The Game-Changing System Behind Kindle, AWS, and Prime—and How I Apply It Today

I’m constantly looking for systems that outlast leaders and market cycles. When I picked up “Working Backwards,” which provides an inside look at the leadership principles and business processes that have made the company so successful, I recognized a playbook product teams can trust when the stakes are high and ambiguity is higher.

Bill Carr and Colin Bryar bring rare operator credibility to the topic. Bill started at Amazon in 1999, and went on to launch and run the Prime Video, Amazon Studios, and Amazon Music businesses before he left the company in 2014. Colin joined Amazon in 1998, as the Director for Amazon Associates and Amazon Web Services Programs. He also spent two years as Jeff Bezos’ technical advisor or “shadow,” and later served as the COO for IMDb.com.

Their stories illuminate Amazon’s culture of innovation and the origin stories of the Kindle, AWS, and Prime businesses. From granular details about the “working backwards” process, to an inside look at how players like Jeff Bezos and incoming CEO Andy Jassy operated up close, the lessons sharpen what “dive deep” and operational excellence look like in practice.

Several ideas have become mantras for my product management leadership practice: why innovation can’t be a part-time job, the perils of taking a “skills-forward” approach to exploring new opportunities, and why mechanisms are more important than good intentions. These principles reinforce the shift from outputs to outcomes and bring needed rigor to outcomes vs output OKRs.

At HighLevel, we apply a working-backwards mindset to product discovery: we start from the customer benefit, pressure-test the narrative with real users, and map success metrics before we write a line of code. This discipline accelerates product-market fit lessons, reduces thrash in product roadmapping and sprint planning, and clarifies trade-offs when timelines and resources are tight.

Mechanisms turn intent into results. For us, that means single-threaded ownership for critical bets, decision logs that preserve context, lightweight written narratives that force clear thinking, and weekly business reviews that highlight leading indicators. These habits create the tight feedback loops needed to dive deep, course-correct quickly, and scale operational excellence.

If you’re a founder, product creator, or operator scaling a SaaS platform, the throughline is simple: make innovation a full-time commitment, resist “skills-forward” biases when exploring new opportunities, and demand mechanisms that institutionalize good judgment. That’s how durable systems outlast any single leader.

Learn more about “Working Backwards” here.

Inspired by this post on First Round.

What is the 'Working Backwards' playbook and why is it relevant to product teams?

The post distills lessons from Bill Carr and Colin Bryar’s Working Backwards and shows how to apply them to product management leadership. It also highlights the origin stories behind Kindle, AWS, and Prime to illustrate these principles in action.

How does HighLevel apply the working-backwards mindset to product discovery?

At HighLevel, the approach starts from the customer benefit, pressure-tests the narrative with real users, and maps success metrics before coding. This discipline accelerates product-market fit and reduces thrash in roadmapping and sprint planning.

What are 'mechanisms' and why are they important?

Mechanisms turn intent into results. They include single-threaded ownership for critical bets, decision logs that preserve context, lightweight narratives, and weekly business reviews that highlight leading indicators.

What does 'outcomes vs output' mean in this post?

It emphasizes shifting from outputs to outcomes and applies ‘outcomes vs output’ OKRs to guide product decisions. It also cautions against ‘skills-forward’ biases and focuses on customer impact.

Who should read this post?

Founders, product creators, or operators scaling a SaaS platform. The message is to make innovation a full-time commitment and demand mechanisms that institutionalize good judgment.