For decades, NATO has operated on a timeline of years—years to design a jet, years to build a warship, years to refine an armored vehicle. But on the battlefields of Ukraine, the timeline is measured in weeks. This discrepancy has created a dangerous gap in readiness, leading one of the alliance’s top commanders to warn that NATO is essentially stuck in a procurement traffic jam while the nature of war evolves at breakneck speed.

Adm. Pierre Vandier, NATO’s Supreme Allied Commander Transformation, describes this as a fundamental clash of operational speeds. Ukraine has developed what he calls an “adaptation DNA,” a capacity to identify a battlefield problem and deploy a technological solution almost in real-time. For the West, which has not faced this kind of systemic pressure in generations, the ability to pivot this quickly is not just missing—it is nonexistent.

The Procurement Traffic Jam

The current Western defense model is designed for stability and massive scale, but it is poorly suited for the “cat-and-mouse game” of modern drone and robotic warfare. Vandier uses the metaphor of a highway to explain the failure: the alliance is trying to “enlarge the highway” by producing more of the same legacy systems, rather than building an “HOV lane” that allows emerging tech to bypass the bureaucracy.

In Ukraine, this fast-track approach is a matter of survival. When the Ukrainian fleet of exploding naval drones began threatening Russian assets in the Black Sea, Moscow responded by increasing combat aircraft patrols. In a traditional NATO procurement cycle, a countermeasure might take years to clear committee and factory lines. Instead, Kyiv rapidly armed its drones with surface-to-air missiles to neutralize the fresh threat.

This urgency is creating a friction point between legacy defense contractors, who remain wedded to old procurement models, and a new wave of defense startups attempting to emulate the Ukrainian model of rapid iteration and direct combatant feedback.

A Humbling Learning Curve

The gap in adaptation is not just about hardware; it is about tactical intuition. Recent reports suggest a sobering reality for the alliance: in some instances, modest Ukrainian teams have outperformed entire NATO battalions, highlighting a disconnect between Western doctrine and the reality of the current conflict.

This has forced a reversal of roles. NATO artillery crews have been receiving instruction from Ukrainians on the effective leverage of drones. These lessons are now being pushed further, as the alliance attempts to figure out how to apply these rapid-adaptation tactics in extreme environments, such as the Arctic.

However, the transition is not seamless. Some reports indicate that Ukraine has even fired its NATO trainers, suggesting that the alliance may be struggling to absorb the very lessons it desperately needs to learn. This tension is echoed by Ukraine’s envoy to the alliance, who has argued that it is time to fundamentally reinvent NATO to match the demands of the present.

Analytical Q&A

Why is NATO struggling to adopt the “HOV lane” for technology?

The primary obstacle appears to be a reliance on legacy procurement models. Large defense contractors are built for long-term, multi-year development cycles for complex systems. Shifting to a model where technology is updated every few weeks requires a level of flexibility and risk-tolerance that contradicts the traditional bureaucratic and financial structures of Western defense spending.

How did Ukraine’s naval drone evolution illustrate “adaptation DNA”?

Ukraine first deployed exploding naval drones to challenge the Russian Black Sea Fleet. When Russia countered by using combat aircraft to hunt these drones, Ukraine did not wait for a new class of ship; they integrated surface-to-air missiles directly onto the drones. This rapid cycle of “threat-response-adaptation” is the core of the DNA Adm. Vandier believes NATO lacks.

What are the broader implications if NATO fails to modernize its speed of adaptation?

If the alliance remains stuck in a “crisis” mindset—trying to fix old models rather than responding to the “shock” of modern warfare—it risks deploying obsolete technology. In a conflict defined by drones and robots, a system that takes years to build may be countered by a software update or a new drone design before it even reaches the field.

Can a massive, multi-national bureaucracy ever truly emulate the agility of a nation fighting for its existence?

The Netherlands is currently grappling with a striking contradiction: a government-backed experiment to legalize the production of cannabis is appearing to be a resounding success on paper, yet it is creating profound social friction on the ground. In cities like Nijmegen, the “weed experiment” has spent a year replacing the illicit back-door supply of coffeeshops with legal, regulated cannabis. Whereas operators and policymakers point to a streamlined, safer system, some residents describe a deteriorating quality of life, claiming the trial has turned their neighborhoods into zones they no longer recognize.

