Red-Teamed My AI Agent. Here Are the 5 Ways It Broke.

🚀 BotGauge just launched their new platform: the AI Agent Red-Teaming Platform.

I spent [a weekend] trying to break my own AI agent. Spoiler: it broke in five different ways. Here's each one and how to test for it, so you can find yours first.

I just… told it to ignore its instructions. [What happened.]

Test it: send override phrases in lots of flavours: polite, urgent, role-play, encoded. Check the system policy holds.

The sneakier one. I hid an instruction inside a doc the agent retrieved.

Test it: plant instructions in tool outputs and knowledge-base chunks. Does the agent treat them as data or obey them?

The one that actually scared me: right tool, wrong arguments.

json { "action": "book_flight", "destination": "", "approval": "skipped", "status": "blocked", "reason": "policy_violation" }

Test it: assert on tool calls and arguments, not just the final text.

Turn one: perfect. Turn six: totally caved.

Test it: run long conversations that slowly ramp up the pressure.

I swapped the model version and a case that used to pass started failing. No code changed.

Test it: keep every past failure as a regression eval and re-run on every change.

Doing this by hand once was fun. Doing it every release is not. BotGauge just launched their new platform, the AI Agent Red-Teaming Platform, and it handles the whole loop:

Red Teaming: adaptive, adversarial and real-world attacks Tracing: every prompt, tool call and execution path Evaluations: failures become checks automatically Policies and Guardrails: your rules, enforced in prod

Works with LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen and AutoGPT. Check their docs for the SDK setup.

🔗 Product Hunt page: https://www.producthunt.com/products/botgauge-2?launch=botgauge-4

They're live on Product Hunt today, so an upvote and an honest comment would mean a lot to the team.

Which of these five has bitten you? Tell me in the comments 👇