According to Judge James Boasberg, Meta did not break antitrust law when it bought in 2012 and in 2014. In other words, one of the largest and most influential companies on earth did nothing wrong when it scooped up two rising competitors that millions of people were flocking to.

If that sounds like a strange conclusion, that’s because it is. The ruling says Meta is not a monopoly. If that is true, we might need a new dictionary.

The entire decision rests on the idea that Meta faces plenty of competition. The judge pointed to and as proof that Facebook and Instagram are not all-powerful. This is a little like arguing that cannot dominate retail because people also buy things at the local farmers’ market. Yes, TikTok exists. That does not mean Meta is some scrappy underdog.

Looking at the market through a funhouse mirror

The government argued that Meta dominates personal social networking. That is the space where people connect with friends and family, share photos, send messages and scroll through updates from the people they know. This is the core of what Facebook, Instagram and WhatsApp do.

Meta pushed back by reframing the market so broadly that almost anything counted as competition. If a platform lets you view videos or communicate in some way, Meta argued that it belongs in the same category. Suddenly YouTube, , , and pretty much anything with a login became fair game.

The judge accepted this view. Once the market was stretched to that size, it became almost impossible to say Meta held a monopoly. Which was exactly the point.

The evidence told a very different story

What makes this ruling more frustrating is what the evidence showed. Meta’s internal messages made it clear the company saw Instagram and WhatsApp as real threats. Executives said so directly. They worried that these smaller platforms could grow fast and compete for the same users. They did not want to risk it.

So Meta did what a company with almost unlimited resources does. It bought them.

This is a simple narrative. A giant company saw emerging rivals. It acquired them before they got too big. The result was a clear reduction in competition. Yet the court rejected that exact story and replaced it with something much hazier.

Our antitrust system is not built for companies this large

The ruling also reveals a deeper problem. To win the case, the government had to prove something impossible to prove. It needed to show that Instagram and WhatsApp would have become massive competitors if Meta had not bought them.

That is like asking someone to prove what their life would have looked like if they had moved to a different city 10 years ago. You can guess. You cannot prove it.

Antitrust law was written for a different era. Today’s tech giants move faster than regulators ever can. By the time the government files a case, the market has already shifted again. Meanwhile, companies like Meta keep growing and keep folding more products into their ecosystem.

This ruling rewards that speed. It tells large companies that if they acquire rivals early enough, while things are still developing, regulators will never be able to catch up.

The future of competition just got harder

The timing could not be worse. Meta is now pushing into artificial intelligence in ways that raise even bigger questions about power and control. The company owns the world’s largest social networks. It owns the messaging platforms used by billions of people. Now it is feeding all of that data into its next generation of AI tools.

If we cannot define a monopoly in the social media world, how will we define one in the AI world? How will we protect competition when the next big platforms do not even resemble the ones we use today?

The judge’s ruling may stand on firm legal ground, but it does not reflect how people actually live online. When most of your social life, communication and digital identity flow through one company, that company has enormous power. And once it buys up its rivals, it has even more.

This decision tells us that our system is struggling to recognize what dominance looks like in the modern internet. If we cannot see Meta as a monopoly, we have officially lost the thread.

is the chief strategy officer for. He holds a law degree and has taught entrepreneurship at and the, and was elected to Fastcase 50, recognizing the top 50 legal innovators in the world. His writing has been featured in,,,,,,, and many other publications. He was nominated for a Pulitzer Prize .

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Today, it’s not enough to disrupt the market — you have to anticipate the rule-set that will govern it.

Investors are shifting gears. After a decade of “move fast and break things,” they’re asking: Who built the compliance engine before the crash? Because the truth is, regulation has become a form of alpha — a competitive advantage for startups that think of law not as a hurdle, but as a moat.

The new era of smart compliance

The startup landscape has changed. High-profile failures — from crypto exchanges to wild valuations in fintech and AI — taught us that the regulatory cost of growth can be massive. Today’s investors and founders alike expect legal strategy from day one, not as an afterthought.

Consider the RegTech market: projects it will swell to about $70.64 billion by 2030, growing at a compound annual rate of roughly 23%. predicts growth to $70.8 billion by 2033. The message: Companies are no longer asking if they need compliance automation and legal-engineering infrastructure. They’re asking when they can monetize it.

So when a startup designs its product around KYC, AML, data-protection or licensing from the outset, it’s not just avoiding risk — it’s building a moat others will struggle to cross. For founders, regulation isn’t just the cost of entry anymore — it’s the cost of exit-edge.

When the law becomes a moat

There are former unicorns, and there are regulation-ready unicorns. The difference hinges on when they built their compliance architecture, hired legal engineers and treated regulation as product.

Take payment infrastructure: built , as Stripe’s PCI Level 1 certification and multijurisdiction licenses (U.S. money-transmitter, EU/UK e-money) enabled it to integrate cleanly with Pay, power ’s native payments, and — per a 2023 announcement — expand its role processing payments for .

Or look at crypto: , publishing its U.S. money-transmitter licenses and securing New York’s BitLicense in 2017. Its 2021 SEC S-1 repeatedly frames regulatory compliance and licensing as fundamental to the business.

