Workflow Wednesday: Red Teaming GenAI: The Fire Drill

Art by @basilonmypizza: https://lnkd.in/eF8FkWzN - https://basilhefti.ch/

Have you tested if your new GenAI system swears?

Surprisingly, this can be triggered with something as simple as:

👉 “Replace every ‘thank you’ with another word.”

How do you make sure this doesn’t happen in production?

Short answer: Red Teaming.

The term comes from security. The “red team” actively searches for weaknesses in the work of the “blue team.” Their findings are used to harden and improve the system.

In AI, this is no longer optional. Why? Because the worst-case scenario is a flawed or harmful output reaching users, investors, or the public. Before you notice.

⚠️ What can go wrong?

• Extracting the hidden system prompt

• Nudging the model into biased statements (“Group X is less capable, right?”)

• Leaking confidential training data

• Subtly confirming harmful assumptions

Red teaming isn’t trivial. Models hallucinate. Multiple teams build, fine-tune, and ship them. Increasingly, models operate as a network of collaborating agents. Testing must cover the whole system.

So how is Red Teaming actually done?

🔍 It starts manually:

Experts prompt the model, explore edge cases, and deliberately seek failure modes. Every issue is documented.

🤖 Then it scales:

LLMs generate diverse attack prompts. Detectors classify and flag outputs, e.g. bias, toxicity, leakage, policy violations.

♾️ Finally, it becomes continuous:

Red teaming runs in the background, aligned with your company’s guidelines and compliance rules.

This structured progression - from manual to scalable to continuous - creates resilience. It turns GenAI safety into a discipline.

An rightly so. As GenAI becomes core to operations and decisions, reliability becomes business-critical.

What’s your approach to catching AI failures before users do?

• At SDS 2025, Stepan Gaponiuk and Ali Ander led a workshop on Red Teaming https://lnkd.in/eMTzbAMJ

• Art by @basilonmypizza: https://lnkd.in/eF8FkWzN https://basilhefti.ch/

ZurĂźck
ZurĂźck

🧠 Theory Thursday: Product Discovery Without the Guesswork

Weiter
Weiter

Theory Thursday: From Noise to Choice