Generative AI is incredibly powerful and broadly capable. AI-based products are becoming more embedded across our economy and an integral part of company success. The scope, scale, and impact of this technology requires thoughtful deployment to capture the benefits without amplifying harm. This blog post introduces Yellow Teaming, a powerful methodology for software developers and product managers to rooted in Responsible AI principles. It helps you build better products – better for your company in the short and long term, better for your users, and better for society.
No technology is neutral. Arm solutions, for example, are not neutral – they are designed for security, low power draw, and high performance. AI-powered applications are no different, as they enable certain user behavior and prevent others from happening.
Think of your product like a compass. The compass always points somewhere, but the direction depends on where its needle is set. In AI-based products, the needle is set by your training data biases, by the incentives you create, and by the easiest path through your interface. If you do not adjust this needle on purpose, you may guide users in the wrong direction—harmful to them, to society, and ultimately to your business.
Yellow Teaming is the compass calibration process for your product. It prompts you to ask broader "so‑what?" questions early, so your product’s magnetic center aligns with long‑term value rather than only short‑term metrics.
Yellow Teaming builds on the more familiar concept of Red Teaming. During Red Teaming, teams step into the role of malicious users and attempt to break or use their product in nefarious ways. They then use insights from this exercise to strengthen their product before release. If you are not already practicing some form of Red Teaming, we highly encourage it.
Yellow Teaming involves asking a set of probing questions to help reveal the broader, unintended impacts of your product on your business, your users, and society at large. What you learn from asking and answering these questions is fed back into design requirements and success metrics, creating a better product. The concept draws on the Development in Progress essay by The Consilience Project and The Center for Humane Technology’s Foundations for Humane Technology courseware (Module 3).
We released a blog post on PyTorch community that teaches software developers (1) How to Yellow Team their own products, and (2) How to build a custom GPT to assist in their Yellow Teaming process. We also apply the methodology to a hypothetical AI-based app that turns a group chat conversation into a catchy pop song.
If you are interested in Yellow Teaming your product or product concept, we recommend that you read the PyTorch blog post for implementation details. You can then Yellow Team yourself/with your team, build a local Llama3-8B model with PyTorch to assist, or use the provided system prompt in a more capable public GPT.
Visit us at We Are Developers in Berlin where we are delivering a workshop on Yellow Teaming your product. Later in the year, you can visit us at PyTorch Conference 2025 where we will be showcasing Yellow Teaming best-practices for developers creating AI applications with PyTorch.