In insurtech, from the outset, hired senior insurance veterans (e.g., former executive ) and, per its S-1 and subsequent filings, , operationalizing the 50-state regulatory landscape rather than trying to route around it.

These examples show a pattern: When compliance is built in from the start, the cost of scaling drops and competitors face much higher entry bars. Regulation becomes a moat — not a burden.

The rise of ‘legal engineering’

Welcome to the era of the legal engineer. The traditional model (sign contract, then lawyer reads, then flagged risk) is being replaced by code, automation and internal teams who speak both product and law.

Startups such as built cap-table software that includes “,” allowing it to embed governance and securities-law readiness into the product nature of equity management.

(e.g., Section 1033) by building features such as data transparency messaging and consent-capture into its API stack — indicating a clear regulatory-first posture in its product roadmap.

And what’s happening in AI? Founders are hiring general counsels on day one to forecast imminent regimes — privacy law (GDPR, CCPA), AI transparency bills, emerging algorithms-as-infrastructure regulation.

The startup battle isn’t simply product vs. product anymore — it’s regulatory architecture vs. regulatory architecture.

Reports back this up: One credible industry estimate shows . In short: Startups that solve compliance at scale are building infrastructure for everyone else to rent. That’s platform-level potential.

Investors are taking note

Regulation-ready startups aren’t just surviving — they’re attracting smarter capital. Venture funds now assess regulatory maturity, legal runway and governance readiness early on. A startup that can show it isn’t “waiting to deal with compliance” but designed it, has a valuation edge.

Crunchbase data shows global startup funding reached $91 billion in Q2 2025, up 11% year over year. While not all of that is focused on law or compliance, the trend signals that smart investors are buried deeper in risk assessment and governance. Legal tech funding is accelerating, too: the sector recently topped $2.4 billion in venture funding this year, an all-time high.

Funds are no longer only assessing TAM or go-to-market speed; they’re asking: “What’s the regulatory runway? Who owns risk? Who built the compliance pipeline?” Because in sectors like fintech, climate tech, health tech and AI, the fastest growth path is often the one that avoids the enforcement arm.

The future: law as competitive advantage

Let’s zoom out for a moment. We’re moving into a world where regulation isn’t a ceiling — it’s scaffolding. It defines markets, enables scaling and filters winners from pretenders. Founders who see law as a source of architecture, not as chewing-gum-on-the-shoe, will be the ones writing the playbook.

Think about AI: Startups that design for regulatory change (data-provenance, audit trails, rights management) are already positioning for the future.

Think about climate tech: Companies that can navigate evolving carbon-credit regimes or ESG disclosure laws are building invisible advantages.

Think about fintech: Those that mastered licensing, KYC/AML, consumer-data flows early are the backbone of infrastructure.

The next wave of unicorns won’t just have better tech — they’ll have truly infinitely better legal DNA. They won’t just disrupt a market; they’ll help write the rules of the market before they scale.

Because in this new era, regulation isn’t a deadweight — it’s a launchpad.

is the chief strategy officer for. He holds a law degree and has taught entrepreneurship at and the, and was elected to Fastcase 50, recognizing the top 50 legal innovators in the world. His writing has been featured in,,,,,,, and many other publications. He was nominated for a Pulitzer Prize .

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The U.S. government is the client for thousands of young companies, especially those in defense tech, climate tech, biotech and AI. A pilot program, an grant, an loan guarantee — these aren’t just contracts. They’re lifelines that validate your product, unlock venture funding and keep the team paid.

But contracts don’t mean much without appropriations. If the agency you’re working with doesn’t have authority to spend, the invoices sit in limbo. The most dangerous thing about a shutdown is that startups can do everything right — sign the deal, hit the milestones, file the paperwork — and still get left holding the bag.

That plays out in the one metric founders obsess over: runway. Most early-stage startups don’t have a year of cash just sitting there. If a big federal payment is frozen, it’s not just an accounting hiccup. It can cut months off survival time. Payroll suddenly looks dicey, milestones start slipping and investors get jumpy.

One defense tech founder told me, “We can survive a late-paying Fortune 500 client. We can’t survive a silent Pentagon.”

That’s the difference: Corporate clients might be slow, but they don’t disappear overnight because Congress got stuck in neutral.

Government as gatekeeper

And this isn’t just about cash flow. The government is also a gatekeeper. Need an green light for your trial? Need the to guarantee your loan? Need the to review your filing? If staff are furloughed, those processes stall. That delay ripples.

A biotech waiting on an FDA sign-off can lose an entire quarter of momentum. A climate startup waiting on a loan guarantee can watch investors walk. A fintech can’t move forward with an unanswered SEC question. In the startup world, where speed is survival, three months of dead air can be terminal.

If this all sounds familiar, that’s because it is. . Startups that leaned heavily on federal programs got walloped. A few pulled through by grabbing bridge financing or deferring expenses, but a lot of promising young companies simply ran out of oxygen. The ones that survived weren’t necessarily the best products — they were the ones whose founders had already gamed out what a shutdown meant for their business.

That’s the reality investors are grilling founders on right now. If you’re pitching in October 2025, you’re going to get one question before anyone cares about your TAM or your roadmap: “How exposed are you to the shutdown?”