For decades, the Dutch “gedogen” (tolerance) policy created a legal paradox where selling cannabis was tolerated, but producing it remained a crime. This trial aims to close that gap by allowing coffeeshops to source their product from licensed growers. The goal is simple: strip the profit from organized crime and bring the entire supply chain into the light of regulation. In the trial zones, the transition has been largely seamless for the businesses, with legal cannabis now filling the shelves of Nijmegen’s shops.

The Friction of Progress

But, the administrative success of the trial is colliding with a visceral human cost. While the government tracks metrics of legality and safety, residents living near the participating shops report a different reality. Some neighbors have expressed desperation, citing an increase in nuisance and a perceived decline in neighborhood safety. In one poignant account, a resident noted that the atmosphere has shifted so drastically that they no longer experience comfortable having their grandchildren visit.

This tension highlights a recurring theme in public policy: the gap between macro-level success and micro-level impact. The trial may be effectively cutting ties with the underworld, but it is doing so in a way that some citizens feel prioritizes the “experiment” over the stability of their residential streets.

A Success Pending Political Will

Despite the localized complaints, the general consensus among those managing the trial is overwhelmingly positive. The logistical hurdles of legal production have been cleared, and the proof of concept is largely established. Yet, the future of the program does not rest with the scientists or the shop owners, but with the political climate in The Hague.

The transition from a successful pilot to a national law is rarely a straight line. The Dutch government must now weigh the empirical success of the trial against the political pressure from concerned citizens and the ideological stances of the current governing coalition. If the experiment is deemed a success, it could lead to a permanent shift in how the Netherlands manages its most famous legal gray area; if the political cost is too high, the trial could remain a footnote in policy history.

Analysis & FAQ

Is the cannabis experiment considered a success?

From an operational and regulatory standpoint, yes. The trial has demonstrated that legal production can effectively replace the illicit supply chain in coffeeshops without disrupting the market. However, its social success is contested by residents who report increased neighborhood disturbances.

What specifically changed for coffeeshops in Nijmegen?

For the past year, these shops have been supplied exclusively with legal cannabis. This removes the legal risk associated with the “back-door” supply, where shop owners previously had to buy from illegal growers to stay in business.

What are the primary obstacles to making this a national law?

The primary obstacle is political will. While the data may support legalization, the government must balance this against the “nuisance” factor reported by local communities and the potential for political backlash from conservative factions within the government.

Could this lead to a fully legal market like in parts of the US?

It is possible, but the Dutch model remains distinct. The focus is currently on regulating the supply chain for existing coffeeshops rather than creating a wide-open commercial retail market. Any further expansion would likely depend on how the government addresses the social friction observed during the trial.

Can a policy truly be called a success if it solves a criminal problem but creates a community one?

When Ellis Neder interviewed for the role of head of design at Foxglove, a platform for robotics developers, he wasn’t asked to provide a polished portfolio or a list of accolades. Instead, he was asked to show up and actually do the job. He flew to San Francisco for a long weekend, spent several days in the office, and worked through a real-world user experience issue within the company’s app. It was a trial by fire—and Neder loved it.

Today, Neder oversees these work trials for every single role at Foxglove. When candidates ask if they can use AI during the process, his answer is a definitive yes: “We expect you to use AI, and we will give you whatever AI tools you seek.” For Foxglove, the trial isn’t just a competency test; it is a window into the company’s actual pace and a way to ensure a candidate can “walk” in an era where generative AI allows almost anyone to “talk.”

The death of the paper trail

The traditional résumé is losing its cachet. In a landscape flooded with AI-generated “slop,” hiring managers are increasingly viewing online portals as voids. The result is a pivot toward a “show your work” era of job hunting. It is no longer enough to list a GPA or a former employer; candidates are being asked to perform live, much like a musician’s audition or a student’s in-person exam.

This shift is driven by a fundamental distrust of static credentials. AI has made it possible to fabricate expertise or polish a CV to perfection, but it cannot simulate the ability to solve a problem in real-time under the gaze of a team. This is why companies are turning to work simulators—such as Rounds, which uses an AI agent named Sophia to lead candidates through technical simulations—or asking finance applicants to decipher complex spreadsheets on the spot.

The data suggests this is more than a startup trend. According to an analysis from the Brookings Institution, job postings requiring AI skills quadrupled from roughly 50,000 in March 2024 to nearly 200,000 recently. A 2025 survey from the National Association of Colleges and Employers found that the proportion of employers using skills-based hiring rose to 70%.

The adaptability premium

Beyond hard technical skills, there is a growing obsession with “capability-mapping”—the search for traits that correlate with success in a volatile environment. Some leaders are now prioritizing personality over prestige. Davide Grieco, head of growth at Clay, has built a team not from Huge Tech veterans, but from people demonstrating “obsession, creativity, and the ability to multitask.” His hires include a top NCAA artistic swimmer and an applicant who simply joined his livestream and started participating.

This trend toward “vibe coding” and adaptability is echoed by recruiting experts like Michelle Volberg of Twill, who notes a surge in demand for former athletes. The logic is simple: in a world where AI changes the nature of a job every six months, knowing how to do a specific task today is less valuable than the innate ability to learn and pivot tomorrow.

For minor firms, this approach is a risk-mitigation strategy. Peter Grafe, cofounder of BlueAlpha, pays candidates $2,000 or covers their travel to San Francisco for multi-day trials. “Everyone can code something within 48 hours,” Grafe says. The goal is to see how a candidate thinks and whether they can use AI to become “10X faster.”

Efficiency as the new benchmark

The pressure to prove value doesn’t end at the hiring stage; it has moved into performance reviews. Big Tech companies are now tracking exactly how employees use AI to justify productivity gains. Meta provides a stark example: after implementing layoffs and adopting AI over the last three years, the company’s revenue per employee has jumped to an average of more than $2.5 million per worker.

However, a tension remains between the agility of startups and the inertia of large corporations. For massive firms, sorting thousands of applicants by degree is simply easier than conducting individual skills assessments. Moe Hutt of HireClix notes that while large companies are adding tests to their process, it is often a “knee-jerk reaction” to verify that a candidate is real, rather than a genuine attempt to prioritize aptitude over experience.

Despite this, the trajectory is clear. Whether it is through an application portal that ignores CVs entirely—like the one used by Jake Ward of Contact—or a week-long in-office trial, the burden of proof has shifted. The modern candidate is no longer asked to tell the employer what they can do; they are expected to do it.

How is AI actually changing the interview process?

AI is acting as both the disruptor and the tool. Because it can automate the creation of resumes and cover letters, employers are moving toward live simulations and “work trials” to verify authenticity. Simultaneously, AI is being integrated into the evaluation itself; companies now expect candidates to use AI tools to solve problems faster, treating AI competency as a core requirement rather than a bonus.

Why are companies hiring former athletes or people from non-traditional backgrounds?

Employers are increasingly valuing “adaptability” over specific white-collar experience. Because AI evolves so rapidly, specific technical knowledge can become obsolete quickly. Traits associated with competitive athletics—such as discipline, obsession, and the ability to perform under pressure—are seen as better indicators of a candidate’s ability to thrive in a rapidly changing workplace.

What does “revenue per employee” have to do with AI hiring?

It serves as a metric for AI’s impact on productivity. Companies like Meta are using this figure to demonstrate that a smaller, AI-empowered workforce can generate more value than a larger, traditional one. This creates a higher bar for new hires, who must now prove they can integrate AI into their workflow to maintain or increase these efficiency levels.

Will the traditional resume disappear entirely?

While unlikely to vanish completely—especially in large corporations where it remains a convenient sorting tool—the resume is losing its status as a primary validator of talent. The market is shifting toward a model where results, launched projects, and live demonstrations of skill carry more weight than a list of previous employers or degrees.

As the barrier between “talking” and “doing” continues to shrink, are you prepared to audition for your next job?