The Build vs Buy Dilemma in the Age of AI and User Programming

In the tech industry, one age-old question has always loomed large: should you build or buy to solve a particular problem? This decision is crucial for both traditional IT and modern product teams. Each option comes with its own set of trade-offs-buying can be quicker but may lack customization, while building gives you control but at the cost of time and resources.

Core Competency vs. Non-Core Functions

For most companies, the rule of thumb is straightforward: if the problem falls within your core competency, build it. If it’s outside that scope, consider buying a solution. However, there are always exceptions. For instance, highly specialized problems often lack off-the-shelf solutions, forcing teams to roll up their sleeves and start from scratch.

The Evolution of User Programming

Historically, product teams had the luxury of building custom solutions, while other departments in the company typically did not. This led to a common scenario where "the business" would have an endless list of requests for IT, often bogging down development cycles.

This dynamic began to shift in 1979 with the invention of VisiCalc, the first spreadsheet program designed for personal computers like the Apple II. VisiCalc marked the beginning of user programming-enabling non-technical users to create their own solutions without deep coding knowledge. Today, millions of user-created programs (mostly formulas) run in Excel and similar tools across various industries.

Low-Code and No-Code Solutions

The trend continued with the release of Visual Basic in 1991, which was arguably the first low-code platform. This allowed even more non-technical users to create custom applications. Over the years, a wave of low-code and no-code tools emerged, further democratizing software development.

The Rise of Generative AI

Now, with the advent of generative AI, we are witnessing a new generation of user-programming tools that make it easier than ever for non-technical users to create complex applications. Tools like Lovable and Bolt use natural language as the programming interface, effectively turning English into a powerful coding language. This means nearly anyone with a problem to solve can now write code, even if they have no formal training in software development.

What’s Different This Time?

While the build vs buy decision has always existed, and non-technical users have had options, the key difference today is the skill set required. In the past, using these tools often required some level of technical knowledge, limiting their accessibility. Now, with natural language as the interface, the barrier to entry has been significantly lowered.

Implications for Product Teams

For product teams, this shift means a few things:

• Increased Agility: Non-technical team members can now create and iterate on solutions more quickly, reducing dependency on IT.
• Broader Innovation: Ideas from across the organization can be rapidly prototyped and tested, leading to more diverse and innovative solutions.
• Resource Allocation: Teams can focus their technical resources on core competencies while leveraging user-programming tools for non-core tasks.

Conclusion

The build vs buy dilemma is as relevant today as it has ever been. However, the rise of generative AI and user-programming tools is reshaping how we approach this decision. By lowering the barrier to entry for software development, these tools are empowering a wider range of users to create solutions, leading to more agile, innovative, and efficient product teams.