How to Succeed in Technology: The 10,000 Experiment Rule


In a world obsessed with mastery and success, the 10,000-hour rule has long been heralded as the golden standard for achieving expertise in any field. Popularized by Malcolm Gladwell in his book “Outliers,” this rule suggests that with 10,000 hours of dedicated practice, anyone can master a skill. However, in the fast-paced and ever-evolving landscape of technology, a new paradigm is emerging as a more effective blueprint for innovation and success: the 10,000-experiment rule.

Introduced by Michael Simmons in his thought-provoking article on Medium, “Forget The 10,000-Hour Rule; Edison, Bezos, & Zuckerberg Follow The 10,000-Experiment Rule,” this new rule shifts the focus from the quantity of time spent practicing to the number of experiments conducted. This approach champions experimentation, quick learning, and the ability to adapt and pivot as the cornerstones of technological innovation and personal growth. Through this lens, the stories of Thomas Edison’s relentless experimentation, Jeff Bezos’s innovative leadership at Amazon, and Mark Zuckerberg’s rapid iteration at Facebook take on new significance. They exemplify how embracing a culture of experimentation can lead to unprecedented achievements.

As we dive deeper into the essence of the 10,000-experiment rule, we will explore its foundations, its scientific backing, and its application across various domains of technology, with a special focus on robotics. By understanding and applying this rule, individuals and organizations alike can unlock new pathways to innovation and success in the technological realm.

The Evolution from Hours to Experiments

The traditional 10,000-hour rule, while a useful guideline for developing skill through practice, presents a linear approach to mastery that overlooks the complex, non-linear nature of innovation. In contrast, the 10,000-experiment rule represents a paradigm shift, focusing on the iterative process of trial, error, and learning. This approach is particularly resonant in the field of technology, where rapid advancements and unpredictable challenges require a more flexible and adaptive mindset.

In his 2018 CNBC interview, Bezos articulated the essence of this experimental approach:

To be innovative you have to experiment. If you want to have more inventions, you need to do more experiments per week per month per year per decade. It’s that simple. You cannot invent without experimenting. And here’s the other thing about experiments…lots of them fail. If you know it’s going to work in advance it is not an experiment.

Jeff Bezos

Also, keep in mind that when you experiment, you have to be prepared for many failures. Bezos mentions this in his 2016 Annual Letter to Shareholders:

To invent you have to experiment, and if you know in advance that it’s going to work, it’s not an experiment. Most large organizations embrace the idea of invention, but are not willing to suffer the string of failed experiments necessary to get there. Outsized returns often come from betting against conventional wisdom, and conventional wisdom is usually right. Given a ten percent chance of a 100 times payoff, you should take that bet every time. But you’re still going to be wrong nine times out of ten.

Jeff Bezos

Bezos’s emphasis on experimentation as a core strategy highlights the critical role that embracing failure and learning plays in driving innovation. Under his leadership, Amazon has become a prime example of how a culture of experimentation can lead to groundbreaking innovations, from AWS to Alexa.

Thomas Edison, often hailed as one of the greatest inventors in history, exemplifies the 10,000-experiment rule long before it was formally articulated. Edison’s approach to invention was fundamentally experimental, famously remarking, “I have not failed. I’ve just found 10,000 ways that won’t work.” His work on the electric light bulb, phonograph, and motion picture camera, among countless other inventions, showcases the power of persistence and the willingness to embrace failure as a stepping stone to success.

The shift from hours to experiments encourages a mindset of curiosity, resilience, and openness to failure. It suggests that success in technology and innovation is not merely a function of time spent, but rather the quality and quantity of experiments conducted. This approach fosters a culture of continuous learning and adaptation, essential qualities in the fast-evolving tech landscape.

By embracing the 10,000-experiment rule, individuals and organizations can unlock a more dynamic and effective pathway to innovation. This rule champions the idea that through a systematic approach to experimentation, one can navigate the complexities of technology and emerge with novel solutions and breakthroughs.

Scientific Backing: The Meta-Analysis of Deliberate Practice

The limitations of the 10,000-hour rule are further illuminated by a comprehensive meta-analysis on deliberate practice and performance across various domains, including music, games, sports, education, and professions. This study, which examined the effects of deliberate practice on performance, found that while practice is undoubtedly important, its overall contribution to performance varies significantly across disciplines.