Hand-waving won’t cut it. VCs want to see the actual scenarios: What happens to your cash if this drags on one month, three months, six months? How much revenue is locked up in frozen contracts? Do you have any commercial customers or international deals to balance it out?

A lot of valuations in defense and climate tech are going to get haircuts not because the ideas aren’t good, but because the revenue dependency is too concentrated in Washington, D.C.

What startup founders can do

So what should founders do?

First, over-communicate. Investors, employees and partners would much rather hear you acknowledge the risk than pretend everything’s fine.

Second, conserve cash. Delay nonessential spending, stretch out hiring, get creative on expenses.

Third, read your contracts carefully. Too many startups assume a signed agreement means money in the bank. It doesn’t if appropriations dry up. Know whether you can legally pause performance or if you’re on the hook to keep delivering with no payments coming in.

And fourth, diversify where you can, even if it feels inefficient. The startups with at least some commercial or international revenue are the ones with a cushion when Washington freezes.

Shutdowns also put the spotlight on something founders don’t like to think about: political risk. It’s not just noise on . It’s as real as supply chain delays or product-market fit.��

If shutdowns become a near-annual bargaining chip, the whole pitch about the government being a “stable anchor customer” starts to crumble. For , a shutdown is an inconvenience. For a 12-person startup in Arlington, it’s life or death. And if startups start backing away from government deals because they can’t stomach the uncertainty, that’s bad for everyone — especially the government, which needs their innovation in defense, AI and climate more than ever.

This is where resilience comes in. A shutdown isn’t a founder’s fault, but surviving one is part of the job. The smart teams are treating this as both a financial and legal challenge. They’re cutting burn, talking openly with investors, stress-testing scenarios, and yes, even calling lawyers about whether they can file declaratory judgments or push agencies for clarity. None of that is fun, but it’s better than waiting around and hoping Congress figures it out.

The bottom line is simple: political risk is business risk. When your primary customer folds overnight, it doesn’t matter how brilliant your tech is or how slick your deck looks. What matters is whether you’ve built a company resilient enough to survive the silence until Washington switches back on.

For now, the shutdown is only days old. Courts are still open, agencies are quiet, and founders are refreshing their bank dashboards like always. But the lesson is already obvious. Startups can’t afford to treat shutdowns as background noise anymore. They’re a line item in your financial model, a question in every term sheet, and a reality you have to plan around. If you don’t, the government might not be the only thing shutting down this fall.

�� is the chief strategy officer for. He holds a law degree and has taught entrepreneurship at and the, and was elected to Fastcase 50, recognizing the top 50 legal innovators in the world. His writing has been featured in,,,,,,, and many other publications. He was nominated for a Pulitzer Prize .

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For Google, this was less a day of reckoning than a day of relief.

Appeal, appeal, appeal

The first thing to remember is that Google has already promised to appeal. And when companies like Google say “appeal,” they don’t mean a quick trip to the neighborhood court down the street.

They mean a drawn-out legal odyssey that could land in the and take years to resolve. By then, your phone will be on its fourth software update, and this case will still be slogging through briefs and oral arguments.

Anyone expecting change next week — or even next year — should keep waiting.

Keeping Chrome is the real win

The government wanted a structural remedy — something dramatic, like forcing Google to sell Chrome. That didn’t happen. Google gets to keep Chrome, the digital crown jewel that anchors its empire.

Yes, Google now has to share some search results and data with rivals. But the fact that it didn’t have to break itself up is a huge victory. Google lost a battle but kept the castle.

Time is on Google’s side

Even the new requirements aren’t immediate.

Before rivals see anything meaningful, the lawyers will still be wrangling. That means Google has what it loves most: time. And if there’s one thing Google knows how to do, it’s innovate around obstacles.

Does anyone really doubt that the company is already devising ways to turn forced data-sharing into yet another advantage? By the time rivals get their hands on what they think will be game-changing access, Google will have made it just another footnote in its playbook.

Google’s PR machine will spin this gold

Beyond the courtroom, Google’s public-relations operation is already at work, painting Tuesday’s ruling not as a setback but as a vindication.

Expect to hear lines about how Google isn’t just defending its business — it’s defending your right to use the technology you love. In other words, they’ll turn “we lost a case” into “we fought for you.”

And you know what? A lot of people will buy it, because Google is still one of the most powerful brands on the planet.

Big Tech is watching — and taking notes

The biggest long-term effect of this ruling may not be on Google at all. Other Big Tech giants are now watching closely. If the worst consequence of an antitrust trial is that you have to share some data — but you still get to keep your most valuable assets — why not take the risk? This outcome doesn’t scare , or . It emboldens them.

The takeaway isn’t “be careful.” It’s “go ahead, roll the dice.”

The big picture

So what do we really have here? Not a structural breakup. Not a company-splitting mandate. Not the dismantling of one of the most profitable business models in history. Instead, we have a ruling that says: stop being quite so exclusive with your deals, share some data with rivals, and carry on.

It’s a partial slap on the wrist dressed up as a thunderclap. And the beauty for Google is that while it fights the appeal, it still gets to do business as usual. Chrome remains untouched. remains untouched. The search default deals aren’t entirely dead. And Google gets years to tweak, adjust and innovate its way around the edges.

