Month: March 2025

As a person with a non-linear career, I never thought I would be one to provide career advice. But as we enter an era in which thousands of people who thought their jobs were secure are suddenly finding themselves unemployed and not knowing what to do, I am realizing I have actually been training my whole life for this. I’ve probably spent less than 20% of my career in a full-time W-2 job with benefits. There has never been a time where both adults in my household had that kind of job security. We’ve learned how to build our own businesses, survive outside of traditional systems by building strong relationships, and we’ve made it work. 

Here are some steps I recommend to anyone struggling with being unemployed, underemployed, or scared for their own work future right now.

Acknowledge any internalized shame 

You don’t need to be ashamed for being born without a giant trust fund that can inoculate you from the whims of an unforgiving labor market, or for being unable to predict the intricacies of said labor market decades into the future. Our culture loves to blame individuals, but you have not done anything wrong.

You may find yourself in a situation where you need to take on work that you feel is beneath your stature or pay grade. It happens! You may need to rely on your family, on your community, or on your government. None of these things are wrong or bad or shameful. It’s called living in a society. Welcome!

It’s difficult to fully rid ourselves of this kind of deeply ingrained capitalist shame, but the first step is acknowledging it.

Determine your income needs

Figure out how long you can survive without income, and the lowest income you need to survive. This is an essential part of thriving in a time of uncertainty. How much money do you have? How much do you need? This is NOT an exercise of forced deprivation—it’s a realistic look at what you actually need, what you already have, and how long you can use it without requiring additional income. You may need less than you think.

Find your community

Find your community and make a list of all the resources available to you. I don’t mean a “network” of people you met at conferences who can toss you a referral link. I mean people who really, truly, deeply care about you and want you to succeed. 

• What can they do to support you right now? 
• What can you do to support them? 
• What resources do you and they have access to? 
• What can you borrow, trade, or barter? 
• Can they get you work—even in a totally different industry or capacity?
• Can you find a way to get on their insurance plan? 
• Does someone have a garden with an abundance of tomatoes, an empty vacation home, a dusty legal degree, free time for babysitting, or an HBO passcode to share? Get creative!

The goal here is not to turn relationships into transactions. This is to identify your own personal net, who is in it and how you can help each other in a topsy-turvy time. You don’t have to do everything alone.

Examine your values and priorities

Identify your top values, and consider how you live those values. 

• Do you need to work in an industry that aligns with your values? 
• Can you work for a company that is morally neutral in a very transactional way and put up very strong boundaries between work and life? 
• Can you work for a lot less money at something you deeply care about? 
• What will certain types of work do for your mental health? What are the acceptable trade-offs?

Consider alternative career paths and models 

We’re experiencing a huge disruption in careers we thought were stable. Some careers are less vulnerable to disruption—some manual trades, jobs that still rely on physical interactions and human touch, etc. But we can’t predict the future, so we need to be creative in how we think about work. 

Maybe this means retraining or thinking about how your skills could apply in a different industry. Maybe it means being creative about consulting, working part-time, starting your own business, sharing a full-time job, creating a new union, or redefining work itself. 

What we do know is it means being flexible and not seeing any job as permanent. Chances are, you’ll have to be ready to change more than once.

Set yourself up as a consultant

It’s okay if you don’t want to be a consultant! Most people would prefer a full-time job with benefits! But even if that’s true, all of us need to be able to sell ourselves as individual contractors when full-time work is not available (and often when it is!). This means:

• Setting up your business basics.
• Learning about how to file quarterly taxes and relevant deductions.
• Knowing how to navigate your state’s health insurance marketplace. 
• Knowing how to buy other services like life insurance on the open market.
• Determining how to identify and price your services.
• Setting up the bare minimum of a basic website so you have it ready for when you need it.

Fight for better working conditions and a social safety net. 

We need new laws and systems that recognize the reality we are in right now, not the reality of 50 years ago. 

Untangling health care from employment is a great first step. Most of us can agree that your ability to see a doctor should not be dependent on what kind of job you have.

Workplaces should have protections for workers, and we should have enough of a social safety net that very sick people do not have to continue to work for specific employers just to stay alive. 

This really shouldn’t be controversial. When you find yourself unceremoniously thrust out of a job that you rely on for basic needs like healthcare, it becomes clearer that a system that relies on the whims of employers is not in service to the vast majority of people.

