at Ford’s factory near Valencia, Spain. The deal will allow Geely to build and produce cars locally, skirting tariffs designed to hinder the European expansion of Chinese car companies.

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Ford’s Almussafes plant has an annual capacity of 450,000 vehicles but has been running at less than a quarter of that for several years. It currently handles production of the Kuga , but soon, it will be joined by a Geely. The company has yet to confirm which model it’ll build in Spain, but reports indicate it’ll be the new EX2, an affordable electric hatchback which was the best-selling new car in China last year.

Read: Geely’s New Sedan Claims 450 Miles From A Battery Most EVs Would Call Small

Spanish prime minister Pedro Sanchez has played an important role in getting the deal done. As Spain does not have a significant homegrown car industry like Germany or Italy, it’s been welcoming companies from China with open arms.

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The Chinese Are Coming To Spain

Ford Kuga

As noted by Bloomberg , Chery is already working alongside Spanish company Ebro and has revived a factory in Barcelona that was once home to Nissan. In addition, BAIC is joining with local firm Santana to build several off-road cars in Andalusia. Stellantis will also establish a battery factory with Chinese conglomerate CATL in Zaragoza.

Additional details about the deal are expected to be announced by Spain’s prime minister later this week, when he is expected to speak with the media at Ford’s factory. As recently as May , it was reported that, through the deal, Ford may be able to build an EV of its own using the same architecture as the EX2, although this has yet to be confirmed.

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Geely EX2

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Engineers have created a drone that camouflages itself as a faint, hovering haze when it takes flight.

The "Phantom Twist" prototype drone is a carefully engineered robot that utilizes motion blur to hide in plain sight — opening up a new frontier in low-visibility flight. Scientists say it could reshape how drones monitor wildlife, survey ecosystems and inspect infrastructure.

Most stealth drones try to disappear by changing their appearance, using camouflage paint, transparent plastics or complex optical tricks to bend or scatter light. The Phantom Twist takes a fundamentally different approach by exploiting how humans and animals perceive motion.

The scientists who created the drone outlined their findings in a study presented July 16 at the conference Robotics: Science and Systems in Sydney, Australia.

"Most efforts to hide drones focus on making them look like their surroundings," said first author of the study Michael Rubenstein , associate professor of computing and mechanical engineering at Northwestern University, in a statement . "Instead, we asked whether we could design the drone itself around the way humans perceive motion.”

(Image credit: Michael Rubenstein/Northwestern University) The result is a machine that behaves more like a spinning fan than a conventional quadcopter. Typical drones have four rotors spinning around a largely stationary body, so your eye can lock onto the frame even as the propellers blur.

Phantom Twist strips this idea down to a single motor and single propeller. The propeller spins one way while the entire body counter‑rotates in the opposite direction with no stationary parts to visually latch on to — spinning 25 times per second, which is too fast for the human eye to resolve clearly.

(Image credit: Michael Rubenstein/Northwestern University) It's about 10 times less visually perceptible than a conventional quadcopter, the scientists said. In practice, that means observers don’t see a crisp flying machine but a translucent smudge, with its few opaque components blending into a haze.

To get there, the team assigned algorithms to explore thousands of designs. First, they used a computational model to automatically generate about 20,000 drone configurations that could fly stably, at least in theory. Each configuration shuffled a motor, propeller, batteries, circuit board and counterweight into different positions.

Then artificial intelligence (AI) and optimization tools took over, iteratively rearranging those pieces to minimize how visible each design would be from almost any viewing angle — all while respecting the constraints of aerodynamic stability.

The researchers simulated each candidate spinning in midair and composited the images over 100 different real-world backgrounds, from skies to trees to buildings.

To determine the stealthiest designs, they applied a perception model that approximated human vision, with drones that better blended into their surroundings earning a lower visibility score. From there, the team selected the 500 lowest-scoring designs and ran their optimization loop again, squeezing out further decreases in visibility. When the team was confident in the design of a particular drone, they built it.

(Image credit: Michael Rubenstein/Northwestern University) The final Phantom Twist isn’t a compact block of hardware; it’s deliberately spread out in three dimensions. Components sit at different heights and angles, with empty space between them, so that when the drone spins, the parts don’t visually overlap into a solid silhouette.

That geometry matters because of the way our eyes process images.

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"The human eye takes time to accumulate signals, roughly analogous to the exposure time of a camera," said computer vision expert and co-author of the study Emma Alexander . When something spins fast enough, distinct edges smear together, and we perceive a blur instead of a shape.

The researchers' initial uses for the stealthy drones include monitoring nesting birds without startling them, surveying wetlands without scattering flocks of waterbirds, and inspecting aging infrastructure without altering human behavior, they said.

For now, Phantom Twist isn’t a perfect "ghost." The spinning propeller still generates a significant amount of noise and the spider‑web of thin wires and support rods remains partially visible. Rubenstein and his colleagues said in the study they’re already thinking about next-generation iterations that swap in more transparent materials and quieter propulsion systems.

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As more Americans experiment with synthetic peptides despite warnings about their unproven benefits and potential risks, an advisory panel to the Food and Drug Administration will meet on Thursday and Friday to discuss changes that could make peptides more accessible.

At issue is whether to allow compounding pharmacies to manufacture seven peptides that are currently designated as unsafe for them to make. The panel discussion is expected to be unusual in more ways than one.

First, many of the newly appointed members on the panel hold what critics ( including FDA staff ) say are conflicts of interest. The panel roster includes several physicians who prescribe peptides to patients as well as pharmacist and Tennessee state Sen. Bobby Harshbarger, whose mother, U.S. Rep. Diana Harshbarger (R-Tenn.) has advocated for looser peptide regulations . Many of these panelists were selected by the Health and Human Services Department, FDA officials previously told STAT.

Continue to STAT+ to read the full story…