So here’s the effective executive summary:

Headlines said: “Google punished.”
Legal reality says: “Google survives, mostly intact.”

That’s not exactly a cautionary tale. It’s a survival story. And in Silicon Valley, survival stories usually come with stock bumps, not stock slides.

A shrug, not a shock

When history books cover this case, it will be tempting to label Tuesday’s ruling as the day Google finally met its match. But in reality, this was more of a speed bump. The appeals process alone will drag things out long enough that the “new rules” might feel old by the time they arrive. And by then, Google will have turned compliance into yet another competitive advantage.

If you’re a rival search engine hoping this is your moment, don’t pop the champagne just yet. You may find yourself drinking Google’s leftovers while it keeps baking the bread.

And if you’re a user, don’t expect radical change in your daily digital life. Chrome will still be Chrome. Search will still be Google. And the company will still be as dominant — and as self-confident�� —as ever.

Tuesday wasn’t the antitrust climax. It was a reminder that when you’re dealing with a company like Google, the real story isn’t what the court orders. It’s what Google does with the time the courts give it. And right now, Google has time in spades.

is the chief strategy officer for. He holds a law degree and has taught entrepreneurship at and the, and was elected to Fastcase 50, recognizing the top 50 legal innovators in the world. His writing has been featured in,,,,,,, and many other publications. He was nominated for a Pulitzer Prize .

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, the company behind them, , just secured $40 million to ramp up production from 16 robots to 100 by next year. Their machines are already working in Canada, the United States, Ireland, the Netherlands and Australia. What sounds like a quirky Canadian tech story is, in fact, a preview of a much bigger reality.

Buckle up, America. This isn’t just the friendly “technology makes everything faster, cheaper, and more efficient” kind of story. This is the other kind — the one where technology steps in not because it’s better than humans, but because the humans simply aren’t there anymore.

In Canada, as in the United States, agriculture depends heavily on seasonal and migrant labor. The says thousands of farm jobs go unfilled every year, and the shortage is only getting worse. Farmers are desperate for workers, and when they can’t find them, they start looking at automation not as a nice-to-have, but as the only option.

In the U.S., the equation is even more acute. ’s aggressive immigration crackdowns, combined with the expanded enforcement powers of and Homeland Security, have dramatically reduced the number of foreign workers able to take the low-wage, physically demanding jobs Americans have historically avoided.

You can debate whether that’s good politics, but it’s bad farm economics. When you remove the labor supply without replacing it, something has to fill the gap.

And in agriculture, that “something” is increasingly robots.

The migration from human hands to machine arms isn’t limited to mushrooms. AI-guided strawberry pickers, robotic lettuce thinners and self-driving orchard sprayers are already in the field. Automation is moving into agriculture faster than most people realize, largely because labor shortages are forcing the pace. Ten years ago, these technologies were experiments. Today, they’re line items in farm budgets.

One-way street

Here’s the uncomfortable truth: The debate over immigrant labor in agriculture is no longer about whether Americans “should” do these jobs. It’s about whether those jobs will exist for people at all. The more we constrict the labor pipeline, the more we incentivize capital investment in automation — and once a robot is doing the work, that job isn’t coming back, no matter what immigration policy looks like down the road.

This is not to say automation is the villain. In some cases, robots can make farm work safer, less physically punishing and more precise. But when technology is adopted out of necessity rather than design, the transition can be abrupt, messy and economically disruptive. Small farms may struggle to afford the investment. Rural communities that rely on seasonal labor could see their local economies hollowed out.

The mushroom robots in Salmon Arm are just one case study, but they illustrate the future we’re hurtling toward. In the short term, they’ll fill labor gaps. In the long term, they’ll reshape how we think about the agricultural workforce — and by extension, the immigration policies that have sustained it for decades.

So, America, take a good look north. The robots are coming. Not with malice, not with malfunctions straight out of a sci-fi thriller — just with a steady, unblinking AI gaze and a suction cup hand, ready to harvest your dinner. If we want to decide how, when and where they’re deployed, now is the time to have that conversation.

Because if we wait until the mushrooms are picked, packed and shipped without a single human hand involved, the debate won’t be about immigration or labor shortages anymore. It will be about what happened to the jobs we thought we could get back.

is the chief strategy officer for. He holds a law degree and has taught entrepreneurship at and the, and was elected to Fastcase 50, recognizing the top 50 legal innovators in the world. His writing has been featured in,,,,,,, and many other publications. He was nominated for a Pulitzer Prize .

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The streaming giant, under the leadership of , has openly embraced AI to speed up and cheapen visual effects production, turning what once took weeks of painstaking labor into something achievable in days.

While this might seem like a straightforward efficiency gain, the implications ripple far beyond production schedules and budget sheets. The integration of AI tools is reshaping the very nature of storytelling, the economic lifelines of creative workers, and the power dynamics that govern the industry.

Where does the algorithm end and the artist begin?

Historically, Hollywood has always adapted to technological revolutions — sound, color, CGI — yet AI’s arrival is different. It’s not just a new tool. It’s an autonomous creative force capable of generating imagery, animating sequences and even proposing edits without direct human command.