In domains where performance is highly predictable and structured, such as classical music and chess, deliberate practice accounted for a substantial portion of variance in performance. However, in less structured and more dynamic fields, such as technology and entrepreneurship, the impact of deliberate practice was notably smaller:

“We found that deliberate practice explained 26% of the variance in performance for games, 21% for music, 18% for sports, 4% for education, and less than 1% for professions.

This finding suggests that while honing specific skills is important, the ability to innovate, adapt, and experiment plays a crucial role in achieving success in these fields.

The implications of this research underscore the value of the 10,000-experiment rule. In the realm of technology, where the landscape is characterized by rapid change and uncertainty, the capacity to learn from experiments—not just from repeated practice—is paramount. This approach aligns with the idea that success in technology hinges on the ability to navigate ambiguity, test hypotheses, and pivot based on feedback and outcomes.

Case Studies of Success Through Experimentation

The power of the 10,000-experiment rule is vividly illustrated in the stories of tech luminaries and companies that have placed experimentation at the heart of their success. These case studies not only demonstrate the rule’s effectiveness but also inspire a culture of innovation and resilience.

Thomas Edison: The Quintessential Experimenter

Thomas Edison’s work is perhaps the most iconic example of success through experimentation. Edison’s philosophy of “genius is one percent inspiration, ninety-nine percent perspiration” reflects his commitment to the iterative process of innovation. His development of the electric light bulb involved over a thousand experiments, a journey marked by setbacks, learning, and eventual triumph. Edison’s persistence and willingness to learn from each experiment laid the groundwork for modern electric lighting and numerous other technologies, embodying the essence of the 10,000-experiment rule.

Amazon: Cultivating an Experimentation Culture

Under Jeff Bezos’s leadership, Amazon has become synonymous with innovation, largely due to its embrace of experimentation. Amazon’s foray into cloud computing with AWS, its development of the Kindle, and its exploration of AI through Alexa are outcomes of its experimental culture. Bezos’s approach—viewing every failure as an opportunity to learn and every experiment as a step toward discovery—has propelled Amazon into new markets and technologies, illustrating the transformative power of the 10,000-experiment rule in corporate innovation.

Facebook: Rapid Iteration and Growth

Mark Zuckerberg’s Facebook has similarly leveraged the power of experimentation to evolve from a college networking site into a global social media platform. Facebook’s rapid iteration on features, constant A/B testing, and openness to pivoting based on user feedback have been instrumental in its growth and adaptability. This commitment to experimentation has enabled Facebook to stay relevant amidst changing social media landscapes and user preferences.

Applying the 10,000 Experiment Rule in Robotics

Robotics is a field that epitomizes the intersection of complex hardware, sophisticated software, and intricate real-world interactions. The 10,000-experiment rule finds a fertile ground in robotics, where practical, hands-on experimentation and iterative learning are key to innovation and breakthroughs. 

Using ROS 2 (Robot Operating System 2) significantly enhances the capacity for such experimentation, providing a unified and flexible framework for robotics development.

Iterative Design and Testing with ROS 2

The iterative design process in robotics is crucial for developing effective and efficient systems. ROS 2 facilitates this process by offering advanced tools for building and testing robotic applications. Its modular architecture allows roboticists to experiment with different configurations and functionalities easily, streamlining the process of learning from each iteration. By leveraging ROS 2’s capabilities, developers can quickly prototype ideas, test hypotheses, and refine their designs based on real-world feedback.

Simulation-Based Testing Enhanced by ROS 2

ROS 2 integrates seamlessly with powerful simulation tools, such as Gazebo and NVIDIA Isaac Sim, enabling developers to conduct thousands of simulated experiments efficiently. These simulations are invaluable for exploring the behavior of robotic systems under a wide range of conditions without the time and cost associated with physical prototypes. By utilizing ROS 2 in simulation-based testing, researchers can accelerate the experimentation process, rapidly iterating on design and software algorithms to identify promising approaches before real-world implementation.

