AI Agents Like OpenClaw Are Here. How Can You Use Them?

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Hey, what's news listeners?

It's Sunday, March 29th.

I'm Alex Osula for The Wall Street Journal.

This is What's New Sunday,

the show where we tackle the big questions

about the biggest stories in the news

by reaching out to our colleagues across the newsroom

to help explain what's happening in our world.

On today's show,

Agentic AI is the busiest word in tech right now.

AI agents are taking on tasks like tracking customer orders

and making restaurant reservations.

And the next generation promises to be even more powerful,

becoming kind of like a personal assistant.

But AI agents also come with big risks,

even as they may stand to finally help tech companies

make money off artificial intelligence.

Journal tech reporter Isabel Busquet joins me to discuss.

Isabel, when developers or companies refer to an AI agent

or AI assistant, what do they mean?

Like, what is that?

This is a very overhyped, overused term.

And I don't think the industry has a common definition.

But at its base, an agent is an AI

that can do something for you.

It becomes agentic when you say,

make this restaurant reservation for me,

book this doctor's appointment for me,

book this flight for me by this dress for me,

anything where it's going out into the world

and executing some behavior on your behalf.

That's the point at which it becomes an agent.

When companies talk about using AI agents,

how are they using them?

We're seeing two kind of big categories emerge so far.

One is in the coding space.

There are a million companies that offer this

from the cloud code and open AI code acts of the world

to cursor, replicate, loveable.

Everyone has an AI coding agent these days.

Engineers are using this a lot.

The other area we've started to see agents take off is

in customer service.

It kind of grows out of the traditional phone tree technology

that was not really AI enabled at all,

but now it can be of a customer calls with a question

about where the order is,

an AI agent can handle that call

and give status updates or replace a missing loyalty card

or things like that.

How do these tools actually help companies make money?

We know companies are spending a lot of money to use them.

If we take engineering, this is the example

a lot of people use because it's just the most mature use case

by far.

So every time a coder uses an agent,

it costs money.

It costs what they call tokens.

And some companies give their engineers a certain

allotted number of tokens and some companies are more

flexible saying, have as many tokens as you want.

But some companies compare the salary of the engineer

to the amount of tokens they're using.

And they're saying that in a lot of cases,

this person is costing more in tokens

than they are in actual salary.

But on the flip side of that,

they're also looking at the amount of work this person is doing.

And they're saying this person is being like 10 times

or 50 times more productive than they would

if they didn't have a coding agent.

So although they're costing two times an engineer salary,

they're delivering like 10X of what an engineer can do.

So that's how they're weighing their returns at this point.

The kinds of agents we've been talking about

are out there in the world.

But there's something else that's coming, right?

And it's something called OpenClaw.

Yeah, so OpenClaw is the open source orchestration framework.

For it to be a true personal assistant,

you have to give it access to everything,

which is a huge security concern because there have been instances

where it goes and deletes a bunch of your files

or deletes a bunch of your emails

or we could get your credit card into a fraud situation.

It's very insecure, but the potential is massive

for you to just connect it to everything in your system

and all of your logins and all of your data.

And then these agents, they're doing all these complicated things.

You can set it to do a task and then walk away.

It's just become this whole other level

in terms of what agents are capable of doing.

OpenClaw was acquired by OpenAI last month,

but other companies are getting on board

with what agents like OpenClaw can do.

Here's Nvidia's CEO, Jensen Wong,

speaking at the company's annual developers conference

earlier this month.

Every company in the world today needs

to have an OpenClaw strategy,

an agentic system strategy.

This is the new computer.

Isabel, what is the promise for this next generation

of AI agents for companies?

Jensen saying every company needs

to have an OpenClaw strategy was really bold.

It's hard to know how different

an OpenClaw strategy needs to be

from an agent strategy.

The potential for businesses is vast.

And I think the direction this is all going

is that knowledge workers will engage

with fewer and fewer interfaces.

And if you could think about a way, way, way future state

as a knowledge worker, you might just have to engage

with your OpenClaw agent.

The agent handles the back end of everything.

And you just have a much simpler,

cleaner experience.

Coming up, the risks that agentic AI brings with it.

And where AI agents go from here?

That's after the break.

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It's about what are the risks that come

with the use of Agentic AI?

The idea that an agent can take action is great,

but also not great for businesses,

because in AI, by its nature, can hallucinate.

It can get things wrong if you're issuing

a customer a refund.

What if you issue them like too big a refund

or what if you promise them a deal that doesn't exist?

You have to put a lot of faith in the agent

in order to let it act fully autonomously.

So a lot of companies still want to have a human in the loop.

They want the agent to do a lot of the leg work

and then the human employee can sign off on that.

And then agentic shopping is going to be a huge trend

like giving an agent your credit card information

and saying, purchase this shirt for me

when the price hits $50.

But what if it purchases it for you?

Well, the price is still $80.

If you're a credit card company,

the one that operates that credit card that was used

are you liable?

Is the AI liable?

How responsible are people for the actions

their agents take?

And 10 agents be hacked to give away

your personal, sensitive, valuable data,

things like your credit card information.

So there's a lot of unknowns and a lot of security concerns.

What sort of harkens back to the early days of the internet

when people were afraid to put their credit card information?

To buy anything online.

Tech companies have been investing hundreds of billions of dollars

into AI.

Are AI agents finally the way that AI makes companies money?

I don't know if we've seen that prove out yet.

It still seems like companies are investing a lot of money

to use AI.

And it's been hard for them to point to a clear example

of an actual financial return.

In a lot of ways, those financial returns are linked

to the size of the workforce they have.

And so if they do layoffs and say we're being a lot more

efficient with AI, is that an example of a return?

So I do think over time there will be some right sizing of

the workforce based on the fact that companies now have all

these AI capabilities.

But that kind of seems like a longer term horizon.

I do think revenue per employee is going up.

Like companies are making more money on a per employee

basis than they have in the past.

But this is something that's just very hard to measure.

And so I think a lot of companies have given up on the phase

of we made X percent return on the amount of money we

spun on AI and have just accepted that this is a necessary

technology for them to be using as a company.

And even if they can't prove it out with a specific number

value that doesn't make the investment all worth of.

One of the other bigger conversations that's going on in this moment

is particularly investor skepticism about what AI means

for companies built around software.

Some people are calling it the SaaS apocalypse

referring to software as a service.

What does the rise of AI agents tell us about where that

conversation is headed?

The rise of these super capable AI agents is another thing

that puts pressure on these traditional legacy SaaS

companies, especially the coding agents,

because that's where you saw a lot of the SaaS

apocalypse fears stem from, which is with this great

new coding agent.

I don't need those expensive legacy providers.

The more nimble startups with supercutting AI agents we see,

the more pressure it does put on those companies.

From what I've seen, most of those companies are pretty

aware of where things are headed.

And they've made huge investments themselves in agents,

like if you take sales forces, an example,

like they're making it a very front end center in terms of

their strategy.

I think it's just a question of how fast can those companies move

and how good are the agents they're building compared to the AI

native startups and the agents they're building?

That was Wall Street Journal Tech reporter,

Isabelle Busquette.

Thanks, Isabelle.

Thanks again for having me.

And that's what's new Sunday for March 29th.

Today's show was produced by PRBNMA

with supervising producers Tally Arbell and Melanie Roy.

I'm Alex Osola, and we'll be back tomorrow morning

with a brand new show.

Until then, thanks for listening.

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