AI coding tools democratize development, making simple 'coding' obsolete. However, this expands the amount of software created, which in turn increases the need for sophisticated 'engineering' to manage new layers of complexity and operations. The field gets bigger, not smaller.
The tech industry has the knowledge and capacity to build the data centers and power infrastructure AI requires. The primary bottleneck is regulatory red tape and the slow, difficult process of getting permits, which is a bureaucratic morass, not a technical or capital problem.
The current AI boom isn't a speculative demand bubble. Real companies are paying for and getting value from AI, creating a supply shortage, not an overhang. In the long term, the market's disruptive potential is actually undervalued.
When developers use AI to code, the AI agent itself selects the underlying infrastructure like databases. This shifts the purchasing decision from human developers and central IT teams to the AI, fundamentally disrupting how the multi-trillion dollar enterprise infrastructure market operates.
SaaS value lies in its encoded business processes, not its underlying code. AI's primary impact will be forcing SaaS companies to adopt natural language and conversational interfaces to meet new user expectations. The backend complexity remains essential and is not the point of disruption.
History shows that major technological shifts like the internet and AI require a fundamental re-architecting of everything from silicon and networking up to software. The industry repeatedly forgets this lesson, mistakenly declaring parts of the stack, like hardware, as commoditized right before the next wave hits.