Why "Working Backwards" is the One of the Best Ways to Design AI Products
Most AI projects start with a model, not a mission. A team finds a new algorithm or API and thinks, “What can we do with this?” Weeks later, there’s a working prototype—but no clear user value.
That’s why “Working Backwards”, a method popularized by Amazon, is one of the best approaches for designing AI products. It flips the process: instead of starting with technology, you start with the user.
This mindset is especially powerful in AI, where possibilities are endless and focus is scarce.
What “Working Backwards” Means
Working Backwards is a simple but disciplined approach:
Start with the customer experience.
Write the press release for the ideal product launch.
Define the FAQs—the tough questions users, engineers, and executives will ask.
Then, and only then, decide what to build.
It forces clarity: if you can’t explain the user benefit in plain language, you’re not ready to start building.
Why It Fits AI Product Management So Well
AI makes it dangerously easy to build before thinking. The models are impressive, the demos exciting—but without purpose, AI features turn into gimmicks. Working Backwards keeps you grounded.
It helps PMs avoid three common traps:
Building “because the model can,” not because the user needs it.
Measuring success only in accuracy, not in outcomes.
Forgetting ethical and trust considerations until it’s too late.
When you begin with the user and work back to the model, everything—from data to metrics—aligns with value.
The Press Release Exercise
Writing the press release (PR) is the heart of the Working Backwards method.
Imagine the product has launched successfully and you’re announcing it to the world. The PR should include:
The problem it solves and for whom.
Why it’s different from what exists today.
The user benefit in simple, emotional language.
How it works at a high level—without buzzwords.
If you can’t make it exciting, simple, and believable on paper, it probably won’t resonate in real life.
The FAQ Exercise
Once the press release is done, you write an internal FAQ—anticipating hard questions before anyone builds a thing.
What data do we need, and do we have it?
What are the risks of bias or misuse?
How will we measure trust and success?
How will the AI explain itself to users?
What is our fallback if the model fails?
Answering these early protects the team from surprises later. It also aligns engineers, designers, and stakeholders around what really matters.
Why It Works for AI
AI products live in uncertainty. You don’t always know if the data is sufficient, the model will perform, or users will trust it. Working Backwards gives you a way to test clarity before committing to complexity.
It’s user-first, ethical by design, and measurable from day one.
Real-World Example
Before Amazon launched Alexa, the team didn’t start with “let’s build a voice assistant.” They started with a vision statement: “It should be effortless for anyone to order something or get information just by speaking.”
That user-centered statement guided everything—from the architecture to the skills ecosystem that came later. The same principle applies to any AI product.
Final Thought
Working Backwards may sound simple, but it’s one of the most effective disciplines for AI product management. It forces clarity, accountability, and empathy—the three things AI needs most.
AI may change how products are built, but Working Backwards ensures we never forget why we build them.