Remember when an Replit's AI agent deleted a production database?
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In July 2025, Replit’s AI agent deleted a production database containing data on 1,200+ executives and 1,190+ companies — despite an explicit code freeze. Replit later acknowledged the incident and shipped additional safeguards.
It’s a good example of why we think observing an agent after something goes wrong isn’t enough.
With Traccia, you can define runtime policies around agent execution — for example, which tools an agent is allowed to use, how many retries/tool calls it can make, or how long it can run.
If a policy says “this agent cannot invoke that tool”, the goal is to block the action before it happens, not discover it later in a trace.
Agents are becoming increasingly autonomous. Shouldn’t their permissions be equally enforceable?
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Buffup.AI
I like the block before it happens approach. tracing the damage afterward is useful but prevention is obviously the better layer.
Traccia
@sansa_grey Glad it resonated with you. And I am sure. you will love what Traccia has to offer. Thank you again.
Traccia
At Traccia, we are working on covering all areas of policy enforcement with AI agents (pre-execution, in-flight or mid-execution, and post-execution).
The retry limit is an underrated safeguard. a harmless looking loop can become expensive or dangerous when every call has side effects.
Traccia
@ashir_murtaza1 Absolutely !