4 tips for building better AI agents that your business can trust

## Summary
Also: Worried AI agents will replace you? 5 ways you can turn anxiety into action at work Hron told ZDNET that Thomson Reuters uses a mix of in-house models and off-the-shelf tools to power its AI innovations. But it's increasingly delivered via agents, or agents plus software." Hron points to several key agentic achievements at Thomson Reuters, including the AI-powered legal research tool Westlaw Advantage and the firm's Deep Research agent that reviews insights and strategizes as a researcher would. Make experts sit together Hron advised professionals to understand deeply what agents do and how they operate over time. "Tightly coupling that awareness to the user experience is increasingly important," he said. "If you think about these agentic systems like human AI collaborators, then the human and the agent need a common language and a common interface that they work on." Also: Why enterprise AI agents could become the ultimate insider threat Hron said this common language and interface should give humans valuable insight into agentic thought processes and vice versa. "This area is a new and important UI experience, and I think tightly coupling deep technical understanding of the agent with a good user experience is critical." While many experts talk about the importance of human/agent coupling, Hron said the key to success is straightforward: bringing teams in the business together. "This process isn't scientific -- it's about forcing my designers to sit with data scientists and talk about what's happening," he said. "The closer we can make those two sets of people, and the more often they can sit together, the better you have the osmosis of thinking across those two areas." 3. Also: 90% of AI projects fail - here are 3 ways to ensure yours doesn't "If we can decompose these elements as tools for the agent, then we're actually extending the capabilities of these models quite a lot, and that's really the future of agents." Rather than seeing agentic AI as an omniscient model that attempts to do everything under the sun, Hron advised professionals to give agents access to proven capabilities people already use, which is a focus of his team. "We're looking at our systems and asking ourselves, 'OK, we've built this for a human user for many, many years.

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4 tips for building better AI agents that your business can trust
Agents are coming. Here are four ways to prepare for the AI-powered workplace revolution.
Written by
Mark Samuels,
Senior Contributor
Senior Contributor
March 21, 2026 at 3:00 a.m. PT
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ZDNET's key takeaways
Companies are exploring AI agents in multiple ways.
Professionals must consider how to exploit these technologies.
Measurement, collaboration, and experimentation are key.
AI agents will
impact every professional role
. If your company hasn't started using agents yet, it will soon, either through off-the-shelf software products or in-house tools that draw on large language models and data sources.
Professionals exploring how to use agents in their roles are well-advised to seek
best-practice guidance
. One such source of information is Joel Hron, CTO at Thomson Reuters Labs, who is helping the information services company exploit generative AI, machine learning, and agentic technologies.
Also:
Worried AI agents will replace you? 5 ways you can turn anxiety into action at work
Hron told ZDNET that Thomson Reuters uses a mix of in-house models and off-the-shelf tools to power its AI innovations. As well as advances in frontier labs from Big Tech firms, Hron and his team ensure the firm exploits its proprietary knowledge and assets.
"If you look at the core of what we do well, it's being able to synthesize human expertise and information into judgment that can be served back to professionals," he said.
"The delivery mechanism for how that expertise is delivered is evolving right now. Traditionally, it's been delivered via software. But it's increasingly delivered via agents, or agents plus software."
Hron points to several key agentic achievements at Thomson Reuters, including the AI-powered legal research tool Westlaw Advantage and the firm's Deep Research agent that reviews insights and strategizes as a researcher would.
Also:
AI agents are fast, loose, and out of control, MIT study finds
From these explorations, Hron said he's learned four key lessons that professionals can use to build trustworthy agentic AI systems.
1. Measure your success
Hron said the first area to focus on is evaluations: "You need to know what good looks like."
While this focus on evaluations sounds like an obvious requirement, Hron said it's a hard process to get right, to quantify, and to systematize.
"We've said that for the last three years that this is one of the most important things for building good AI systems, and it continues to be true today in an era of agents," he said.
Hron: "We still want the confidence of our human experts."
Thomson Reuters
Hron's team tracks and measures agentic success in several ways. First, they leverage public benchmarks, which he said provide good early indicators of the positive potential performance of new models.
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Second, they've developed their own internal benchmarks with strong directions for automated evaluations: "Rather than just saying, 'How close is the generated answer to a good answer?', our process is about really defining, 'Well, what makes the answer good?'"
Finally, Thomas Reuters keeps humans in the loop, ensuring evaluations go a step beyond automated assessments.
"Automated evaluations help drive the flywheel faster for our development teams, and they can test a lot of ideas relatively quickly, and that's good. But before we ship, we still want the confidence of our human experts and their assessment of the performance," he said.
"The continued reliance on that approach has allowed us to ship great products that perform well in the market. I think human input is a critical ingredient to us being able to do that work well and do it with confidence."
2. Make experts sit together
Hron advised professionals to understand deeply what agents do and how they operate over time.
"Tightly coupling that awareness to the user experience is increasingly important," he said. "If you think about these agentic systems like human AI collaborators, then the human and the agent need a common language and a common interface that they work on."
Also:
Why enterprise AI agents could become the ultimate insider threat
Hron said this common language and interface should give humans valuable insight into agentic thought processes and vice versa.
"This area is a new and important UI experience, and I think tightly coupling deep technical understanding of the agent with a good user experience is critical."
While many experts talk about the importance of human/agent coupling, Hron said the key to success is straightforward: bringing teams in the business together.
"This process isn't scientific -- it's about forcing my designers to sit with data scientists and talk about what's happening," he said