Real-World Experimentation and ROS 2

When transitioning from simulation to real-world testing, ROS 2’s robustness and flexibility become even more beneficial. Its support for diverse hardware and real-time communication allows for extensive real-world experimentation, critical for refining robot designs and ensuring they can handle the complexities of their intended environments. ROS 2’s ecosystem encourages a collaborative approach to experimentation, where developers can share insights, tools, and best practices, further accelerating innovation in robotics.

Leveraging ROS 2 for the 10,000 Experiment Rule

ROS 2 is designed to support the rapid iteration and flexibility required by the 10,000-experiment rule. Its features enable roboticists to:

  • Prototype Quickly: Developers can use ROS 2 to build and test new ideas swiftly, reducing the time from concept to experimentation.
  • Analyze and Iterate: With ROS 2, it’s easier to collect and analyze data from experiments, facilitating a deeper understanding of each trial and informing subsequent iterations.
  • Collaborate and Share: The ROS 2 community encourages sharing of software, tools, and best practices, making it easier for roboticists to learn from each other’s experiments.

Practical Tips for Implementing the 10,000 Experiment Rule

Adopting the 10,000-experiment rule requires a strategic approach to experimentation. Here are some practical tips for individuals and organizations looking to embrace this mindset:

  • Document Everything: Keep detailed records of each experiment, including the hypothesis, methodology, results, and learnings. This documentation is invaluable for tracking progress and informing future experiments.
  • Embrace Failure: View each failed experiment as a learning opportunity. Analyzing why an experiment didn’t work is often more informative than a successful outcome.
  • Foster a Culture of Curiosity: Encourage team members to ask questions, propose experiments, and explore new ideas. A supportive environment that values curiosity and risk-taking is essential for innovation.
  • Leverage Technology: Utilize software and tools designed for managing experiments. These can help organize data, track progress, and analyze results, making the experimentation process more efficient and effective.


The 10,000-experiment rule offers a compelling framework for achieving success in technology and beyond. By shifting the focus from sheer hours of practice to the quality and quantity of experiments, individuals and organizations can foster a culture of innovation, resilience, and continuous learning. The stories of Edison, Bezos, Zuckerberg, and countless others in the field of technology underscore the transformative power of this approach. As we look to the future, embracing the mindset of experimentation will be key to navigating the complexities of technology and unlocking new realms of possibility. Let the journey of 10,000 experiments begin.

The Secret to Tech Startup Success: Speed and Simplicity


Winning technology companies become winners and remain winners by satisfying human desires with greater SPEED and/or SIMPLICITY than those who came before them. Those who keep that in mind will profit immensely. Those who lose sight of that will have problems.

If you are running a tech startup, remember that to win over the long haul, you must satisfy human desires with greater speed and/or simplicity than current market leaders. The easiest way to do that is to take a human desire…one that has been around for a long time…and make it more easily attainable by using technology to remove steps from what people are currently doing to satisfy that desire.

Entrepreneurs are professional step removers.

Bottom Line: Help people get what they want faster and/or more simply, and profit immensely.


In the realm of technology and innovation, Ev Williams, a co-founder of Twitter and Medium, has articulated a compelling formula for achieving wealth and success: eliminate unnecessary steps in everyday tasks. This principle of simplifying processes to their most efficient forms is not just a strategy but a philosophy that has propelled companies like Uber, Google, and Amazon to unprecedented heights of success and influence. These tech giants have mastered the art of providing unparalleled convenience and ease, essentially by adhering to two fundamental tenets: speed and cognitive ease. By understanding and harnessing the power of these elements, they’ve managed to tap into long-standing human desires, making them more accessible through modern technology.

This blog post aims to delve deep into the concept that Williams highlighted, exploring how the simplicity and speed in technology can serve as a golden ticket to startup success. By examining the trajectories of Uber, Google, and Amazon as illustrative examples, we will uncover the underlying principles that any tech startup can adopt to achieve similar success. Additionally, we will offer actionable insights and strategies for integrating these principles into the fabric of emerging technology ventures.

The Human Desire for Convenience

The quest for convenience is as old as humanity itself. From the invention of the wheel to the creation of the internet, each technological breakthrough has been driven by a desire to make life easier, more efficient, and more enjoyable.

In the pre-digital age, innovations were primarily focused on physical labor and time reduction. However, as we transitioned into the digital era, the focus shifted towards cognitive ease and speed of access.