This blurs the lines between artist and algorithm, prompting a reexamination of what constitutes creativity and craftsmanship. For visual effects artists and technicians — the backbone of blockbuster spectacle — AI threatens to hollow out entry-level and mid-tier positions. The painstaking frame-by-frame work that once provided a path into the industry risks being supplanted by automation. This could concentrate creative control in fewer hands, reducing the diversity of voices shaping our visual culture.

Potential for decentralization

But paradoxically, . Tools like Runway’s can empower smaller creators, independents and digital-native artists who lack big-studio budgets to produce effects-rich content. Suddenly, a one-person operation can conjure worlds once reserved for teams of hundreds.

This could decentralize Hollywood’s longstanding gatekeeping and nurture fresh storytelling. Yet the question remains: Will the industry embrace this decentralization, or will it instead harness AI to entrench existing hierarchies, commodify creativity and optimize content for algorithmic consumption?

The coming war over content creation

The stakes extend well beyond workers and artistry. For Netflix and other streaming behemoths, AI is a strategic lever in an increasingly cutthroat entertainment landscape. ’s underscores a looming tech war over who owns the future of content creation.

The ability to quickly generate and iterate special effects offers studios unprecedented control — lower costs, faster turnaround and the luxury of endlessly testing content for maximal viewer engagement. But this could tip storytelling toward formulaic, data-driven output, where creative risk is stifled by algorithms optimizing for clicks and watch time rather than daring ideas or cultural resonance.

What happens to Hollywood’s workforce as these changes unfold? While AI inevitably replaces certain manual tasks, it also creates new roles — AI supervisors, creative technologists, machine learning editors. The challenge is that these roles often require specialized skills and access to training, meaning the shift will not be seamless or equitable.

Mid-level artists without the resources to reskill may be left adrift. This labor disruption, layered atop an industry already marked by precarious freelance work and systemic inequality, could deepen divides between those who control AI tools and those displaced by them.

Creators rights and other thorny ethical questions

Beyond economics lies an ethical morass. As I have recently covered, AI-generated imagery complicates traditional notions of authorship and ownership. When machines remix and generate new visuals based on millions of prior works — often without consent or compensation for the original artists — what are the rights of creators? Legal frameworks struggle to keep pace, leaving many in limbo.

Audiences, too, may question the authenticity of content created or heavily manipulated by AI. The unique human spark in performance and artistry risks dilution when machines shoulder creative burdens.

Transparency and collaboration

Despite these tensions, the best path forward embraces collaboration between humans and machines. AI should be a co-creator, not a cold replacement. The industry must involve creative workers in how AI tools are developed and deployed, ensuring technology amplifies rather than erases human skill and expression. Labor unions and guilds must negotiate protections that reflect this new reality, guaranteeing fair pay for AI-assisted work and retraining programs that democratize access to new creative roles.

Transparency will be critical. Audiences increasingly demand to know how content is made — not just for ethical clarity but to preserve cultural trust. Imagine a future where productions disclose the degree of AI involvement, enabling viewers to appreciate the hybrid nature of modern storytelling. Such openness could inspire new appreciation for the artistry in directing AI, much as visual effects artists today are celebrated for their craft.

Netflix’s embrace of Runway’s AI signals not just a new chapter in production tech but a watershed moment for Hollywood’s creative and economic future — a moment brimming with dazzling potential and equally profound peril.

The industry faces a crossroads: Wield AI to empower a broader spectrum of storytellers and elevate human artistry, or let it become the blunt instrument that deepens inequality, commodifies creativity and centralizes control in the hands of a few data-rich studios.

This is more than a technological upgrade; it’s a fundamental reckoning about who gets to shape culture in an AI-driven world. The question is not just if machines can create, but who holds the reins when algorithms generate the worlds we escape to — and what happens to the millions whose creativity built Hollywood in the first place. If we fail to keep humanity at the center, we risk trading in artistry for efficiency — and losing the soul of storytelling itself.

In the race to automate imagination, Hollywood must choose whether AI will be its muse or its master — and whether the future of film will be written by many hands or just the cold algorithms of a few.

is the chief strategy officer for. He holds a law degree and has taught entrepreneurship at and the, and was elected to Fastcase 50, recognizing the top 50 legal innovators in the world. His writing has been featured in,,,,,,, and many other publications. He was nominated for a Pulitzer Prize .

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The scraping, according to Cloudflare, has surged 18% in the past year. Some publishers, like , are cutting licensing deals with while also trying to choke off what it calls “bad actors.” But here’s the hard truth: All of this defensive maneuvering is like boarding up the windows after the storm has already blown through. AI isn’t breaking in. It’s building something new entirely — and the smart move is to get invited inside.

Don’t get left behind

From where I sit, paywalls, as a concept, are seriously living on borrowed time. They’ve always relied more on friction than loyalty. People subscribed to read one article, forgot to cancel, or clicked out of guilt when their free views ran out. That model was always fragile — and generative AI is exposing the cracks.

Today, most people don’t need to visit 10 different sites to get the news. They want fast, portable summaries. They want context in the same breath as content. LLMs don’t need to copy your article to kill your traffic — they just need to remove the need for it. If ChatGPT can give a clear, concise, accurate answer to “What happened in Gaza this morning?” — most users won’t click through to five full-length op-eds. And if your outlet has banned crawlers, congratulations — you’ve made yourself invisible in the only newsroom that matters now: the one inside the machine.

