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Chronicles

The story behind the story

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Goldman Sachs CTO Marco Argenti says the bank will “start augmenting our workforce with Devin”, Cognition's AI software engineer, as Wall Street firms adopt AI

The newest hire at Goldman Sachs isn't human.  —  The bank is testing an autonomous software engineer …

CNBC Hugh Son

Context & Ripple Effects

Goldman had already moved from experimentation to broad employee access with its companywide GS AI Assistant rollout, creating an internal base for more specialized AI tools. Devin marks a more consequential step because it is aimed at software-engineering work rather than general productivity.

Subsequent coverage of Goldman working with Anthropic on agents for trades, transactions, vetting and onboarding shows the bank extending agent use beyond coding. That makes this an early signal of a broader operating-model shift, not an isolated developer-tool pilot.

First-order effects

  • Goldman Sachs begins integrating Cognition's Devin into its workforce model, putting the bank's software-engineering workflows under immediate pressure to define which tasks can be delegated and how outputs are reviewed.
  • Cognition gains a high-profile financial-services deployment for an autonomous software engineer, while Goldman’s engineers must work alongside and validate an AI contributor.

Second-order effects

  • Wall Street peers that have deployed general-purpose assistants face a sharper decision: whether to limit AI to employee support or test agents that execute discrete technical work.
  • The shift raises the value of controls around code review, access permissions and accountability, especially as Goldman’s own later employee-use coverage identified over-reliance on generative AI as a risk.

Third-order effects

  • If banks can reliably supervise agent-produced work, enterprise AI adoption may progress from productivity assistants to role-specific systems embedded in regulated operating processes.
  • The durable competitive divide may center less on access to a model than on institutions’ ability to integrate agents with proprietary systems, oversight and human escalation paths.

The trend: Financial institutions are moving from broad generative-AI assistance toward supervised, task-executing agents in core internal workflows.