When “AI Employees” Call Humans The Constraint: Why Podium’s Jerry 2.0 Feels So Gross

There is a very specific kind of nausea that hits when you read a post like this:

“The biggest constraint isn’t software. It’s people. Labor is expensive and inconsistent.”

On its own, it is just one more founder bragging about a new AI product. Put it in the context of the last decade of AI talk, though, and something curdles.

For years, leaders told workers a comforting story. AI would “augment” us. Help us do our jobs better. Take the boring tasks so humans could “focus on what matters.”

Then along comes Podium’s Jerry 2.0, an “AI employee” launched with a proud announcement that people are the problem, and the solution is… fewer of them.

You can feel the mask slip.

This is not just another tool. It is a reveal of what a certain corner of tech really believes about labor, dignity and who is disposable.

Let’s talk about why it feels so scummy.

1. The friendly AI “employee” that never needs a raise

The launch copy calls Jerry “our AI employee,” trained to capture leads, book jobs, close sales and handle complex customer scenarios. It is available 24/7, never takes a break, never gets sick, never pushes back.

In other words, it is not an employee at all. It is software that lets you scale customer contact without scaling payroll, benefits or protections.

Calling it an “employee” is not cute. It is misdirection.

• Employees have rights.

• Employees have workplace protections, legal recourse, and a say, however small, in the conditions around them.

• Employees can quit.

Jerry cannot. Jerry does not need healthcare, paid leave or boundaries. Jerry lives to convert.

Framing that as a “new teammate” is like calling a self checkout kiosk “the new cashier.” The word is doing PR work. It makes the decision to replace people feel like innovation rather than a choice to remove the human layer.

The subtext is simple: the closer your job is to Jerry, the more negotiable your existence becomes.

2. “Labor is the constraint” is not a neutral sentence

When a founder writes:

“The biggest constraint isn’t software. It’s people. Labor is expensive and inconsistent.”

you are not reading a quirky observation. You are reading the business case for treating humans as a bug to be fixed.

Of course people are inconsistent. They have lives. Bodies. Moods. Commutes. Sick kids. Grief. Joy. Burnout. Religion. Queerness. Bias. Empathy. All the messy inputs that make us human and, paradoxically, make us good at hard conversations.

Automation has always promised relief from drudgery. That is the hopeful version. But there is another motivation that rarely gets said out loud in the launch party:

Humans are expensive because they have to live.

When “labor is the constraint,” what some leaders really mean is “workers’ basic needs are inconvenient to my margin.” Underneath the slick interface and the AI Studio dashboard, that is what Jerry is optimizing around.

In that light, this kind of announcement reads less like “future of work” and more like “we finally found a way to avoid hiring your next coworker.”

3. Industrializing yesterday’s bias with tomorrow’s marketing

According to the marketing, Jerry is trained on 10 plus years of industry conversations and tuned for conversion. That sounds impressive until you ask one simple question:

What if those 10 years were biased?

If the historical conversations tilted toward certain kinds of customers, certain names, certain zip codes, certain accents, Jerry will learn that pattern too. If old scripts gave faster follow up to “good” neighborhoods and slower, colder responses to everyone else, Jerry will happily scale that inequity at the speed of silicon.

That is what optimization does. It takes whatever pattern you feed it and sharpens it.

The launch post is full of promises about revenue uplift and industry expertise. What is missing is any clear signal that this team has even asked:

• How does this thing behave for people on the margins?

• Do different demographics get different treatment?

• Are there guardrails to stop it from replicating old harm?

If your AI is trained largely to “convert,” and you never audit who gets converted and who gets quietly shooed away, you are not innovating. You are industrializing yesterday’s prejudice and calling it progress.

Slap a friendly name on it, call it Jerry, and suddenly the bias has a face and a mission statement.

4. The gaslight of “enhance, not replace”

The part that stings is not just what Jerry is built to do. It is the contrast with what many AI leaders have been saying in public for years.

We have heard the talking points on repeat:

• AI will enhance workers, not replace them.

• AI will free people up to do more meaningful work.

• AI will create more jobs than it destroys.

Sometimes that is true. New roles appear. New skills are needed. Some people will move into them and thrive.

But when a company launches an AI “employee” and markets it as a way to handle more leads, close more deals and manage more conversations without calling it what it is — headcount avoidance — workers are not confused. They are being asked to ignore what is right in front of them.

You cannot proudly announce that “labor is expensive and inconsistent” and then act shocked when people hear “you are next in line.”

You cannot celebrate a tool that handles the bulk of frontline customer work and then insist that this is all about “empowerment.” Empowerment for whom, exactly?

When the value proposition is “grow revenue without hiring more humans,” this is not augmentation. It is substitution wrapped in soft language.

5. The missing word is dignity

There is also a quieter loss hidden under all the conversion metrics: dignity.

Customer facing work, especially in small and local businesses, is often where people first learn:

• How to de escalate a situation

• How to read tone in a text or voice

• How to care for a stranger in a difficult moment

• How to represent a brand with their own personality

It is where a lot of queer kids and immigrants pay rent while they figure out their next move. It is where people with non traditional resumes can still build skills, relationships and reputations.

When you decide that all of that human nuance is “inconsistent labor” and you rush to replace it with a scripted AI, you are not just shaving costs. You are saying that this layer of human contact is interchangeable, generic, disposable.

Yes, some tasks are boring. Yes, automation can be a relief. But there is a line between building tools that support people and building systems that erase them.

Dignity lives in that line.

6. This is not about one company

To be clear, Podium is not unique. It is a very visible example of a broader pattern.

• Give the AI a cute name.

• Call it a coworker.

• Position it as “always on” and “never misses an opportunity.”

• Describe people as the constraint.

• Avoid any real talk about bias, displacement or the long term social cost.

By the time workers notice what has shifted, the decisions will already be baked into subscription agreements and board decks.

That is why this launch feels so gross. It is not just about Jerry. It is about a tech culture that wants applause for efficiency while outsourcing the fallout to everyone else.

7. What an honest version would sound like

Imagine the same product described with even a fraction of honesty:

We built an AI system that can take over a lot of front line customer messaging. It will let some businesses grow without hiring as many people. That is the financial upside.

We also know this creates real risk for workers and for customers who are already treated as less valuable. We are publishing how we test for bias and what we are doing when we find it. We are transparent about where humans are removed from the loop. We invite scrutiny and regulation because we plan to be here long after the first bump in revenue.

That is not perfect, but at least it treats the public like adults who can handle tradeoffs.

Instead we get the saccharine version: AI as the perfect employee, labor as the problem, and silence on who is protected when everything goes wrong.

8. Why I refuse to clap

I am not anti AI. I work in this space. I understand the power of good tools. I also understand how much pressure small businesses are under to do more with less.

But I will not pretend it is neutral when founders talk about people as “constraints.” I will not pretend that an AI trained on a decade of unexamined conversations is magically fair. I will not clap for the rebranding of job cuts as “24/7 customer love.”

If you want to build systems that truly enhance humans, start by treating humans as more than a line item you are proud to compress.

Until then, Jerry is not an employee. Jerry is a mirror. And what it reflects about how some leaders see the rest of us is exactly why their launch posts feel so rotten in the first place.

If you want cheaper labor, at least have the courage to say that, instead of dressing it up as 24/7 customer love.