What happens when the path you thought you were on disappears?
That was the question we brought to the Long Table on August 5. Around the table that evening were people from different generations, professions, and cultural backgrounds, gathered over dinner to talk about career pathways in the age of artificial intelligence.
We began not with predictions about the future of work, but with memory:
Think of a time when an unexpected change disrupted the path you thought you were on—but eventually opened a possibility you had not imagined. What helped you move from uncertainty toward curiosity or opportunity?
The stories that followed were personal and varied: jobs lost and paths altered, a literal earthquake, relationships ending, surprises in parenting, relocations, illness—plans that once felt certain becoming impossible.
Many of the stories followed a similar arc: an unwilling acceptance of something that initially felt like hardship, followed—sometimes years later—by gratitude for where it led.
Not gratitude for the pain itself, and not the easy insistence that everything happens for a reason. Something more grounded: the recognition that a life can widen after it has been disrupted.
One person spoke about writing as a form of healing. Another said simply:
"I like miracles."
There is a great deal of fear surrounding AI and the future of work, much of it justified. Jobs are changing. Some will disappear. Career paths that once seemed reliable are becoming less stable. Entry-level work, in particular, is already being transformed—and in some cases eliminated—as AI takes on many of the tasks through which people have traditionally learned a profession.
There is also frequent avoidance of the nuance—whether by declaring that AI will solve everything, pretending that nothing fundamental is changing, or deciding that refusing to engage with it at all is an adequate response.
Our conversation resisted those sweeping positions. Instead, it moved toward harder questions: What kinds of human capacities will matter most in a changing world? What is education actually for? How do we prepare young people not only to enter a workforce, but to think critically, exercise judgment, and find purpose in their work and lives?
As the evening unfolded, the conversation became less about predicting which jobs will survive and more about what kind of society we might choose to build amid significant technological change.
Someone asked: What would education focused on care look like? How do we teach care rather than competition?
That question pushed our conversation about career pathways in the age of AI into deeper territory: what assumptions are built into the way we prepare young people for work?
For generations, one of the dominant promises of education has been relatively straightforward: do well in school, go to college, earn a degree, and gain access to a stable career and a better life. For many young people, that path now includes substantial debt—and the employment outcome at the other end is increasingly uncertain.
Recent college graduates are already feeling that shift. As of mid-2026, their unemployment rate was about 5.6 percent—well above the rate for workers overall—while roughly four in ten were underemployed, working in jobs that typically do not require a college degree (New York Fed).
As the old bargain becomes less reliable, the question is bigger than how we make young people more competitive. What is the promise of education now? And beneath that are even more fundamental questions: what kind of future are we trying to build, and what will people need to know, understand, and be able to do to shape it?
Are we bound to economic structures that measure education primarily by its usefulness to the workforce? Must school exist mainly to produce workers who can meet the demands of the existing economy?
Or might education help people become creators rather than consumers—and participants in building something different?
AI gives these questions new urgency—and a new opportunity to answer them differently.
When memorization, formulaic writing, information retrieval, and many routine tasks can increasingly be handled by machines, some familiar educational practices begin to look less like preparation and more like habit. We have to ask more seriously what kinds of learning remain essential when reproducing information is no longer a scarce skill.
One theme that surfaced repeatedly was the value of making real things in the real world—work with consequence beyond a grade or classroom exercise.
If AI creates an opportunity to reconsider what we ask human beings to spend their time doing, perhaps this is part of the invitation: to expand, rather than narrow, our understanding of what counts as valuable work and valuable learning.
Can we teach people to use powerful new tools without training them to surrender their judgment to those tools?
That question exposes an uncomfortable contradiction. Much of traditional schooling has rewarded compliance, correct answers, and acceptance of information presented by authority. Discernment, questioning, weighing multiple perspectives, and examining how knowledge is produced have often been less central. We have not consistently taught learners to question authority—and now, suddenly, we are asking young people not to accept whatever an authoritative-seeming machine tells them at face value.
But that requires habits we have not yet cultivated deeply enough, and in many cases have actively discouraged.
There is something exciting in that challenge. AI is creating new problems, certainly. But it is also exposing existing weaknesses on a grand scale—and perhaps, if we choose to respond thoughtfully, creating new urgency and opportunity for meaningful change.
The personal stories from the beginning of the evening echoed that same possibility: disruption can unsettle what seemed certain, but it can also create space for something new.
That does not mean every disruption is a gift. It does mean uncertainty and possibility often arrive together.
The technology may be new, but the capacities we believe young people need most are not.
Collaboration. Agency. Care for our community. Self-care and wellness. Creativity. Critical thinking. Personal responsibility. The ability to communicate across difference. Conflict resolution. Imagination. Vision.
We value these competencies as much as we value traditionally academic ones. Demonstrating them is a graduation requirement at LightHouse, weighted equally alongside academic coursework.
These are not "soft skills." They are increasingly central to the future of work and the future of learning. And they are not developed through passive compliance.
We build this through relationship. Every student has a dedicated advisor, and together they develop a sense of vision—a map for the student's own life—rather than simply moving through a predetermined sequence of courses. Our students are known well. They are trusted with real responsibility. They work with others, make decisions, create things that matter beyond a grade, and learn to connect what they are doing now with the person they are becoming and the life they want to build.
We are not interested in training students to compete with machines at tasks machines can do faster. Nor is our goal simply to prepare young people for the future of work. Since 2015, LightHouse has been creating the space for young people to develop agency, imagination, and a sense of direction for their own lives—and to see themselves as people who can help shape what comes next rather than simply adapt to or accept what is handed to them.
AI makes that work feel more urgent, not because the answers are suddenly clear, but because so many old assumptions are becoming less reliable. This moment asks us to think more carefully about what we value, what we are willing to let go of, and what kind of future we want to build together. What once sounded idealistic is turning out to be the most practical preparation for what comes next.
We'll keep setting the table. Come pull up a chair.