AI won't replace designers because it lacks taste and subjective opinion. Instead, as AI gets better at generating highly opinionated (though not perfect) designs, it will serve as a powerful exploration tool. This plants more flags in the option space, allowing human designers to react, curate, and push the most promising directions further, amplifying their strategic role.

As AI makes it easy to generate 'good enough' software, a functional product is no longer a moat. The new advantage is creating an experience so delightful that users prefer it over a custom-built alternative. This makes design the primary driver of value, setting premium software apart from the infinitely generated.

In the fast-evolving world of AI, the most valuable trait in a designer is a deep-seated curiosity and the self-direction to learn and build independently. A designer who has explored, built, and formed opinions on new AI products is more valuable than one with only a perfect aesthetic.

With AI agents automating raw code generation, an engineer's role is evolving beyond pure implementation. To stay valuable, engineers must now cultivate a deep understanding of business context and product taste to know *what* to build and *why*, not just *how*.

Dylan Field predicts that AI tools will blur the lines between design, engineering, and product management. Instead of siloed functions, teams will consist of 'product builders' who can contribute across domains but maintain a deep craft in one area. Design becomes even more critical in this new world.

AI and cataloging tools have compressed the competitive research phase from days to minutes. This frees designers from tactical UI comparison and empowers them to focus on higher-level strategic work: crafting product narrative and system architecture, a role previously reserved for senior leadership.

AI tools are collapsing the traditional moats around design, engineering, and product. As PMs and engineers gain design capabilities, designers must reciprocate by learning to code and, more importantly, taking on strategic business responsibilities to maintain their value and influence.

Technical implementation is becoming easier with AI. The critical, and now more valuable, skill is the ability to deeply understand customer needs, communicate effectively, and guide a product to market fit. The focus is shifting from "how to build it" to "what to build and why."

As AI makes it incredibly easy to build products, the market will be flooded with options. The critical, differentiating skill will no longer be technical execution but human judgment: deciding *what* should exist, which features matter, and the right distribution strategy. Synthesizing these elements is where future value lies.