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

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.

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."

1. Measure your success

Hron said the first area to focus on is evaluations: "You need to know what good looks like."

2. Make experts sit together

"Tightly coupling that awareness to the user experience is increasingly important," he said.

3. Develop proven capabilities

AI models are improving across three dimensions: writing code, executing plans, and multi-step reasoning.

4. Look beyond the firewall

Thomson Reuters Labs recently launched the Trust in AI Alliance to discuss how trust is engineered into agentic systems.