Easy AI Help Goes a Long Way

AI Help Goes a Long Way

13:19

A few nights ago, around 1:00 in the morning, I was lying in bed scrolling LinkedIn when I came across a post from someone looking for work.

It was one of those posts you see more and more lately.

An experienced professional. Clearly capable. Clearly having a rough time. They had been looking for work for a while, were struggling financially, and were doing the thing nobody particularly enjoys doing in public: asking for help. Not asking for a handout.

Asking if somebody knew somebody...Asking if somebody could open a door. And if you spend enough time on LinkedIn right now, you have probably seen some version of this.

People with 15, 20, 25 years of experience saying they have applied everywhere, they are not getting interviews, they are open to anything, they are trying one more time to see if somebody in their network can help.

There is something especially painful about watching that happen to someone who has obviously spent decades becoming useful. Because very often, the actual person and the version of that person reaching the market are nowhere near the same thing.

The Human Was Better Than the Profile

I looked at this person's background for a few minutes. And almost immediately I thought: this person is punching way below their weight class.

The LinkedIn post sounded like somebody asking the market to please give them a chance. Their actual experience told a completely different story.

This was someone with years of technical and operational knowledge, quality experience, customer-facing experience, problem solving, and the kind of accumulated judgment companies usually appreciate after they no longer have it. The problem wasn't an absence of capability. The market just wasn't seeing it very well. And that's becoming a bigger problem because increasingly, there's machinery sitting between the person looking for work and the person who might hire them.

• Applicant tracking systems.

• Keyword filters.

• Automated screening.

• AI-assisted recruiting.

• Degree requirements.

• Résumé parsers.

• Job-title taxonomies.

All kinds of things that are supposed to make hiring more efficient. And sometimes they simply do a lousy job of understanding the human on the other side.

So I Tried Something

I took the publicly available information, handed it to my AI system, and essentially said: fix the signal. That was pretty much the production meeting.

• I was still in bed.

• No Photoshop.

• No coding session.

• No project plan.

• No kickoff call.

• No two-hour exercise in writing website copy.

I had already done the part I needed to do. I had looked at the situation and decided the representation was wrong. The AI system took it from there.

It analyzed the experience, reorganized the professional story, built a public-facing site around the person's actual capabilities, and published it. Now there was something people could actually send somewhere. Not: here's somebody who desperately needs a job.

More like: here's an experienced professional. Take a look at what this person has actually done.

I dropped the link under the original LinkedIn post and wrote a short comment saying, essentially, this person isn't fully selling themselves here. If you know someone hiring in the relevant areas, take a look and pass it along. Then I went to sleep.

101,000 Impressions Later

That comment has now been seen more than 101,000 times.

And somewhere in there, this stopped being a neat little AI trick. The website itself isn't the interesting part. We know AI can build websites.

What got my attention was how little distance there suddenly was between: somebody should probably help this person, and something was actually done.

A few years ago, helping someone that way could have turned into a legitimate project.

You would have needed to research the person, figure out their positioning, write everything, design something, build it, host it, publish it, and then figure out how to get it in front of people. That's enough friction to kill a lot of good intentions.

Most people aren't heartless. They're busy.

You see somebody struggling. You feel bad. You click Like. Maybe you leave an encouraging comment. Then life moves on. That's normal.

The thing that changed here wasn't empathy. It was the cost of acting on it.

All I Had to Do Was Human

This is the part that stuck with me.

AI did a huge amount of the production work. But it didn't notice the person.

It didn't have the reaction I had when I looked at the background. It didn't think, this is stupid, the market is seeing the wrong person. It didn't care whether another LinkedIn post disappeared into the feed. That part was mine.

I noticed something....I cared enough to look closer...I made a judgment...Then I handed off the mechanical work.

That's a very different way of thinking about AI than the one most people are currently being sold. Most of the conversation is about productivity.

Write faster.

Research faster.

Code faster.

Make presentations faster.

Produce more content.

Send more emails.

Do more work.

All useful.

But I think there's another possibility buried underneath all of that. AI may let us spend less of our lives behaving like machinery. And if it does, maybe we can spend some of what we get back on other people. In this case, that was basically what happened.

All I had to do was human.

This Is Bigger Than One Person

The individual story happened to catch attention. But the underlying problem is everywhere.

There are a lot of capable people being represented by lousy proxies for capability.

A résumé is a proxy.

A job title is a proxy.

A degree is a proxy.

An employment gap is a proxy.

A LinkedIn profile is a proxy.

None of them are the person.

Someone can spend 25 years learning an industry and still lose to a screening system because their experience doesn't map neatly to a title. A person can be terrific at their job and terrible at selling themselves. They can have deep operational knowledge and no idea how to communicate it online.

They can be unemployed long enough that the way they talk about themselves starts shrinking. You can actually watch that happen in some of these LinkedIn posts. The person begins by looking for the next appropriate role.

Months later, they're asking for anything. Their capability didn't suddenly evaporate. Their signal got weaker. And then the market starts responding to the weaker signal.

That's wasted human capability.

