Adopting First Principles in Artificial Intelligence

Founder's Series

The Secret

As secrets go, we also have one. However, we have decided to make it an open secret. So, let’s just spill the beans. At Whirldata Inc, we have been able to successfully digitize many business processes through Artificial Intelligence (AI) because we undertake all metamorphosis processes through First Principles. Identifying the root cause of the problems and working from ground zero rather than going after analogies is our big secret.

What are First Principles?

First Principles is the strategy of approaching complex problems by breaking them into the simplest fundamental concepts through logical reasoning to find out the best possible solutions taking completely new directions. They arise out of psychological thought processes by continuously questioning a problem with ‘Why?’ till the basic truths land. In layman’s terms, a First Principle can be arrived by questioning each and everything in a concept till there are just facts that can’t be deduced any further. It’s like disassembling a computer until we are left with just resistors, transistors and other simple components with which we can manufacture different products like printers, cameras, etc.

Roots of First Principles:


First Principles have been in existence for hundreds of years right from the time of philosopher Aristotle who gave them their first definition. According to Aristotelous Phusike Akroasis 184a, “In every systematic inquiry (methodos) where there are First Principles or causes or elements, knowledge and science result from acquiring knowledge of these, for we think we know something just in case we acquire knowledge of the primary causes, the primary first principles, all the way to the elements. It is clear, then, that in the science of nature as elsewhere, we should try first to determine questions about the first principles.”


In the 20th century, renowned physicist Albert Einstein had his own idea about First Principle. He said, “If I had an hour to solve a problem and my life depended on the solution, I would spend the first 55 minutes determining the proper questions to ask, for once I know the proper questions, I could solve the problem in less than five minutes.”

Albert Einstein:

Competence revolves around choosing the right tool sets and platforms. Competence can make or break MVP deadlines. The problem with many startups is that they usually choose platforms with a long-term vision which, in several cases, make the learning curve steeper and implementation times exponentially higher. In some cases, some of the learnt skill sets won’t even be implemented in the project. While long-term vision is an absolute must for products’ features and applications in the later stages, most successful MVPs are just the ones that are not fully deployable enterprise solutions. You need to choose technology tool sets which, in most cases, will directly affect the other three ‘C’s. This is because, when the aspects to learn increases, it will consume time, which affects capability. The push for increasing workforce affects capacity and, finally, the increase the burden affects creativity.

How to adopt First Principles in AI

– The first and foremost step is identifying the objective. In a project, it’s the main problem statement which needs to be addressed.

– This should be followed by listing all the obstacles and challenges for the objective’s implementation. It can be skill sets, strength of workforce, proximity of the problem, software resources, time frame, competition, etc.

– Then, all the obstacles should be questioned critically and continuously as to why they arose in the first place in the implementation of the project. The best examples are the following questions:

Why skill sets are lacking?

Why workforce strength is less?

– Later, from these questions, the First Principles need to be extracted. They are the most fundamental truths / assumptions / propositions which can’t be deduced any further.

– First Principles will, then, open up new possibilities for finding solutions. Now, follow-up questions should be built on them so that the process takes a new and best possible direction. These questions and answers will help find undiscovered aspects of the core problem.

– Finally, from the follow-up questions, the best possible solution should be chosen and worked upon for solving the actual problem in the most efficient manner.

First Principles vs analogies:

Time and again, businesses, especially startups in AI, have relied on the paths already taken or by following already-established models. This is because it’s easier to reason by analogy. Just bringing out different iterations of an existing system has always been the first option for many businesses. But, hardly they believe that First Principles can bring about a different model altogether that’s unique. As First Principles are the physics of reasoning from the most fundamental concepts of a system, they require more mental energy. But, the results are always more sure-footed. First Principles give authority over the products that are developed as they have been built from the most fundamental truths and facts. Also, they enable creative and out-of-the-box thinking because of better understanding.

Advantages of First Principles:

Usually, there might be many ways of solving a complex problem or improvise an existing system or a business process. But, not all ways are cost effective and it will be imperative to find the best possible solution, especially if the project is undertaken by a startup. That is when First Principles come into play. While many business processes require manpower for full-fledged functioning, especially medical field, AI is slowly making a progressive change towards automation. Still, finding the right solution is always a tough task at hand.

But, with the use of First Principles, the most efficient solution is possible. Timely decision making is a key to success in almost all businesses. It even has the capability to make or break firms especially startups. Most entrepreneurs struggle with decision making and that is when First Principles come handy. They break the complexity of the problem and help establish the first step for a productive solution.

One of the biggest challenges in businesses is the extent and time of demand especially in specific geographic locations as it’s a continuously varying parameter. But, analysis of sale data in the region through First Principles approach can solve the problem. In fact, it can also help firms prevent losses and find out the root cause of the problems. As said earlier, First Principles have turned out to be deal breakers in a wide range of fields, automating business processes by following models.

They can help streamline businesses and work towards optimizing outputs. Transforming ideas into Minimum Viable Products (MVPs) can be achieved in a best possible and efficient manner using First Principles. By deducing the problem into its most fundamental principles, we can go about finding the best solution through the easiest and cost effective way. Case in point is Whirldata Inc’s recent project where the need was to build an MVP to offer perimeter and commercial building security for a bay area startup. An independent execution was done based on concepts to meet MVP goals with the First Principle. Being cost effective, from idea to execution, First Principle is a must for startups.


“Nothing in this universe is perfect,” said renowned scientist Stephen Hawking and that’s applicable even for First Principles. The biggest drawback in First Principles is that while questioning a system till establishing its fundamental concepts, at times, form is given more importance than function or vice versa, leading to a plethora of new options getting prevented from coming to light. But, nevertheless, if properly brainstormed, this challenge can be easily triumphed over.

If our secret can help the world get to the basics of every problem and solve it with precision, then we will be elated, secretly.