Want to get some deeper perspective on work that might unfold in our current era? Let’s connect, chat, barter, trade—and expand our personal nets together.

At a previous gig, the hype around generative AI was at fever pitch, and every product manager, engineer, and executive was throwing “AI” at anything and everything. There were good ideas — great ideas, in fact — but so many of them were, well, short-sighted. One example I ran into:

Say that as an account executive, you want to take over a project or account from a subordinate who has less experience with high risk projects. Everything is in a project management system which serves as the source of truth.

In a normal situation you might:

• Go into the system and assign the project to yourself.
• Reach out to the subordinate to say hey, I’m taking over this project, sorry, it’s just way above your paygrade now. (Alternatively, you put the message in the status update so they can see it.)

The system would then generate some sort of notification (sent by email, Teams, or otherwise) confirming to the two of you the transfer of ownership.

The AI-infused flow proposed by the product leaders went something like this:

• Go into the system and assign the project to yourself.
• An AI chatbot would help you compose the email message so your voice and tone is right.
• You then copy the resulting AI-generated blurb into your outgoing email to the subordinate.

There are two obvious problems here: 

1. You’re making the manager do the work of creating and sending the email
2. Isn’t this what notifications are for in the first place?

Is this solving the problem between the manager and subordinate? What problem are we even solving here? No problem. This is a facile solution in search of a problem.

In 2025, so many of the AI solutions we’re seeing in the market are essentially the sort of “bolted on” solutions we see with the magic email generator. They’re solutions that use AI. But are they solving a real problem? And if they are, is it solving the problem better than what’s already incumbent? More elegantly?

The AI boosters would tell us, this is all part of early iterations! We need to try every little idea! The kinks will get worked out! Don’t question, just bolt it on! Be cutting edge!

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When the Kindles first came out, I bought one. I wanted to embrace the future. And yes, maybe look cool.

As someone who wrenched his back in school from carrying too many books in my pack, a simple, electronic device that could store hundreds of books was a godsend. 

One day I stopped into Starbucks on my way to the book club. Somehow, I fumbled my Kindle while I was standing in line. To the concrete floor it went. Those first generation models were made with fragile glass and couldn’t take being dropped on concrete. Device ruined.

Now, my book club had taken note of me waving around this Kindle, with some derision (though they liked that I could mark up passages and refer to them without covering the thing in highlighter ink). In the middle of said meeting, one of the attendees said to me, in front of everyone, “I now know how my paper book is better than your Kindle.” He proceeded to drop his book on the floor. And yes, the book was just fine.

Sometimes the cutting edge cuts you.

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I’ve compared the current fervor around AI to sun-dried tomatoes. In the 1990s, they were in everything. Salads. Salad dressing. Pizza. Tapas. If you could put a sun-dried tomato in it, it went in. By the end of the 1990s, though, sun-dried tomato fervor was dying out. Nowadays seeing a sun-dried tomato as an ingredient on a restaurant menu is a rare curiosity.

Gartner describes this sort of rise and fall as the “hype cycle.” 

• Something emerges as a new, cool thing. 
• The people, and the money, flow into making the new, cool thing work everywhere, until it’s being added into every product despite a lack of consideration of whether it even belongs there. (Looking at you, Microsoft and your “It’s not Clippy” AI features that are as annoying as Clippy was.) 
• At some point, we hit the realistic limits of what the new, cool thing can do, whether it’s ethical or moral or technical or monetary. The hype fades — something Gartner dubs the “trough of disillusionment.” 
• The money flows out, the bubble pops, and the hype moves elsewhere. 
• Eventually, as people figure out what the formerly new, cool thing does well, the real solutions emerge, driving the idea into the mainstream. Or, sometimes, they don’t and fade away (Web3, for example).

We know the AI bubble will pop. People will get disillusioned with AI, particularly when it isn’t solving their real problems. The hype will wear off, the money will move on to the next frothy thing, and everyone pushing hard for AI right now will be Mariah Carey going “I don’t know her” to any question about LLMs or agentic AI.

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So what comes after the disillusionment?

The 2000-01 Dotcom Bust was an extinction-level event for web startups. Amazon barely hung on, and they were among the lucky survivors. By 2005, though, we were talking about Web 2.0, full of its design gimmicks (wet floors!) and pushing Javascript to its limit (AJAX!) The money came back.

