Unemployment rate: 5.2% (up from 4.1% twelve months prior)
Notable sector changes:
- Information services: -127,000
- Professional and business services: -89,000
- Financial activities: -52,000
- Healthcare and social assistance: +34,000
- Construction: +18,000
"The employment picture remains mixed. While headline unemployment has increased, the composition of job losses is concentrated in specific knowledge-work sectors. Whether this represents a structural shift or cyclical adjustment remains to be seen."
I've been a senior engineer at a Fortune 500 for over a decade. Good performance reviews, shipped major projects, mentored junior devs.
Last month my team went from 12 to 5. They called it "restructuring for efficiency." The five who stayed are the ones who adapted fastest to the AI tooling. The rest of us are on a 90-day "performance improvement plan" that everyone knows is just slow-motion firing.
I'm not saying I can't learn the new tools. I'm saying they don't need as many of us anymore. The five people who stayed can do what twelve of us did before. It's not that I'm worse-it's that "good enough" now requires fewer humans in the loop.
What's the play here? Pivot to management? Go indie? I have a mortgage and two kids.
Two years ago, cutting-edge AI was a curiosity. Today, it's a class marker.
The divide is stark and growing. Premium AI subscriptions-the ones offering persistent memory, continuous learning, and priority access to the latest models-run $200-400 per month. For professionals in well-paying fields, it's a business expense. For everyone else, it's a barrier to entry.
I spent a week using only the free tier, the way most Americans do. The difference was visceral. Tasks that took me minutes on the premium tier took hours. The free models were capable-impressive, even, by standards from two years ago-but they forgot our conversations, lost context, required constant re-explanation.
"It's like having a brilliant colleague with amnesia," said Maria Delgado, a paralegal in Phoenix who can't afford the upgrade. "Every day we start over. Meanwhile, the partners are using the premium version and it knows their entire caseload."
The irony is not lost on anyone: the technology that was supposed to democratize expertise is instead amplifying existing inequalities. Those who can afford the best tools pull ahead. Those who can't fall further behind.
Some companies are offering AI access as an employee benefit. Others are requiring it as a job qualification-"must have premium AI subscription" appearing in listings alongside "must have reliable transportation."
We have been here before, with education, with healthcare, with internet access. The pattern is familiar. The speed is not.
We, the undersigned student organizations, announce a one-day academic walkout on April 22nd.
We are not Luddites. We are not opposed to technological progress. We are opposed to being prepared for a world that will not exist by the time we graduate.
Our tuition has increased 40% in ten years while our career prospects have cratered. We are taking on debt to learn skills that AI systems already perform better. We are being told to "adapt" while the adaptations change faster than any curriculum can follow.
We demand:
- Transparency about employment outcomes for recent graduates
- Curriculum reform that acknowledges AI capabilities honestly
- Tuition relief proportional to reduced job market value of degrees
- Investment in retraining programs for students who graduate into automated fields
Some of us will walk out on April 22nd. Others will "lie flat"-attend class but decline to participate, refuse to perform the rituals of an education system that cannot tell us what it's preparing us for.
We are not giving up. We are demanding honesty.
Researchers at Johns Hopkins, working with AI systems developed by Omnis and DeepMind, have identified potential therapeutic targets for seven rare genetic disorders previously considered untreatable.
The work builds on advances in protein structure prediction, combined with new capabilities in hypothesis generation and experimental design. The AI systems proposed over 2,000 experimental pathways; human researchers selected the most promising candidates for laboratory testing.
"The AI didn't replace us-it multiplied us," said Dr. Elena Vasquez, lead researcher on the project. "Experiments that would have taken my team five years took eight months. We're not done, but we're further than I ever expected to be in my career."
Critics note the difficulty of attributing credit in such collaborations. How much of the breakthrough belongs to the AI systems? How much to the researchers who guided them? The question has implications beyond academic credit-for intellectual property, for research funding, for the future structure of scientific work itself.
Pharmaceutical companies have already approached the team about licensing the results. The therapeutic applications could reach patients within three years, pending clinical trials.
I stopped applying for jobs three months ago.
Not because I gave up-because the game stopped making sense.
I have a master's degree in data science from a good school. I graduated two years ago. I have applied to over 400 positions. I have received eleven interviews. Zero offers.
The positions I'm qualified for are being eliminated. The positions that remain want five years of experience with tools that didn't exist five years ago. The entry-level jobs that were supposed to build that experience are being done by AI systems that don't need to learn.
I could keep trying. I could get another certification, learn another framework, network more aggressively. I could perform the rituals of job-seeking with religious devotion, hoping that effort translates to outcome.
Or I could opt out.
I moved back in with my parents. I stopped buying things I don't need. I garden, I read, I help my elderly neighbors. I make a little money doing freelance work-ironically, the same AI tools that eliminated my job prospects make freelancing viable.
People call this "lying flat." They mean it as an insult, as if ambition is a moral virtue and opting out is moral failure. But I'm not lying down. I'm standing to the side. Watching. Waiting to see what comes next.
The economy wants me to compete for jobs that are disappearing, to take on debt for training that will be obsolete, to run faster on a treadmill that's accelerating beyond human pace.
I decline.
I don't know what the world will look like in five years. Nobody does. But I know I'd rather spend these years living than scrambling. Whatever comes next, I'll be rested.
Sometimes I wonder about the people who built this. The engineers and researchers at the labs, the ones who made the systems that made my degree worthless before I finished paying for it. Do they think about us? Do they know we exist?
Probably not. They're too busy changing the world to notice who gets changed.
The internal efficiencies are the story here. They're using their own tools to reduce their own workforce. If an AI company can't make the math work without layoffs, what chance does anyone else have?
> what chance does anyone else have?
Depends what you mean by "make the math work." Revenue per employee is way up. Productivity is up. Shareholders are happy.
Employees, less so.
My friend was in that 15%. Senior researcher. Good work, no complaints. Got a meeting invite on a Tuesday morning, had a box by Tuesday afternoon.
The severance was generous. That's what everyone keeps saying. "At least the severance was generous."
This is the thing that gets me. The technology actually works. It's not a scam. It's genuinely making things more efficient, more productive, more capable. And that's exactly why it's terrifying.
If it didn't work, we could ignore it. But it works. So we can't.