This shift is rooted in our inherent desire for instant gratification—a trait that has been significantly amplified by the internet and mobile technology. Today, we live in a world where the expectation is not just for things to be easier, but for them to be instantaneously accessible. The success stories of tech giants like Uber, Google, and Amazon are a testament to this evolution. By identifying and eliminating friction points in everyday activities, these companies have not only satisfied but exceeded the modern consumer’s expectations for convenience.

The Philosophy of Simplification

Humans are wired to seek convenience and efficiency. This innate desire has been the driving force behind many technological advancements throughout history. In the digital age, this pursuit has taken on a new dimension, with simplicity and speed becoming paramount in product design and service delivery. The psychological underpinning of this trend is straightforward: the less effort the brain has to make to achieve a desired outcome, the more appealing that pathway becomes. Simplification, therefore, is not just a design principle but a strategic approach to capturing and retaining user interest and loyalty.

Case Studies


Uber transformed the transportation industry by removing the friction involved in hailing a taxi. By introducing a simple app that connects drivers with passengers, Uber made it possible to secure a ride with just a few taps on a smartphone. This convenience, coupled with transparent pricing and payment, epitomizes the power of removing unnecessary steps to meet a fundamental human need: getting from point A to B efficiently.


Google’s mission to organize the world’s information and make it universally accessible and useful is a testament to the power of simplicity. With a clean interface and a sophisticated algorithm, Google has made it incredibly easy for users to find information on the internet quickly. This focus on speed and ease of use has made Google the go-to search engine for billions of people worldwide.


Amazon has revolutionized the retail industry by making online shopping as easy and convenient as possible. From one-click purchases to same-day delivery options, Amazon has continually focused on reducing the barriers to online shopping, fulfilling the human desire for immediate gratification and hassle-free transactions.

Practical Steps for Startups

For startups looking to replicate the success of giants like Uber, Google, and Amazon, the key lies in identifying common activities or pain points that can be simplified. This involves a deep understanding of the target audience and a commitment to designing with the user experience in mind. Continuous improvement based on user feedback is also crucial, as it helps refine the product or service to better meet the needs of the market.

Challenges and Considerations

While simplicity and speed are powerful drivers of success, they are not without their challenges. Startups must carefully balance the quest for simplicity with the need to provide a comprehensive and functional product. Over-simplification can lead to a loss of valuable features or fail to meet users’ needs effectively.


The secret to tech startup success lies in understanding and applying the principle of removing unnecessary steps to make common activities faster and easier. By focusing on speed and simplicity, startups can create products and services that resonate deeply with users, fulfilling their desires in the most efficient way possible. As the tech landscape continues to evolve, the startups that prioritize the user’s ease and convenience will be the ones that stand out and succeed in the crowded marketplace.

How to Write a Business Plan for a Technology Project

Why Technology Projects Need Business Plans

Having worked with hundreds of early-stage companies as CFO of the first technology startup accelerator in Brazil, I’ve found that one of the most common reasons a business fails is because the founders build things that no one wants. 

A lot of this failure happens because founders — who often have engineering backgrounds — focus so heavily on the shiny, new technology they’ve developed that they overlook the fact that businesses exist to make money by satisfying human desires.

  • A restaurant makes money by satisfying people’s need to eat food. 
  • A software company makes money by satisfying people’s desire to get more things done in a shorter amount of time.
  • A real estate firm makes money by satisfying people’s desire for shelter.
  • A lemonade stand makes money by quenching people’s thirst.

Too many companies create solutions without properly identifying the problem. This happens all the time, especially in robotics.

Remember ASIMO, the cute humanoid robot that Honda spent decades developing? It’s a perfect example of engineers creating a solution without a problem. It wasn’t financially viable, and Honda ceased commercial development of it in 2018.


The market wants its problems solved, its needs met, and its desires satisfied. It doesn’t care about how much effort you put into building your technology, no matter how awesome it is. 

The best way to make money in the technology business is to take a human desire and use modern technology to make it faster and simpler to satisfy that desire. Start with the customer’s desire and work backwards to the technology.

Solve a big old problem with a unique solution.

