One in Four Organizations Are Leaking Secrets Through AI Agent Config Files
A Codacy scan of 34,266 repos found credentials, API keys, and system prompts exposed in AI agent config files at 25% of organizations.
A reality check making the rounds on Reddit's r/artificial forum lands on an uncomfortable number: copper prices hit all-time highs in 2026, and global ore grades are declining — meaning you now have to move more earth to extract the same amount of refined metal. No automation breakthrough changes that equation.
The argument targets a specific strain of AI optimism that claims AI-enabled mining robots will solve resource constraints. Ore grade decline is geological, not logistical. When you are processing lower-quality ore, efficiency gains help at the margin but cannot overcome an exponential increase in the volume of material that has to be dug up and processed. The physics do not bend.
The copper exposure runs throughout AI infrastructure. A large hyperscale data center can consume tens of thousands of tons of the metal across wiring, bus bars, transformer windings, and cooling systems. As the AI build-out accelerates — with dozens of gigawatt-scale facilities now planned globally — demand from the sector is rising against a supply curve that moves in the years-long timescales of mine development.
Resource inflation is already priced into infrastructure project budgets. It just has not made it into the AI abundance narratives yet.
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A Codacy scan of 34,266 repos found credentials, API keys, and system prompts exposed in AI agent config files at 25% of organizations.
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