The In-Between

For most of modern history, work has been the primary container for human meaning.

Not just income. Meaning. The structure that tells you what day it is, who you are, what you’re contributing, and what tribe you align with. You meet people through work. You measure time through work. You answer the question what do you do — which is really the question who are you — through work. After 15+ years in the workplace, I lost sight of the connection between meaning and income. I woke up one day, and I had a lot of stuff, and I was a VP of Design and the bridge between what I did and who I was felt both disconnected and intertwined.

The more I talk to other tech leaders, founders and friends the more clear to me it is that meaning has become something you squeeze in when you’re not working or it is work. Perhaps for some this makes sense but I lost the trail markers. The conversation about why this happened and how it’s accelerating isn’t taking place at the everyday human level. We’ve somehow accepted the trope of “that’s just progress,” “everything evolves,” “get on board or get left behind.” But what are we getting on board for? And what are we leaving behind?

What happens to humans when the thing that organized their lives, their identity, and their sense of contribution is restructured faster than they can adapt? That’s not a future question. It’s a present one. And almost nobody is taking it seriously. The future of work conversation has a thousand participants. It’s global. It’s remote. It’s AI First. The future of humans conversation — the one about meaning, purpose, identity, and what people are actually going through right now — is nearly empty.

Where we are

The in-between is not a waiting room. It’s where millions of people are making consequential decisions about their careers, their skills, and their lives with almost no reliable guidance and a great deal of noise. It’s where organizations don’t know how to staff for a future they can’t see. It’s where the distance between what leaders say and what employees experience has never been wider. And it’s where the question that matters most — what are humans for, if not for this — is going completely unanswered.

Right now, that’s where many of us are. We are in the in-between.

What we’re actually being promised

Elon Musk says work will soon be optional. Sam Altman says AI will completely transform work within a decade. The World Economic Forum says 86% of businesses will be affected by AI and automation by 2030. UK government ministers are floating universal basic income as a soft landing for the industries that won’t survive. These are predictions about work. None of them are predictions about humans. None of them are about meaning.

The meaning was never in the job title. It was never in the org chart. You brought it there. Which means you can build it somewhere that doesn’t depend on a quarterly workforce planning cycle to survive.

Musk gets closest when he asks, briefly, before pivoting back to the economics, whether life has meaning if computers and robots can do everything better than humans. It’s the right question. He doesn’t stay with it, because the abundance story is more sellable than the meaning problem is solvable. But the question doesn’t go away just because the answer is inconvenient.

These aren’t fringe predictions. They’re coming from the people building the systems, and they’re being taken seriously at the government level. And somewhere between those models and your inbox on Monday morning is the actual experience of work in 2026, which looks almost nothing like any of the scenarios being planned for.

What’s happening right now, while we wait for the future

Google restructured its ad sales division in early 2026 after employees spent months training an AI system called Gemini for Sales on their own client relationship workflows. Former employees described it to Business Insider as building your own coffin. The knowledge that took careers to accumulate — extracted, encoded, and then used to justify the headcount reduction.

Meta announced it would cut up to 16,000 jobs while simultaneously planning to spend $135 billion on AI infrastructure this year alone. Their chief compliance officer sent an internal memo telling employees their jobs would be eliminated due to advances in automation. Not restructured. Not evolved. Eliminated. Picture 16,000 people — that’s the Charlotte Hornets basketball stadium almost full — everyone unemployed and wondering what’s next. Thousands of mortgages due. Thousands of childcare bills.

Block laid off 40% of its workforce. Amazon eliminated 16,000 corporate roles. Oracle announced 30,000 people let go. So far in 2026, AI has been cited in over 150,000 U.S. tech job cuts — a number still accelerating.

The technology is being built in a specific order: capability first, efficiency second, humans somewhere after that. That order is a problem.

