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.

Generative AI is a powerful tool for accelerating the production and refinement of creative work, but it cannot replace human taste or generate a truly compelling core idea. The most effective use of AI is as a partner to execute a pre-existing, human-driven concept, not as the source of the idea itself.

Generative AI is non-deterministic, sacrificing precision for creativity. PMs should leverage it to overcome the "blank canvas" problem in brainstorming (e.g., creating a draft value prop canvas) but never rely on it as a definitive source of truth where accuracy is critical.

A 'GenAI solves everything' mindset is flawed. High-latency models are unsuitable for real-time operational needs, like optimizing a warehouse worker's scanning path, which requires millisecond responses. The key is to apply the right tool—be it an optimizer, machine learning, or GenAI—to the specific business problem.

Dylan Field advises against viewing AI-generated outputs as finished work. Instead, leverage AI to explore divergent possibilities and create a wide range of options. The human designer's crucial role is to then select, mold, and refine these initial concepts with intention and craft.

The comparison reveals that different AI models excel at specific tasks. Opus 4.5 is a strong front-end designer, while Codex 5.1 might be better for back-end logic. The optimal workflow involves "model switching"—assigning the right AI to the right part of the development process.

Pega's CTO advises using the powerful reasoning of LLMs to design processes and marketing offers. However, at runtime, switch to faster, cheaper, and more consistent predictive models. This avoids the unpredictability, cost, and risk of calling expensive LLMs for every live customer interaction.

To optimize AI costs in development, use powerful, expensive models for creative and strategic tasks like architecture and research. Once a solid plan is established, delegate the step-by-step code execution to less powerful, more affordable models that excel at following instructions.

For creative work like design, AI's true value isn't just accelerating tasks. It's enabling designers to explore a much wider option space, test more possibilities, and apply more craft to the final choice. Since design is non-deterministic, AI serves creative exploration more than simple speed.