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.
On Wednesday, July 8 we gathered with 18 people for the first Long Table dinner. The topic was AI and Education. Big topic! You’ll be relieved to hear that we hammered out all the answers and solved everything 🙂 Just kidding. I don’t know what that would even mean.
We did not solve all the world’s problems, but for a few hours we created the kind of space that feels increasingly rare: real people in deep conversation about things that matter, sharing and listening with care and respect, open to disagreement, with no expectation that anyone would convince, enlist, or change the mind of anyone else.
The goal wasn’t consensus. It was curiosity. Over a delicious meal and drinks.
LightWorks isn't my home, but hosting the evening feels personal. It's the work my colleagues, our board, and I have spent more than a decade building. Inviting people to gather around our shared table felt a little like inviting people into my living room. There is always a bit of vulnerability in that- are these the right napkins?! Is the water cold enough?! Are they noticing that scratch in the paint?
There is also a great deal of joy in sharing a space we've spent years building for exactly this purpose: to gather, to connect, to learn from one another, and to imagine together what a better future might look like.
If I had to summarize our overall vision in one sentence, it would be this: create places where people learn with each other, from each other, and for each other.
The Long Table is an embodiment of this vision.
One of the things we’re most proud of at LightWorks is our commitment and ability to bring together diverse people. This was again true at this event. Around the table sat people from different professions, generations, nationalities, ethnicities, backgrounds, political viewpoints, and life experiences. The youngest person was 24. The oldest was 90. We had educators, parents, technologists, artists, and community members. Our local diversity—among our greatest strengths—was proudly present in the room.
And despite all those differences, there was remarkable convergence about what matters most.
The evening wasn't a panel or a lecture. Instead, we centered the conversation around two carefully chosen questions and used a two-minute sand timer as a talking piece.
The first question invited people to look inward:
Describe a time when learning felt truly alive.
Unsurprisingly, not a single person spoke about grades or assignments. Many talked about curiosity. About pursuing something because they cared about it.
They talked about the satisfaction of working through struggle. Many described learning as something that became meaningful in part because it was difficult.
Several people shared about someone who believed in them: a teacher, a coach, a mentor, a parent. Someone who helped them keep going when they might otherwise have given up.
A few people spoke about beauty, which seemed to really resonate with the group—the experience of being drawn toward something simply because it felt beautiful or meaningful enough to pursue.
Listening to those stories, the contrast with so much of our current conversation about AI was significant.
Much of the current public conversation about artificial intelligence is driven by fear. Some of that fear is manufactured by algorithms that reward outrage. Some of it is entirely justified. AI represents an extraordinary disruption.
But disruptions also create opportunities to ask better questions.
As machines become increasingly capable of memorization, compliance, information retrieval, and routine production, perhaps school no longer needs to organize itself around those abilities. Perhaps this disruption requires us to spend more time cultivating the capacities that make us human.
Our second conversation turned toward that future.
As AI changes what is easy to look up, generate, or outsource, what could education become if we used this moment well? What would you most want to see protected, strengthened, or reclaimed?
The answers echoed what had already emerged around the table: empathy, communication, collaboration, leadership, creativity, judgment, confidence, and the ability to imagine something that doesn't yet exist—and then bring it into being.
People spoke about their fears, but also the importance of AI fluency: helping young people understand these tools, think critically about them, use them wisely, and remain their authors rather than becoming their products.
One of my favorite moments came near the end of the evening when someone observed that meaningful social change has rarely begun with sweeping declarations. More often, it begins around tables like this one—in homes, cafés, community centers, and gathering places where ordinary people wrestle with difficult questions together.
The feedback we've received since the dinner has reinforced that feeling.
Again and again, people wrote about how refreshing it felt simply to have a thoughtful conversation with people they might not otherwise meet. They appreciated the diversity of perspectives. They appreciated the structure that gave everyone a voice. And many commented on how isolating our algorithm-shaped lives have become—and how different it feels to think together with actual human beings.
We don't need to agree about everything.
We do need places where we can practice curiosity and deepen our understanding through unfamiliar perspectives.
For one evening, the room became a small reflection of the world we hope to build: curious, generous, diverse, thoughtful, willing to consider difficult questions together. That feels like something worth building.
The Long Table continues every other Wednesday this summer before moving to a monthly gathering this fall. If you have a question you'd love to explore—or someone you think should be around the table—we would love to hear from you.