Most of these companies are not cutting workers because AI has proven it can do the work better. They’re cutting jobs based on AI’s projected future capability, and primarily to fund the infrastructure by reducing headcount today, before the productivity gains have materialized. Which means people are losing work, or living with the anxiety of potentially losing it, based on a promise that hasn’t been cashed yet for the business, and one that will never cash for the humans let go.

People worrying about next month’s mortgage are not thinking about Mars or the abundant future. Bills are due today.

The meaning problem nobody wants to sit with

Work isn’t just an economic arrangement. For most people it’s the primary structure around which they organize time, identity, relationships, and a sense of contribution. Loss of work correlates with loss of meaning at levels that track closer to grief than inconvenience. The research on this is not ambiguous.

This is already a present-tense question for anyone whose expertise has been extracted by a system they helped train, or whose function is quietly losing leverage inside an organization reorganizing around a different center of gravity, or who spent fifteen years becoming excellent at something the job market now values differently.

The UBI conversation doesn’t address this. A monthly check solves the economic floor problem. It does nothing for the person who trained an AI system on their own knowledge and then got the memo. Cashing that check doesn’t answer who they are now or how they inspire their children to work hard.

Nobody in the abundance narrative is seriously grappling with what happens to human purpose when the economic justification for expertise is removed faster than the cultural and psychological structures built around it can adapt. It’s showing up in the anxiety statistics, in the trust collapse around AI, in the fact that two thirds of the global workforce doesn’t yet have the skills to work in AI-enabled roles while their organizations are simultaneously cutting the entry-level positions where those skills used to get built.

The system designed to manage this isn’t managing it

HR is the organizational function built to manage humans at work. Right now it’s being asked to run a workforce transformation it wasn’t designed for, and in most cases wasn’t included in designing. Only 21% of HR functions are closely involved in AI strategy decisions at their organizations. 69% of leaders say they’ve communicated clearly about AI. 12% of employees agree. That’s not a communication gap. That’s a structural one.

The result is predictable. Some organizations are running upskilling programs while leaving the actual structure of roles, functions, and career paths unchanged. Tool training is up. Workflow redesign is lagging. The WEF’s diagnosis from Davos this year was direct: the biggest challenge organizations face isn’t a skills gap or an AI gap. It’s a work design gap. Nobody is redesigning work. They’re layering AI onto the existing structure and then cutting the people whose roles have been made redundant by that layering, while calling it transformation.

The hiring paradox

Spend 30 minutes on LinkedIn. You’ll read the stories that are the outcome of wanting to move revenue per employee from 300k to 600k. “15 years of excellent performance reviews. 13 months out of work. I’ve cashed in everything.” “150 jobs applied for — 2 interviews. What am I doing wrong.” Nothing my friend, the system is broken.

Hiring managers are overwhelmed. The matching systems are antiquated and organizations are currently seeking the 99/100 candidate — the near-perfect fit, every box checked, minimal risk. It’s understandable. Uncertainty breeds caution. But it’s exactly backwards for this moment.

The most AI-experienced candidate in any field has at most 18–24 months of real expertise. The models, workflows, and processes are changing week to week. The person who checks 93 out of 100 boxes on a static job description is being pushed to the maybe pile while the search continues for 99 out of 100.

For decades, organizations optimized for people who were excellent at reading maps — following established routes, executing known playbooks, navigating a landscape someone else had already charted. That skill was genuinely valuable. It still is, in stable terrain. But the map is wrong now. The terrain changed faster than the cartographers could keep up. What you need isn’t someone better at reading the old map. You need Magellan — someone willing to sail toward the edge of what’s known, make decisions without a clear route, and bring something back that didn’t exist before they left. Someone who finds the uncertainty clarifying rather than paralyzing, because their sense of direction comes from something internal, not from the lines on the page.

When every team has access to the same tools, the same models, the same platforms, the differentiator isn’t the technology. It’s the perspective the person brings to it. The centered employee doesn’t need the org chart to tell them who they are, so they’re not optimizing for survival inside a structure that may not survive. They’re thinking clearly. They push back when it matters. They have a point of view that didn’t come from the last All-hands.