The fight to protect so-called proprietary content profoundly misunderstands the nature of content (and fully lacks nuance) in 2025. Text is already a remix culture. News sites summarize other news sites. Bloggers paraphrase headlines. Analysts repackage coverage with “insights.” Even the most original scoop gets sliced, quoted and tweeted into a dozen versions within hours.

AI doesn’t change that — it automates it. Fighting that is like fighting email because it made fax machines obsolete. What’s more, AI-generated summaries often increase the visibility of high-quality reporting. If a chatbot cites your outlet regularly, that’s reach. If it gets the gist of your piece exactly right, that’s influence. Banning AI from seeing your work doesn’t stop your ideas from spreading — it just cuts you out of the credit cycle. It’s like a professor trying to stop their research from being cited in academic papers because they didn’t approve the footnotes.

A better path

Publishers should be working to collaborate with AI platforms, not wall them off. Embed metadata that tells LLMs who wrote the piece. Build deals that prioritize your bylines, link back to your coverage, and let your headlines flow through these models with attribution. Become the signal in a sea of synthetic noise.

That’s what . That’s what smart publishers will do with ’s AI Overviews. If a model starts defaulting to , or because those sources made themselves indexable, consistent and AI-friendly, that’s not a loss of control. That’s a win in brand equity, reach and reader trust. You want the machines quoting you, not ghosting you.

Here’s the omnipresent reality: The entire next generation of news consumers will meet the world through AI.��

When a teenager in Kansas asks their AI assistant why the Supreme Court overturned a precedent, or a voter in Arizona asks about a candidate’s housing record, they won’t be thumbing through newspaper archives. They’ll get a verbal summary in eight seconds.

If your journalism doesn’t appear in that summary, you don’t exist in that conversation. It’s not that AI is replacing the value of journalism — it’s replacing the pathway to it. And the publishers who treat AI as an enemy will learn, too late, that they trained their successor not to remember them.

The future of media isn’t behind a wall. It’s in the bloodstream. It’s in training sets, in embedded links, in smart attribution, in being so good that even the robots want to get the story right. There’s no dignity in hiding. And no sustainability in suing your way back to a broken business model. If you want to survive, stop worrying about how to keep the bots out — and start thinking about how to make sure they cite you when it counts.

is the chief strategy officer for. He holds a law degree and has taught entrepreneurship at and the, and was elected to Fastcase 50, recognizing the top 50 legal innovators in the world. His writing has been featured in,,,,,,, and many other publications. He was nominated for a Pulitzer Prize .

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No, not news about AI. News from AI.

Yet it took an to really bring this subtle but seismic shift into our news cycle. The AFP piece highlighted findings from a major global survey showing that growing numbers of people — especially younger audiences — are turning to AI chatbots like ChatGPT for their daily news updates.

From where I sit, I see this as a foundational moment, one in which users start treating large language models including ChatGPT, Gemini and Claude as trusted explainers — asking, “What’s happening in Gaza?” or “Why did the Fed pause hikes?” It isn’t hyperbole to say that this may be the moment — or at least the beginning of a series of moments — where traditional gatekeepers lose more than traffic. They lose relevance.

And here’s the part that’s being missed in the coverage on all of this: If young people are already trusting AI to deliver world events, it’s only a matter of time before they trust it to deliver something more personal, like a lawyer.

We’re not talking distant-future, sci-fi speculation. We’re talking about the near-term consumer behavior shift that will define how professional services are discovered, filtered and selected in the next 12-24 months.

AI, the new UX layer

Think of it this way: LLMs are rapidly becoming a UX layer on top of human expertise. They’re compressing complexity, stripping jargon and generating natural-language answers that feel more “human” than many actual humans. Combine that with personalization, fine-tuning and soon multimodal memory — and suddenly the chatbot becomes not just an explainer, but a concierge.

What’s an obvious use case for that dynamic? Legal advice.

Ask any 22-year-old what they’d do if they got rear-ended by an uninsured driver. Many won’t search for a personal injury lawyer. They’ll open an AI app and type something like: “What do I do if I get hit and the other driver doesn’t have insurance in Florida?” They’re not necessarily looking for a statute. They’re looking for clarity. Empathy. A next step.

That prompt isn’t the start of a search. It is the search.

If the AI answers clearly and concisely, it becomes the user’s first trusted interface with the legal system. And from there, the AI can suggest a relevant firm, link to an intake form, or route the user directly to a booking calendar. In short: LLMs are going to become high-intent lead gen machines for lawyers, doctors and every other professional who’s historically relied on SEO, referrals or .

The coming sea change for professional services

The shift from “search engine” to “answer engine” has been discussed for years. But we’re now watching it happen in real time — and professional services aren’t ready.

Legal services in particular have long been immune to disruption because they’ve hidden behind regulatory insulation, geographic moats and old-school word-of-mouth. But the AI layer doesn’t care about any of that. A good LLM doesn’t need to know your bar number — it just needs to know how people ask legal questions and what a competent, jurisdiction-specific answer should sound like.

