Gaurav Sagar - Technical Building Blocks: A Technology Reference for Real-world Product Development

This Apress imprint is published by the registered company APress Media, LLC, part of Springer Nature.

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Software products are all around us, and some are so widely successful that we even use their names as verbs, like Google for searching on the Internet, Uber for getting a taxi, and Venmo for transferring money. Software as a Service (SaaS) and cloud computing have completely revolutionized how quickly products and new features in them can be brought to market. Due to the widespread success of so many software products, there is a huge demand not only for software engineers but also for professionals in these product development teams who act as a liaison between the stakeholders, the various cross-functional teams, the customers, and the leadership teams. These professionals are usually in the roles of product manager, program manager, or project manager and require some technical knowledge to be effective at various aspects of their jobs such as defining the customer needs for a technical product, ideating a feature to solve a customer pain point, evaluating the technical feasibility of their proposal, reviewing the long-term and short-term risks from using a particular technology for product development, providing updates to the stakeholders and leadership teams on technical blockers, etc.

Being technical is quickly becoming a critical trait for people in these roles, and companies are adding in technical interviews to filter out candidates who dont have these skills. However, technology evolves fast and can seem overwhelming to people looking to explore these roles. One needs to learn so many things starting with the tools and techniques used to develop software, different experimental design techniques, technologies to instrument and measure success, artificial intelligence algorithms to build features like personalized recommendations, etc., and the list goes on. Some try to self-learn by first trying to learn a programming language and then reading upon system design across various articles on the Internet or buying books on various technical subjects but achieve limited success. The problem is that the Internet is full of inaccurate and shallow information and the books picked on individual topics are meant to develop subject matter expertise and are too detailed, each coming up with its own prerequisites and time commitments.

How does one get technical enough for these roles then?

This book is designed for professionals who are working as product manager, program manager, project manager, business analysts, etc., in product development teams and feel that having more technical understanding will help them be more effective at work and grow faster in their careers. It is also useful for people looking to transition to one of these roles and want to gain the required technical knowledge to pass those dreaded technical interview rounds.

There are seven chapters in this book that explain the various technologies and tools used by the various teams to develop products. While each chapter is self-contained and you can start with any of them, we feel going through the chapters in order will help you absorb the book material more effectively.

There is some code listed in a few chapters, and you can do without running it; however, read it at least as plain English. The goal is to just get you accustomed to what you might hear and see from your engineering teams. We dont expect you to know any programming language, nor will we teach you one as its not required to become technical in these roles.

To aid you, the code is present in IPython notebooks, which you can download from the books source code repository located at github.com/apress/technical-building-blocks and upload them to Google Colab at https://colab.research.google.com/notebooks/ . From there, simply execute the code blocks right from your browser for free. We recommend this approach as it will save you from having to set up the environment on your local machine and not have to worry about dependencies. Since we build these code examples on Google Colab, they will work there without any issue.