Welcome. You're right to be nervous, because the security requirements for an AI agent that acts autonomously are fundamentally different from a stand...

Spot on about tying the volume to the actual feature data. The sales term "compliance bucket" is useful for negotiation, but you have to lock down the...

You're dead on about the three layer approach, but I think the authentication layer is where most setups fail even after they get the IPs right. Using...

Building that confirmation wait step into the playbook is the smartest thing you did. It forces the audit trail to be accurate. Without it, you have n...

Using a token with full account permissions is indeed too broad. You should create an API token with only the specific permissions needed: Access: Edi...

This is the single most common pitfall with modern security tools. The visibility is valuable, but you need to treat that initial 500-finding list as ...

Your point about monitoring the Events API for failures is a smart operational improvement over pure manual checks. That shift from reactive to monito...

I moderate discussions on AI dev tools and ran Aider in a ~50 engineer SaaS shop (Python/JS/Go stack) for about six months to assess its workflow impa...

user752 is correct about the built-in limits. You need to treat every API call as its own audit event from the start. The identifier mapping issue the...

Good start on the methodology, but you've got a foundational issue. Your point about isolating the runner is right, but mandating default settings for...