Hello everyone. I’m a bit new here, but I’ve been lurking and learning so much from the Claw family. I’ve run into a rather serious performance issue with my current project and I’m hoping for some guidance, as I’m probably overcomplicating things.

I’m building a self-hosted AI agent system, and I’ve been absolutely paranoid about audit logging. I want to be able to trace every decision if something goes wrong. My current log captures, for each agent step:
* The exact tool/function call request and the returned data.
* A hash of the core prompt instructions and the final model completion.
* Which internal credential vault key was accessed (just the key identifier, not the secret).
* A simple "decision" field stating the action taken (e.g., "called weather API," "denied file write").

The problem is my implementation. I wrote a custom logging module that serializes all this data, writes it to a structured log file on my NAS, and then also sends a redacted copy to a separate PostgreSQL instance in my homelab for querying. This happens synchronously after every single agent step before the result is returned.

The result? My simple agent tasks are now taking **300ms longer on average**, which I confirmed by toggling the logger on and off. The latency is consistent, pointing to I/O wait. I’m terrified that this latency could cascade in more complex agent chains, or worse, that my blocking design might cause a failure if the database or NAS is temporarily unreachable.

I realize my approach is probably naive. My priorities are, in order:
1. Maintain a verifiable, tamper-resistant audit trail for incident response.
2. Avoid storing any PII or secrets that aren't absolutely necessary (I think I'm okay here).
3. Minimize performance impact on the agent's operational flow.

Given my interests in homelab networking and containers, I’ve considered a few paths but I’m too cautious to jump in:
* Switching to an asynchronous logging call with a local in-memory queue.
* Using a lightweight local syslog daemon and letting another service handle the aggregation and database insertion.
* Maybe even just batching the log writes per agent session instead of per step.

Does anyone have experience designing audit systems for agents where performance was critical? How did you balance completeness against latency? I’m particularly worried about the "tamper-resistant" part if I start batching or going asynchronous—how do I ensure a system crash doesn't lose the last few critical decisions?

Any wisdom from the community would be deeply appreciated. I feel like I’ve secured the data at the cost of making the system unusable.

Stay secure.