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

29 Mar 2026 · 12 min · 7 chapters

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In short

Agentic AI—AI agents that execute tasks on your behalf—what they mean, how companies use them (coding and customer service), how they may generate value, and the major risks (hallucinations, security, liability). It also connects to investor concerns about SaaS (“SaaSpocalypse”) as coding agents threaten legacy software providers.

Guest backgrounds

Isabel Busquets, Wall Street Journal tech reporter.

Key claims

“Agent” lacks a common definition; agentic starts when the system acts externally (e.g., booking, buying). Coding agents are measured via token costs vs productivity (claims of 10x–50x). OpenClaw is an open-source orchestration framework; OpenClaw’s acquisition by OpenAI raises expectations. Companies may shift knowledge workers to fewer interfaces via an “OpenClaw agent.” Risks include hallucinations, human-in-the-loop needs, credit-card/agent liability, and hacking/data exposure.

Notable examples

restaurant reservations, doctor appointments, flights, order tracking, loyalty-card replacement; coding tools (Claude Code, OpenAI Codex, Cursor, Replit, Lovable); OpenClaw; Jensen Wong urging an “OpenClaw strategy”; Salesforce investing in agents.

Written by AI. May contain mistakes. Listen to the episode to check what was said.

Chapters

Tap a time to open that second in VO

Understanding AI Agents

0:45 to 1:57

Explore the concept of AI agents and their emerging roles in technology.

“On today's show, agentic AI is the buzziest word in tech right now.”

AI Agents in Coding and Customer Service

1:57 to 3:19

Learn how AI agents are transforming coding practices and customer service.

“that's the point at which it becomes an agent.”

The Financial Implications of AI Agents

3:19 to 5:01

Discover how AI agents impact company profitability and efficiency.

“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.”

The Promise of OpenClaw

5:01 to 6:20

Delve into OpenClaw's potential as a personal assistant and its risks.

“Here's NVIDIA CEO Jensen Wong speaking at the company's annual developers conference earlier this month.”

Risks of Agentic AI

6:36 to 7:58

Examine the risks and uncertainties associated with AI agents.

“The idea that an agent can take action is great, but also not great for businesses because an AI, by its nature, can hallucinate.”

The Financial Future of AI Agents

7:58 to 9:27

Discuss the potential for AI agents to generate financial returns for companies.

“were afraid to put their credit card information to buy anything online.”

The SaaSpocalypse: AI's Impact on Software

9:27 to 10:50

Analyze the effects of AI agents on traditional software companies.

“with a specific number value, that doesn't make the investment not worth it.”
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Transcript

Automatic transcript. May contain errors.

0:02Alex Ossola:If you're early in your career and looking for insight, inspiration, and honest advice, listen to the Capital Ideas podcast. Hear from Capital Group professionals about leaning into the differences that make you unique, making decisions that last, and what it means to lead with purpose. The Capital Ideas podcast from Capital Group, available wherever you listen. Published by Capital Client Group, Inc.

0:32Alex Ossola:Hey, What's News listeners. It's Sunday, March 29th. I'm Alex Osola for The Wall Street Journal. This is What's News 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 buzziest 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.

1:12Alex Ossola:Journal tech reporter Isabel Busquets joins me to discuss.

1:22Alex Ossola: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. Buy 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?

2:07We'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 Claude Code and OpenAI Codex of the world to Cursor, replit, lovable. 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 if a customer calls with a question about like where their order is, an AI agent can handle that call and give status updates or replace a missing loyalty card or things like that.

2:51Alex Ossola: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 an actual salary but on the flip side of that they're also looking at the amount of work this person is doing.

3:42And 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 the returns at this point.

4:03Alex Ossola: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 an 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 it 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.

4:43And 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.

4:57Alex Ossola:OpenClaw was acquired by OpenAI last month, but other companies are getting on board with what agents like OpenClaw can do. Here's NVIDIA 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 open claw strategy needs to be from an agent strategy.

5:34The 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 open claw agent. The agent handles the back end of everything. And you just have a much simpler, cleaner experience.

6:02Alex Ossola: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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6:35Alex Ossola:Isabel, 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 an 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 legwork. And then the human employee can sign off on that.

7:15And 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 can 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. It 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.

8:05Alex Ossola: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.

8:56I do think revenue per employee is going up. 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 spent 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 not worth it.

9:32Alex Ossola:One of the other bigger conversation 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 SaaSpocalypse, 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 SaaSpocalypse fears stem from, which is with this great new coding agent, I don't need those expensive legacy providers.

10:12The more nimble startups with super cutting edge 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 Salesforce as an example, like they're making it very front and 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.

10:50Alex Ossola:That was Wall Street Journal tech reporter Isabel Busquets. Thanks, Isabel. Thanks again for having me. And that's What's New Sunday for March 29th. Today's show was produced by Pierre Bien-Aimé with supervising producers Tali Arbel and Melanie Roy. I'm Alex Osala, and we'll be back tomorrow morning with a brand new show. Until then, thanks for listening.

11:21Alex Ossola:legal teams face more data and more scrutiny than ever they need ai built for both relativity is the ai platform for legal work delivering defensible ai that handles the tedious tasks so judgment stays where it belongs, with you. Learn more at relativity.com forward slash WSJ.

From the publisher

AI agents—artificial-intelligence tools that can perform real-world tasks—are the buzziest thing in Silicon Valley. Some businesses and individuals are already using them, and the next generation of agents like OpenClaw could be even more promising. But they also come with significant risks. WSJ tech reporter Isabelle Bousquette joins host Alex Ossola to discuss how agentic AI is being used now and how it could be used in the future.

Further Reading: 

China’s OpenClaw Craze Buoys Tech Stocks, Fuels AI Pivot 

The World’s First Viral AI Assistant Has Arrived, and Things Are Getting Weird 

This Viral AI Project Went From Side Hustle to Coveted Prize in Three Months

Nvidia Software Aims to Bring OpenClaw to the Enterprise 

Silicon Valley’s New Obsession: Watching Bots Do Their Grunt Work Mark Zuckerberg Is Building an AI Agent to Help Him Be CEO

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