True commoditization of software is near…

 

Generative AI: Where Are We Going With This?

Over the last couple of years, we’ve witnessed an exponential rise in AI adoption. Harnessing the power of AI, particularly generative AI, no longer requires a steep learning curve, at least in terms of getting started. As a result, we’re seeing AI assistants permeate nearly every facet of our daily lives, and the tools and platforms emerging in this space are shaping a future of software engineering that looks drastically different from what we know today.

It’s becoming increasingly clear that the nature of employment for software engineers will evolve significantly. With the rise of generative AI, I believe the industry at large may reduce its workforce, favoring a more gig-based model for many roles. Why? Because automation and AI-driven tooling can handle tasks that once demanded larger development teams.

Consider how modern construction projects rely on heavy machinery and automation to accomplish tasks that once required large crews. We’re now seeing similar trends in large software enterprises, where AI tools can expedite coding, testing, and deployment processes, effectively reducing the number of people needed. In response, enterprises will likely shift their investments toward quality and compliance in the software development lifecycle, ensuring that rapid, AI-assisted development still meets high standards and regulatory requirements.

On the flip side, smaller software enterprises (akin to custom home builders in the construction world) may flourish. These niche shops often consisting of one or two people can leverage AI assistants to build specialized solutions for small to mid-sized businesses. With minimal overhead, these “boutique” outfits can provide highly customized services, filling the gap for organizations that don’t need the scale or cost of a large enterprise partner.

As AI assistants mature, I expect we’ll see a DIY movement among small and medium businesses. With increasingly user-friendly AI agents, these companies may no longer need to outsource everything. Instead, they’ll adopt self-service tools effectively “constructing” smaller software projects in-house. With the diverse needs of these DIY users being met by marketplaces of specialized “AI agents” hosted by generative AI vendors.

The true commoditization of software seems imminent as generative AI technology continues to advance. Large enterprises will refine their focus on quality and compliance, smaller boutique firms will customize solutions, and a growing DIY community may handle simpler projects independently. In this new landscape, software engineering could indeed parallel the construction industry using “machinery” (AI Agents) to accomplish more with fewer people, all while spurring a rise in nimble, specialized outfits ready to meet unique market demands.

Regardless of how it unfolds, there’s no denying that the software engineering world is on the cusp of significant transformation. Embracing these changes and recognizing the opportunities they bring will be crucial for engineers, businesses, and entire industries alike.