AWS Engineer Maps Programming's Uncertain Future Amid AI Disruption

Marc Brooker, an engineer at Amazon Web Services working on databases and serverless technologies, has published a provocative analysis of artificial intelligence's impact on programming careers. Drawing from his experience building core AWS services like EC2 and EBS, Brooker contends that generative AI has driven the cost of "turning written business logic into code" and "integrating services and libraries" down to near-zero. However, he emphasizes that constructing reliable, secure, and efficient systems remains stubbornly complex and expensive—a reality that will bifurcate tech careers into divergent evolutionary paths.

Brooker frames the current moment as a historical inflection point comparable to the transition from analog to digital electronics. He recounts an anecdote about a 1960s engineer who bet against digital circuits, illustrating how technological shifts create both winners and losers. "Statistically, measured by the ratio of transistors in digital and analog circuits in 2026, it’s unlikely anybody has ever been more wrong," Brooker notes, highlighting the magnitude of such transformations.

The first path Brooker describes involves treating programming as a diminishing craft, akin to traditional trades like weaving or coopering. While acknowledging the emotional weight of this transition—"You’re not wrong to feel a deep sense of loss. I feel it too"—he suggests economic opportunities will persist for specialists maintaining legacy systems or pursuing programming as an artisanal skill. This path requires intentionality: "Those that succeed will increasingly be those that acknowledge what they’re doing, and why they’re doing it."

The second path embraces AI as an unprecedented toolset for innovation. Brooker predicts decades of opportunity in applying AI to previously unsolvable problems, building companies that outcompete incumbents, and solving emergent challenges created by the technology itself. He invokes Amdahl's Law to illustrate why systemic complexity remains a bottleneck: "A massive speed up on a portion of the problem becomes less and less of a contributor to the overall speedup as that portion accelerates."

Crucially, Brooker argues that while AI handles translation and simple synthesis, transformative ideas retain immense value. "As the lever gets longer, new ideas become more valuable," he writes, suggesting that conceptual innovation will drive disproportionate returns. Despite uncertainties, he remains bullish: "The second act will be more economically valuable and mentally stimulating than we can imagine."

Brooker's analysis avoids hype, instead grounding predictions in historical precedent and engineering principles. His perspective carries weight given his role at AWS (@MarcJBrooker on Twitter, @marcbrooker on Mastodon), where he observes firsthand how enterprises wrestle with system complexity. The full essay—part of his ongoing technical commentary—is available on his personal blog.

For engineers navigating this transition, Brooker offers no easy answers but frames the dilemma with pragmatic clarity: Whether preserving a craft or pioneering new frontiers, success requires acknowledging that "the cost of building efficient, reliable, secure, end-to-end systems is starting to drop, but slowly." This friction point, he suggests, is where lasting value will be created.