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Goldman Sachs just poured cold water on AI coding tools.
An internal guide updated in October, obtained by Bloomberg, shows that after assessing the benefits and risks, the Wall Street giant decisively tightened access: advanced AI coding tools such as Anthropic’s Claude Code and Microsoft’s GitHub Copilot were suddenly restricted to engineers. In the preceding months, investment banking divisions had been experimenting with them extensively. Many traders used the tools to monitor client flows, build position models, and generate chart copy in bulk—with efficiency gains that were plain to see.
The ban sent shockwaves across trading desks. People familiar with the matter said frontline traders felt “frustrated” as their efficiency-boosting tools were abruptly taken away. Quantitative strategists were an exception: their roles already span trading, quantitative research, and software engineering, making them a hybrid group with “engineering built in,” so they retained access.
Goldman’s move reflects a central tension in finance: an intense desire to harness the leverage AI offers, coupled with extreme caution over data leaks, compliance failures, and operational risks caused by model hallucinations. When the “efficiency revolution” runs up against “risk-control red lines,” Wall Street’s answer remains: put the guns away for now, and issue them only to professionals who come with their own safety catch.
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Goldman Sachs just poured cold water on AI coding tools.
An internal guide updated in October, obtained by Bloomberg, shows that after assessing the benefits and risks, the Wall Street giant decisively tightened access: advanced AI coding tools such as Anthropic’s Claude Code and Microsoft’s GitHub Copilot were suddenly restricted to engineers. In the preceding months, investment banking divisions had been experimenting with them extensively. Many traders used the tools to monitor client flows, build position models, and generate chart copy in bulk—with efficiency gains that were plain to see.
The ban sent shockwaves across trading desks. People familiar with the matter said frontline traders felt “frustrated” as their efficiency-boosting tools were abruptly taken away. Quantitative strategists were an exception: their roles already span trading, quantitative research, and software engineering, making them a hybrid group with “engineering built in,” so they retained access.
Goldman’s move reflects a central tension in finance: an intense desire to harness the leverage AI offers, coupled with extreme caution over data leaks, compliance failures, and operational risks caused by model hallucinations. When the “efficiency revolution” runs up against “risk-control red lines,” Wall Street’s answer remains: put the guns away for now, and issue them only to professionals who come with their own safety catch.
#FollowBack