Goldman's engineers have a new challenge: turning AI agents into firm insiders

Marco Argenti said that an engineer's main AI challenge has shifted.

Bloomberg/Getty Images Marco Argenti, chief information officer, said engineers need to transfer "tribal knowledge" to AI.

Now that all developers are using AI, Argenti said the focus is on making tools specific to Goldman.

AI is also transforming mentorship structures across lines of business.

Marco Argenti is facing a new problem: how to communicate the subtleties of Goldman Sachs' engineering culture to an AI bot.

Argenti, the firm's chief information officer, said that since the firm's more than 12,000 developers are all using AI, the focus is on making their AI tools Goldman-specific.

All of the bank's developers have access to updated agentic technology, including Claude and Devin, Cognition's AI coding assistant.

They now must figure out how to "mentor" the AI, much as they would a new employee who doesn't yet know Goldman's standards.

An AI agent that's familiar with Goldman's environment — its data standards or security protocols, for example — can produce better work, faster for engineers to review.

"The transfer of the institutional knowledge into the AI is the biggest question," Argenti said.

"How does an experienced GS AI look versus a naive AI?" Transferring "tribal knowledge" Goldman spent around $6 billion on AI last year and is, like its peers, under mounting pressure to show that its investments are paying off.

Jamie Dimon , the CEO of JPMorgan, said spending on AI is a prerequisite to staying competitive at this point.

Developers are often the most sophisticated AI users at banks, and Argenti said that they now need to teach AI agents the "tricks and tribal knowledge" that the technology doesn't intuitively grasp.

Goldman's "engineering tenets," as described in a blog post on the firm's website, include "innovate incrementally" and "look around corners," subjective directives that AI tools can't grasp as easily as rote instructions.