What happened? Some people didn’t give up on the idea of the web, the browser, and what it could deliver that was fundamentally different from selling software on CD-ROMs. YouTube, Uber, Flickr, and many others were founded after everything fell apart in 2001.

Remember when Alexa was all the rage? Voice assistants were supposed to solve all our problems! Amazon loaded up on voice designers, but they struggled to make it a going financial concern for the company, and eventually they started laying those designers off.

We still have Alexa and other voice assistants. They’re not trying to solve All The Problems with bolt-on solutions anymore; they have found their purpose in the use cases they’re best used for. If I need to set a timer while elbow deep in making dinner, Siri can do that. If I need a quick thought recorded before I forget to write it down, the Alexa will hold onto it.

Sometimes the idea gets written off, only to re-emerge when a problem it’s perfect for solving becomes evident. QR codes were all but dead in the US (despite uptake in Asia) until the COVID pandemic made touchless, online restaurant menus a necessity.

Once the hype wears off, new tech ideas find what they are truly useful for.

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After the AI bust, what will we see? It won’t be a screen to help you write an email when sending an automatic notification makes more sense. Nor will it be the second coming of Clippy in MS Word or Google.

What we will see are products that find the right balance between augmentation and replacement of humans. Much of the focus during the bubble has been on replacing people with bots. The replacement has gone, well, terribly. Between the slop content it produces and the constant inaccuracies and hallucinations, AI comes across as an eager, obsequious intern you shouldn’t let out of your sight.

What could you use an eager intern for? Or more, what could you use a pattern-matching, predictive language model for to augment instead of replace?

Let’s return to that sales organization where the boss is taking over the account from a junior salesperson. Imagine if:

• You could identify the accounts where the executives might need to get involved and flag them in advance for the account executive to watch
• You could suggest to the salesperson how to better manage such an account using known and tested best practices
• You could identify the customers that need “high touch” vs the ones where quarterly check-ins may be enough to keep them happy, so you can focus your energy where the escalations may lie
• You could help prioritize the accounts that will most help the business — and most help the salesperson obtain the best possible commission payouts
• You could compile the salesperson’s notes along with others from history to help understand the players, their concerns, and possible pitfalls along with potential areas to probe for upselling — in a way where anyone could step in and learn the needed info quickly

If the system could tell you farther in advance when and where the boss may need to step in, or help the salesperson solve their problems without involving the boss directly, then perhaps they would never need to take the account away using an AI bot to help them write that email. They’d never send that email, in fact. The process and the people have been augmented by a system that gives them control over the situation and helps everyone avoid surprises.

Out beyond the hype and the bolt-on solutions we’re already seeing what generative AI and large language models can do — spotting tumors in MRIs that a technician may miss, for example. That space out there, where innovation, augmentation, and solving real problems lies, is where the product design world, the UX community, needs to be focusing right now. The bubble’s going to burst. Money will race away from current AI solutions while the financial and technical dead ends continue to pile up. Something newer and cooler will lure the VC money away. And like a meteor wiping out the megafauna, the ones who are small, nimble, and different will have the opportunity in the ruins to evolve into the new megafauna.

It is essential design is out there in that space because being farsighted is something product designers are exceptionally good at. Every innovation lab, every design thinking workshop, every argument over product roadmaps and user pain points is about designers thinking beyond the right now. There’s a good reason designers are often seen as Cassandras in organizations — we spot the problems with facile solutions and get in fights over how anti-user, anti-business, anti-human those facile solutions are in the long term.

Design needs to stop hoping and waiting for the AI bubble to pop. It needs to start worrying about what happens once the bubble pops. UX has immense potential to, if not own, influence the narrative around AI, machine learning, and large language models.

Up until now, delivering the pixels has been a core part of a design’s job. That narrative is starting to change. When AI-based site generators like Replit can spit out an OK website for product folks to walk around and engineers to build on, the pixels will matter less and less. Design’s skills at understanding the problem and the user needs will matter more and more.

Being a designer isn’t, and shouldn’t be, about the pixels. It’s always been about the user experience perspective we bring to the table that others do not have — or don’t have enough time to focus on. We have an entire user research practitioner community to look to. Some of us have service design in our arsenals. More than a few of us have picked up product management skills.

The future of UX is in being farsighted, being small, being nimble, and making it through the extinction level events that hit our industry. We can own the future, so long as we are willing to look beyond the present.