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## Expert Analysis

### Merits
- Innovation Home Innovation Artificial Intelligence 4 tips for building better AI agents that your business can trust Agents are coming.
- But it's increasingly delivered via agents, or agents plus software." Hron points to several key agentic achievements at Thomson Reuters, including the AI-powered legal research tool Westlaw Advantage and the firm's Deep Research agent that reviews insights and strategizes as a researcher would.
- Measure your success Hron said the first area to focus on is evaluations: "You need to know what good looks like." While this focus on evaluations sounds like an obvious requirement, Hron said it's a hard process to get right, to quantify, and to systematize. "We've said that for the last three years that this is one of the most important things for building good AI systems, and it continues to be true today in an era of agents," he said.
- Hron: "We still want the confidence of our human experts." Thomson Reuters Hron's team tracks and measures agentic success in several ways.

### Areas for Consideration
- Make experts sit together Hron advised professionals to understand deeply what agents do and how they operate over time. "Tightly coupling that awareness to the user experience is increasingly important," he said. "If you think about these agentic systems like human AI collaborators, then the human and the agent need a common language and a common interface that they work on." Also: Why enterprise AI agents could become the ultimate insider threat Hron said this common language and interface should give humans valuable insight into agentic thought processes and vice versa. "This area is a new and important UI experience, and I think tightly coupling deep technical understanding of the agent with a good user experience is critical." While many experts talk about the importance of human/agent coupling, Hron said the key to success is straightforward: bringing teams in the business together. "This process isn't scientific -- it's about forcing my designers to sit with data scientists and talk about what's happening," he said. "The closer we can make those two sets of people, and the more often they can sit together, the better you have the osmosis of thinking across those two areas." 3.

### Implications
- AI agents will impact every professional role .
- If your company hasn't started using agents yet, it will soon, either through off-the-shelf software products or in-house tools that draw on large language models and data sources.
- Also: Worried AI agents will replace you? 5 ways you can turn anxiety into action at work Hron told ZDNET that Thomson Reuters uses a mix of in-house models and off-the-shelf tools to power its AI innovations.
- Make experts sit together Hron advised professionals to understand deeply what agents do and how they operate over time. "Tightly coupling that awareness to the user experience is increasingly important," he said. "If you think about these agentic systems like human AI collaborators, then the human and the agent need a common language and a common interface that they work on." Also: Why enterprise AI agents could become the ultimate insider threat Hron said this common language and interface should give humans valuable insight into agentic thought processes and vice versa. "This area is a new and important UI experience, and I think tightly coupling deep technical understanding of the agent with a good user experience is critical." While many experts talk about the importance of human/agent coupling, Hron said the key to success is straightforward: bringing teams in the business together. "This process isn't scientific -- it's about forcing my designers to sit with data scientists and talk about what's happening," he said. "The closer we can make those two sets of people, and the more often they can sit together, the better you have the osmosis of thinking across those two areas." 3.

### Expert Commentary
This article covers hron, agents, models topics. Notable strengths include discussion of hron. Areas of concern are also raised. Readability: Flesch-Kincaid grade 0.0. Word count: 1543.