Gergely Orosz: The Real Scarcity in the Next Two Years Will Be AI Developers with UX Judgment
Software engineering author Gergely Orosz predicts that in the next 12 to 24 months, there will be a shortage of developers and product engineers with strong user experience (UX) skills. These individuals not only use AI tools to enhance efficiency but, more importantly, are able to create "intuitive, smooth, and natural" application experiences, differentiating themselves from products that solely rely on AI-generated code.
He further points out that the current M&A market has begun to pay premiums for companies with "small teams + high-quality experiences." These teams are usually very small but have high product completion and significantly better user experiences than their competitors. Discussions among relevant English developer communities and investors also confirm this trend, believing that while AI lowers the barriers to development, it simultaneously raises the value of "experience design and product judgment."
This assessment aligns with recent observations from several tech media outlets: as AI-generated coding capabilities rapidly become widespread, the ability to "create" is no longer scarce, and the focus has shifted to "how well it works" as the new core of competition, with product differentiation returning to human judgment and design capabilities.
Source: Public Information
ABAB AI Insight
AI is compressing the gap in "production capability" but cannot simultaneously replicate "judgment capability." Code generation and functionality realization are gradually becoming commoditized, leading to rapid supply-side expansion, while the demand-side attention and usage time have not increased correspondingly. This will shift competition from "who can do it" to "who is used," with the core variable determining usage being experience quality.
UX capability is essentially a cross-dimensional integration ability: understanding user behavior, anticipating usage paths, and balancing complexity with intuitiveness. Such abilities are difficult to train directly through data and hard to standardize and replicate, thus becoming scarcer in the AI era. In other words, AI has lowered the technical barriers but amplified the returns on product judgment.
The premium in the M&A market for "small teams + strong experiences" reflects a revaluation of "product completion" by capital. As development costs decrease and time becomes the main scarce resource, acquiring a well-polished product with user stickiness is more certain than building from scratch. This change will drive entrepreneurial models from "expand first, optimize later" to "refine first, scale later."
On a deeper level, this is a typical signal of a technological cycle moving from "infrastructure-driven" to the "application differentiation stage." Early competition revolved around models, computing power, and data, and as these capabilities gradually spill over, value begins to migrate to the interface and interaction layers. Ultimately, the party that controls user entry points may not necessarily be the one with the strongest technology, but rather the one that understands how to make users "willing to use and continue using."