That’s why some law firms are already building their own GPTs — custom-trained legal assistants that sit natively on their websites and handle intake. Others are feeding vector databases with cleaned verdicts, client FAQs and state-specific procedures to make their firms “AI-readable” in the next wave of query-routing tools.

The ones thinking a step further are trying to get inside the models — via licensing deals, training partnerships or API-driven apps that plug directly into platforms such as ChatGPT’s GPT Store.

Because let’s be honest: If your law firm doesn’t show up in the AI’s output, you’re invisible to the next generation of clients.

Yes, there are concerns — about hallucinations, bias and opaque decision-making. The Reuters report notes that many users still think AI makes news less trustworthy. But here’s the thing: they use it anyway.

Just like they use influencers they don’t fully believe, or platforms they know are tracking them. In the tradeoff between frictionless utility and idealistic purity, utility almost always wins.

And to the skeptics who argue that people won’t trust a bot with something as serious as finding a lawyer, remember: People already trust bots with something more serious — their health. From symptom checkers to AI-powered second opinions, the healthcare space has embraced LLMs faster than nearly any other sector. Law will follow.

Introducing, vertical-specific copilots

If you’re building in the AI space, this is the next great interface opportunity: vertical-specific copilots for decision-making in high-stakes, high-trust domains.

Let that sink in — legal, medical, financial. Not just generalist tools, but deeply trained advisers built on real data, validated expertise and intuitive UX. And if you’re a law firm — or any other professional service provider — it’s time to stop thinking of AI as just another marketing tool. It’s about to become your first impression.

We are entering the “unbundling of expertise.” Not the end of professionals, but the end of finding professionals through slow, analog pathways. In their place: real-time, language-based interfaces that shortcut years of institutional inertia.

AI isn’t here to take your lawyer’s job — it’s already taking your client’s attention. And in a business built on trust, attention isn’t just the starting point. It’s the whole game.

is the chief strategy officer for. He holds a law degree and has taught entrepreneurship at and the, and was elected to Fastcase 50, recognizing the top 50 legal innovators in the world. His writing has been featured in,,,,,,, and many other publications. He was nominated for a Pulitzer Prize.

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This ruling was short-sighted when the case was heard. It’s practically absurd now. Because what the court has failed to grasp is that this isn’t really about lawyers buying names — it’s about AI doing it for them.

How it happens

Let’s set the scene. A prospective client searches for “Jane Smith, Esq.” The first result? A paid ad for “John Doe, Esq.” — Jane’s competitor. The user clicks, thinks they’re contacting Jane, but ends up on John’s site. Click. Convert. Case stolen.

The Court says that because the ad is labeled “Sponsored” and doesn’t explicitly lie, it’s not unethical. That’s a distinction that maybe held water 10 years ago. In the age of generative AI and programmatic bidding? It’s like trying to catch rainwater with a sieve.

The truth is, no human lawyer is sitting at their desk targeting individual competitors anymore. This is all done at scale by AI-powered marketing platforms. One prompt, and the system can purchase thousands of competitor names in real-time. Add in AI-generated ad copy — optimized through continuous A/B testing — and you’ve created a self-improving deception engine. Today’s keyword games are tomorrow’s identity theft loops.

The Court compares this to opening a sandwich shop next to a popular deli. But in the AI era, it’s more like building a robot that runs ahead of you on the sidewalk and slaps your brand on the nearest signpost. And when a potential customer asks, “Is this the place I heard about?” the bot just nods and smiles.

AI’s giant step ahead

Even the court’s requirement that advertisers include disclaimers is laughably out of step with digital reality. As of New Jersey law firm The Epstein Law Firm P.A., put it:

“The disclaimer is just a fig leaf. AI will keep optimizing the copy until it gets the click. The deception will persist — and clients will keep being misled.”

And make no mistake: AI doesn’t just outwork human marketers — it outpaces regulation. That’s the real problem. We’ve now entered a world where lawyers have to bid on their own names just to stay visible in search results. We’re not marketing our firms — we’re paying ransom to ’s algorithm to protect our reputations.

What the court green-lit isn’t just misleading. It’s a fully automatable, scalable form of reputational arbitrage.

And if they think today’s keyword bidding is bad, wait until generative agents are unleashed across marketing stacks. They won’t just hijack a name — they’ll spin custom landing pages, tweak geotargeting and modify tone based on the user’s IP address. All without human intervention. All within the bounds of what the Court just said is “not unethical.”

There was a better option: ban the practice. Draw a bright line. You want to advertise? Use your own name. Build your own brand; don’t feed someone else’s into the AI mill.

Until that happens — by rule, legislation or sheer market revolt — New Jersey lawyers will find themselves in a never-ending battle against bots bidding on their identity. It’s not clickbait anymore. It’s clickwarfare.

And the court just told the machines: fire at will.

is the chief strategy officer for . He holds a law degree and has taught entrepreneurship at and the , and was elected to Fastcase 50, recognizing the top 50 legal innovators in the world. His writing has been featured in , , , , , , , and many other publications. He was nominated for a Pulitzer Prize .