You can’t certify for that. You can’t upskill toward it. And right now, most hiring processes are structurally designed to filter it out. Organizations are cutting experienced workers to fund AI infrastructure, while simultaneously refusing to hire the adaptive, unconventional talent that the moment actually demands. The hiring system is optimizing for a stability that no longer exists.

What actually needs to exist

The questions are being asked at the wrong level — and in the wrong order. Almost everything being built around AI and work starts with the technology and works backwards to the human. Human first › the thinking that serves them › the AI that amplifies it — that sequence barely exists.

That’s what I’m trying to build toward. What Companies Value is an attempt at the first piece — organizational transparency. Which companies treat people as strategy and which treat them as cost, based on what they actually do, not what they say at the all-hands. Career Decoder is an attempt at the second — individual navigation. Not career advice. Scenario logic for your specific role, at your specific company, in this specific moment. Neither is finished. But the sequence matters: understand the landscape, then navigate it.

We may not have the power right now to change those but we can restructure ourselves for the in-between. Before any external clarity can orient you, before scenario logic can help you decide, before honest signal can tell you what’s real — you have to know enough about yourself to use any of it.

Most people in the in-between don’t. Not because they’re incapable of self-knowledge, but because work has been answering those questions for so long they stopped asking them independently. Work gave you the story: I’m a senior designer, I lead a team, I ship products people use. Work told you what mattered: the deadline, the review, the promotion cycle. Work structured your time so completely that the question of who you are outside of it rarely came up with any urgency.

Cue the urgency

So before the structural clarity, before the navigation tools, before any of it: what is your story, in your own words, without the job title? What actually matters to you — not what you’ve optimized your career around, but what you’d protect if you had to choose? Who are you when you’re not performing competence for an organization? And the one most people find hardest to sit with: are you fulfilled? Not successful. Not busy. Not useful to the quarterly plan. Fulfilled.

If you don’t have answers to those questions, the in-between will rattle you from side to side with every All-hands, every layoff announcement, every AI LinkedIn post. You’ll make decisions based on whoever had the most recent access to your anxiety. You’ll optimize for survival in a structure that most likely will not survive.

The people who move through this well aren’t the ones with the best skills or the most AI certifications. They’re the ones who have a center that isn’t located inside their employer. Not because they care less about work — because they know what, and who, they’d still be if the work went away. That self-knowledge isn’t soft. Right now, in this specific moment, it’s the most practical thing you can build.

What’s your personal me.md file

If you recognized something in this — maybe it was the Google story, maybe the mortgage line, maybe just the feeling of documenting your own workflows and wondering what you’re actually building toward — I’m not going to tell you to update your LinkedIn or take a course. You don’t need more noise.

There’s a harder question underneath that one. And it’s not about your org. Work became the answer to so many things it was never really designed to answer. Who am I. What am I for. Where do I belong. What does my day mean. We handed all of that to our employers, partly because the culture told us to, partly because it was convenient, partly because it worked well enough for long enough that we stopped noticing how much weight we’d put on it.

That was always fragile. AI didn’t create the fragility. It’s just moving fast enough now that we can’t pretend it isn’t there anymore.

The meaning was never in the job title. It was never in the org chart. You brought it there. Which means you can build it somewhere that doesn’t depend on a quarterly workforce planning cycle to survive.

Find the thing that is yours regardless of where you work, what you’re called, or what the market decides your function is worth this quarter. That thing exists. Most people just haven’t had to look for it yet because work was loud enough to cover the silence.

The in-between is uncomfortable. It’s also, if you’re willing to use it that way, the first real opportunity many people have had in years to ask what they actually want. Not what they were trained to want. Not what their LinkedIn says they want. What they actually want. That question is worth something. Don’t waste it waiting for the uncertainty to resolve.

You don’t have to have the answer today. But you do have to start asking. I’m here, with you.

If you want to do that work, secondharvest.co is a good place to start.