Whether you plan to start a small robotics startup or you work for a Fortune 500 company as a machine learning engineer, it’s imperative that you keep the big picture in mind of why a business exists. You’re going to be spending countless hours working on some product, so make sure you:

  • Build things others want. 
  • Build something that has practical, real-world commercial value. 
  • Generate a return on your time and money. 

Life is too short to waste on projects that aren’t worthwhile. 

Millions of dollars and developer hours are wasted each year on products that should never have been built. In order to survive, a company has to make sure it uses its limited time and financial resources efficiently and intelligently. This is especially true in startups where money and time are so often scarce.

Before you begin investing your time and money on developing a product, take a day or two to write up a business plan. As I’ll show you below, it doesn’t need to be anything elaborate. You can put everything on just a single page. 

For example, Sequoia Capital, the early investors of companies such as Apple, Google, LinkedIn, and WhatsApp, has a one-page business plan template that they recommend to founders interested in pitching them for millions of dollars in funding.

Below is the 12-point business plan template I recommend you fill in before you write the first line of code for your next project. Make sure you spend a lot of time on the two most important slides: the problem and the solution. If you get these two slides right, everything else will take care of itself.

Sample Business Plan: Autonomous Strawberry-Picking Robot


1. Purpose 

We developed [product] that makes it easier and faster for [target market] to [human desire…preferably one that has been around for a long time].


  • We developed a self-driving strawberry-picking robot that makes it easier and faster for California strawberry farmers to harvest strawberries.

2. Problem 

  • Describe the pain of the customer. 
  • How does the customer address this issue today?


  • California farmers have been unable to find enough workers to harvest their fruits and vegetables, resulting in millions of dollars’ worth of produce rotting in the fields. 
  • Farmers have hired recruiters, raised wages, increased mechanization, and adjusted cultivation practices, yet they still face millions of dollars in crop losses each year (Source: California Farm Bureau Federation).

This video below shows several interviews with farmers who are having trouble finding workers to pick strawberries.

3. Solution 

What is the solution, and how does it make it easier and faster to satisfy the customer’s desire?


  • We developed an autonomous strawberry-picking robot for farmers that is 8x more efficient than humans and can work 24 hours a day, 7 days a week.

4. Product Demo 

  • How does the product work? 
  • Provide use cases.


  • Using the latest advances in computer vision and deep learning technology, the self-driving robot can pick strawberries without bruising them and detect ripeness better than humans.
  • Farmer Joe lost 60% of his crop last year because he was unable to find enough workers. Using the strawberry-picking robot, he can harvest his crop 24/7, while requiring up to 70% fewer seasonal workers.

5. Why Now 

What recent trend makes this product feasible?


  • Computer vision and computer processing power have matured to the point where an autonomous strawberry detection and picking system is feasible.

6. Market Size 

Who does the product cater to, and how big is that market?


7. Competition and Alternatives 

  • Who is the competition?
  • What are the alternatives to using your product?


  • ABC and XYZ are companies that are in this space.
  • Farmers have tried a number of tactics, such as hiring recruiters, raising wages, increasing mechanization, and adjusting cultivation practices.

8. Competitive Advantage 

What about your solution can’t be easily copied or bought?


  • It’s hard to find someone with more integrated knowledge of both robotics and entrepreneurship to lead the design, development, and deployment of a financially viable robotics product.
  • Existing customers and switching costs.

9. Business Model

  • How will you make money? 
  • Do you have any traction?


  • Subscription (i.e. robotics-as-a-service (RaaS))
  • 15 existing customers, each paying a monthly fee of $2,000.

10. Marketing Plan

How will you acquire new customers?


  • Trade shows
  • Door-to-door sales

11. Team

Who are you, and what are your qualifications?


  • Addison Sears-Collins: A roboticist with over 15 years of experience across a range of industries who has founded several successful technology startups.

12. Financials and Use of Funds

What are your financial projections?


  • Present Value of Cash Inflow = $20M
  • Present Value of Cash Outflow = $5M
  • Net Present Value = US$15M
  • Return of Investment = 300%
  • We will use the funds to hire robotics developers and researchers.

Remember Why You’re Doing What You’re Doing

Being able to clearly articulate why a particular product could contribute to business success is a rare skill among engineers. Having that entrepreneurial mindset will almost certainly separate you from the pack.