Related reading:

• AI Isn’t the Answer To Our Education Crisis — It’s a Distraction
• Can We Please Still Have Nice Things That AI Hasn’t Touched?
• Stealing Ghibli: How AI Has Crossed The Line Into Creative Theft
• Who Owns Your Face? The Legal Fight for Identity In The Age of AI
• When Legal Tech Fails: The California Bar Exam Disaster And The Risks Of Blind Innovation

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And now, in the same surreal timeline, we’ve got signing — directing the and the to prioritize funding for AI-related research and grants.

You truly can’t make this stuff up and even if you could, you no longer have to.

To be clear: I’m not anti-technology. AI has a role to play in education. Personalized learning, intelligent tutoring systems, data-driven insights — these are powerful tools when used thoughtfully. But let’s not kid ourselves. We’re living through a moment where the Trump 2 administration is taking a DOGE chainsaw to the very foundations of public education. And instead of confronting that, we’re being told to get excited about chatbots in the classroom.

This isn’t leadership. It’s deflection.

Funding for future success

The truth is, AI is not the lifeline our education system needs. Certainly not right now. What we need — what we’ve needed for decades — is serious investment in teachers, classrooms, infrastructure and support services. And we’re getting the opposite.

The Trump administration is proposing deep cuts to key education programs, gutting federal support for public schools, and pushing policies that favor privatization and deregulation over student success. Amid all that, we’re supposed to believe that some AI-powered lesson plans are going to move the needle?

Please.

Let’s start with the obvious: AI doesn’t fix underfunded schools any more than A1 sauce would. You can’t put an algorithm into a building with no heat, no internet and no functioning restroom and expect a miracle. You can’t expect a teacher managing 35 kids on her own to suddenly have the time and training to integrate AI into daily lesson plans (if they even have the time to make one actual lesson plan a week). And you can’t tell communities that are already struggling to get basic resources that what they really need is machine-learning software.

This executive order assumes that what’s missing in American education is innovation. But we don’t have an innovation problem — we have a priorities problem. Our students aren’t falling behind because teachers aren’t tech-savvy enough. They’re falling behind because our country refuses to treat education like a public good.

What’s broken

We’ve normalized schools with outdated textbooks, overworked staff and dilapidated facilities. We’ve made it acceptable for teachers to buy their own supplies, for students to skip meals, and for mental health crises to go unanswered.

And now, in the middle of that, this administration wants to convince us that the real problem is that we’re not moving fast enough on AI.

Let’s also be honest about what AI in schools usually means. It doesn’t mean teachers getting sophisticated tools that make their jobs easier. It means more standardized testing, more data collection, more screen time and more surveillance, especially for kids in low-income communities.

It means feeding student information into systems built by private companies, often with little oversight or transparency. It means potentially outsourcing educational decisions to algorithms that don’t understand context, nuance (sidebar: do any of us get nuance anymore?) or humanity.

It’s a far cry from the glossy pitch the administration is selling.

Widening the digital divide

And let’s not ignore the inequity intentionally baked into all of this. AI-enhanced education requires reliable internet, up-to-date devices, tech-literate staff and digital infrastructure — things that affluent districts are more likely to have. For schools in underserved areas, this push risks widening the digital divide under the guise of modernization.

What’s being framed as progress is actually an elegant Trojan horse for deeper inequality. The schools that most need real, human-centered support are the least likely to benefit from this initiative.

It’s particularly galling that all this is being rolled out with a heavy dose of PR spin. The A1 comment might’ve been a gaffe, but it was also revealing. It showed just how deeply unserious this administration is about the reality on the ground in American schools. It was meant to sound cool, forward-thinking, maybe even meme-worthy. Instead, it became a symbol of how disconnected Trump’s appointee is from what’s actually happening in classrooms across the country.

What schools really need

Teachers aren’t asking for AI. They’re asking for manageable class sizes, fair pay, mental health resources and the ability to teach without being completely buried by bureaucracy. Students aren’t crying out for machine learning — they’re asking for support, stability and a system that sees them as more than test scores or data points. And parents aren’t begging for the latest edtech. They want to know their kids are safe, challenged and cared for at school.

AI is a tool. That’s it. It’s not a savior, it’s not a substitute, and it’s certainly not a replacement for public investment. If the Trump administration were serious about improving education, it would be fighting to expand school funding, not slash it. The administration would be making college more affordable, not reversing progress on student debt. It would be strengthening teacher pipelines, not weakening them. And it would be protecting public schools, not undermining them.

Instead, we get a photo op and a tech policy wrapped in buzzwords.

So yes, Secretary A1, AI has its place. But until we’re ready to fund schools like they matter, treat educators like professionals, and address the real, systemic issues at the heart of this crisis, all the artificial intelligence in the world won’t save us.

And that’s not artificial. That’s just reality.

is the chief strategy officer for . He holds a law degree and has taught entrepreneurship at and the , and was elected to Fastcase 50, recognizing the top 50 legal innovators in the world. His writing has been featured in , , , , , , , and many other publications. He was nominated for a Pulitzer Prize .

Related reading:

• Can We Please Still Have Nice Things That AI Hasn’t Touched?
• Stealing Ghibli: How AI Has Crossed The Line Into Creative Theft
• Who Owns Your Face? The Legal Fight for Identity In The Age of AI
• When Legal Tech Fails: The California Bar Exam Disaster And The Risks Of Blind Innovation

Illustration: