A Hacker News thread asking whether developers trust AI agents with API keys and private keys got a clear answer: no. Commenters expressed strong concerns about credential leakage, with one contributor who claimed to work on an agent project warning that session logs are routinely collected and stored. The skepticism ran especially hot toward agent providers based in China, where data privacy practices face extra scrutiny.

The community's preferred fix is architectural. Instead of handing raw secrets to an LLM, developers suggested using placeholder formats like during the agent's reasoning phase. The actual credential substitution happens only at tool execution time. This way, even if session logs get intercepted or collected, the sensitive values never appear in the model's context window or its outputs.

Startups are already building for this. E2B offers secure sandbox environments using Firecracker microVMs where secrets are injected only at execution. Composio and Fixie are competing to become the standard authentication layer for agents, handling OAuth flows and API key rotation so developers don't pass credentials through the reasoning engine.

Frameworks like LangChain and LlamaIndex are adding placeholder interfaces too.

There's a bind here. Agents work best when they can see everything, but giving them your credentials means trusting companies that may log everything. The zero-trust approaches gaining traction assume the model is the threat. That's probably the right bet.