Interview: How a startup mentality helps keep pace with AI

Keeping up with the AI development cycle

Hron joined Thomson Reuters through the 2022 acquisition of tech startup ThoughtTrace, which had developed a document analysis system for due diligence. Following the acquisition, Hron worked as the company’s head of AI, then, in 2024, he became CTO. In this role, he leads product engineering and AI research and development for Thomson Reuters’ global portfolio of products and services.

Given AI’s pace of change, with major shifts happening every six months or so, Hron admits that some organisations may struggle to keep up.

Drawing on his own personal experience, he says: “I think my career has taken a lot of unpredictable paths and turns along the way, and adaptability has really helped me in this environment because the pace of change that we’re experiencing requires high levels of conviction. You need to be able to have strong opinions, but change those opinions any day.”

Working at a startup provided a grounding in how to be successful by having what he calls “really intense focus and being able to move fast”. 

The ability to adapt quickly is a key factor in whether an AI project succeeds or fails, and how quickly organisations can swap and replace models. His advice to tech and business chiefs is to ensure their organisation has a deep understanding of how decisions are made, covering areas such as process analysis, organisational design and culture.

Building for agentic AI

The MCP connectivity with Claude represents the continued evolution of the Thomson Reuters CoCounsel Legal product. Hron says the North Star for CoCounsel is to build AI products that deliver a fiduciary-grained level of performance. While the legal profession is being transformed by AI, which is being used to draft, summarise and analyse documents in seconds, he says it is difficult to ensure outputs are grounded in authoritative sources, validated for accuracy and traceable back to their origin. This is why Thomson Reuters has spent the past three years working on how to deliver an agentic AI workflow for the legal profession.

About nine months ago, the company decided to rebuild CoCounsel from the ground up, taking what Hron calls “an agent-first approach with coding agent orientation in partnership with Anthropic. “We focused on giving access to our content tools from the agent natively and we have exposed all our information so that the agent can use these tools to discover, plan and execute work,” he says.

Among the areas of the development he is most proud of is an evaluation framework called CoCounsel Bench. Explaining the work involved, Hron says: “We spent hundreds of thousands of hours with our internal experts developing to enable us to climb the hill from an agent development standpoint and help us understand whether we are making progress across all of the different segments of law.” 

CoCounsel product development began in 2023, with the $650m acquisition of CaseText, which had developed the tool as an AI legal assistant powered by GPT-4. In May, Thomson Reuters announced Model Context Protocol integration with Anthropic, which connects Claude directly to CoCounsel Legal. This enables legal professionals to move seamlessly between general-purpose AI and citation-grounded legal work from either working environment.

While 99.99% of the development effort has been spent on CoCounsel, Hron says the support for agentic AI workflows using MCP has mainly involved authentication and making sure the connection is secure and private, and that customer data is protected in an appropriate way. 

Although the MCP connector can be invoked by a Claude user to communicate with CoCounsel, Hron says it is more likely that Claude will access CoCounsel itself, to find the information it needs to complete a task.

“It will come up with its own plan and trajectory of work, cycling through iterations as many times as it deems necessary, which is why we have wide error bars in terms of the expectations of how those interactions with CoCounsel will happen,” he says.

Patterns of usage are analysed to enforce rate limiting and restrictions to prevent CoCounsel from being overloaded. “These constructs are very similar to how you might think of an API [application programming interface] rate limit, and in many ways they’re identical,” adds Hron.

Agentic coding

When asked for his thoughts on where AI is likely to be in six months from now, Hron says: “Software engineers fundamentally operate differently than they did six months ago, which has been driven by agentic coding tools.”

This has occurred because the LLMs have improved. But, he says, what has also evolved is the paradigm of how agents work and how they emulate human behaviour. In his experience, this has shifted the pattern of software development.

And as for his predictions for what will happen six months from now, Hron says: “I think you will see the patterns of other parts of work change in the same way.” 

He believes agents will operate in more humanistic contexts, which will mean that to ensure accountability and trust in what they do, human governance will need to be built into the workflow. It is something that is already built into the software development process.

“In coding, that’s self-governed,” says Hron. “For instance, on GitHub, you have diffs on code [the tools that list differences between different versions of source code], you have PR [pull request] reviews and stage gates [to review distinct phases of a software project] that enforce auditability.

“Human governance and oversight will be tremendously important as [agentic AI] starts to proliferate into other disciplines,” he adds.