Capability Recovery

I've started thinking about the problem as capability recovery. There are people walking around with far more value than the market can currently see. The job is to surface it.

That could involve improving someone's professional presentation. It could reveal a consulting opportunity they had never considered. Maybe the thing they know how to do for an employer could become a service, a product, a training program, or a piece of software. Or maybe the answer really is another job, but they need a much better way of showing why they belong in it.

AI is useful here because exploring those possibilities no longer has to become a massive undertaking.

You can test an idea.

Build the first version.

Research the market.

Create the asset.

See whether anything is there.

The price of finding out has collapsed. That matters a lot if you're 52 or 62 and staring at the possibility of starting over.

The Network Already Exists

There was another thing about this story that kept bothering me. The original post attracted more than a thousand reactions.

That's a lot of people saying: I see you.

And there's real value in that.

But I kept thinking about what would happen if only 10 percent of those people turned the reaction into some tiny action.

That's roughly 100 actions.

A hiring manager sees the profile because somebody forwarded it. A former coworker makes a phone call. A recruiter takes another look. A business owner realizes they actually need somebody with that background. A friend makes an introduction. Maybe somebody else notices a flaw in the résumé and fixes it.

You don't need a new LinkedIn feature for this. The network is already sitting there.

The useful question is whether the network only reacts, or whether occasionally it moves.

That's the part I want to play with.

AI Makes Small Acts Bigger

A lot of the AI conversation immediately goes enormous.

• AGI.

• Mass unemployment.

• Trillion-dollar companies.

• Autonomous agents.

• Robots.

• Civilization.

Fine.

I'm interested in those things too. But this little episode has me paying more attention to something much smaller.

A person notices another person having a problem. The problem is solvable.

Historically, helping might have required enough time, money, or specialized skill that nothing happened. Now the person noticing the problem has access to an absurd amount of computational leverage. That changes what a small act can look like.

No committee...No organization...No grant...No meeting...No permission.

Just: I think I can make this a little better. And then you do. That's interesting to me.

Especially for People My Age

I turned 52 this week.

And one of the reasons I'm starting to talk more specifically to the 50-plus crowd about AI is because I keep seeing experienced people act as though everything they spent their lives learning somehow expired. I don't believe that.

In fact, I think AI may make a lot of that experience more useful.

If producing the work gets easier, knowing what work is worth producing becomes more important. If information becomes cheap, judgment matters more. If anyone can generate ten answers, knowing which answer smells wrong matters more. If a person can suddenly build something without knowing every technical step, then knowing what should be built becomes a hell of an asset. Those are things people accumulate through reps. And people over 50 have reps. Lots of them.

They've watched projects fail.

They've hired the wrong person.

They've trusted the wrong vendor.

They've made money.

They've lost money.

They've dealt with customers.

They've survived things.

They know things they no longer even think of as knowledge because the knowledge became instinct years ago. I think there's a goldmine sitting there.

The problem is that a lot of people don't yet understand how to connect what they know with what these systems can now do. I'm interested in figuring that out with them.

So I Am Going to Run an Experiment

Starting now, I'm going to give one person 15 minutes every weekday. They'll come to me with whatever is actually going on.

Maybe they lost a job.

Maybe they've spent 30 years in an industry and have no idea what to do next.

Maybe there's a business idea buried in something they know.

Maybe they're running a company and wasting half their life on work AI could absorb.

Maybe they simply know they need to get involved with this stuff and have no idea where to begin.

We'll talk. I'm not promising to rebuild anybody's life in 15 minutes. I'm promising to pay attention. Then I'll use the tools I have and see whether there's something useful I can give back.

I honestly don't know what the output will be from one person to the next. That's part of why I want to do it.

One conversation might result in a page or a report. Another might expose a business idea. Somebody else may need a completely different way of thinking about their career.

And occasionally, the best thing I can give somebody may simply be clarity about the next move.

With their permission, I'll also write about what we learn. Not as testimonials. As case studies.

Real people entering this strange transition from the old operating environment into the new one, one at a time. Over time, I suspect the lessons will start stacking.

The next person will get the benefit of everyone who came before them. That's how I want the classroom to work.

Keep the Human Part

The thing I want to be careful about is turning vulnerable people into material. Somebody publicly admitting they're struggling deserves some grace. Especially when the struggle involves work, money, health, family, or the uncomfortable realization that the professional identity they carried for 25 years may not be opening doors anymore.

Technology should make it easier to meet that with humanity. Not harder. And maybe that's the larger point.

We've spent years asking what AI can do for us. Maybe another worthwhile question is: what can we do for somebody else now that AI has made it easier?

You don't need to solve homelessness...You don't need to start a nonprofit...You don't need to make a grand gesture. There's probably something you know how to do that takes you almost no effort and would mean a great deal to somebody who doesn't know how to do it. Use it once in a while.

AI can take care of a surprising amount of the machinery. Which leaves us with the part that was ours all along.

Human.

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Rich Washburn is a technologist, strategist, and Founder & Chief AI Architect of ARIA AI Labs, working at the intersection of AI, infrastructure, communications, and capital. He also serves as Managing Partner and Chief AI Officer at Eliakim Capital.