Unlike traditional software development, AI-native founders avoid long-term, deterministic roadmaps. They recognize that AI capabilities change so rapidly that the most effective strategy is to maximize what's possible *now* with fast iteration cycles, rather than planning for a speculative future.

The unpredictable, rapid evolution of foundation models makes traditional roadmaps obsolete. AI companies like Legora embrace this by operating on a near-daily planning cycle, allowing them to immediately pivot and capitalize on new model capabilities.

The idea of setting a yearly vision is outdated when new, compelling prototypes can be generated weekly. At Shopify, strategy now emerges organically as a powerful prototype gets shared, generates excitement, and a team forms around it, shifting priorities in near real-time.

In the fast-evolving AI space, detailed long-term roadmaps are a "waste of time." Cursor opts for a flexible approach guided by a high-level "fuzzy direction" rather than a rigid plan. This allows them to adapt to new models and user behaviors quickly.

In the fast-moving AI sector, quarterly planning is obsolete. Leaders should adopt a weekly reassessment cadence and define "boundaries for experimentation" rather than rigid goals. This fosters unexpected discoveries that are essential for staying ahead of competitors who can leapfrog you in weeks.

Jack Dorsey argues that rigid, pre-planned roadmaps are obsolete. In an AI-driven model, the product roadmap should be generated in real-time based on customer queries and needs, allowing the company to build and compose features on demand.

With AI accelerating development from months to days, PMs must focus on unblocking engineers and launching weekly. This supersedes traditional emphasis on long-term, cross-team roadmap alignment, which was crucial when code was more expensive to produce.

In a rapidly evolving field like AI, long-term planning is futile as "what you knew three months ago isn't true right now." Maintain agility by focusing on short-term, customer-driven milestones and avoid roadmaps that extend beyond a single quarter.

The rapid pace of change in AI renders long-term strategic planning ineffective. With foundational technology shifts occurring quarterly, companies must adopt a fluid approach. Strategy should focus on core principles and institutional memory, while remaining flexible enough to integrate new tech and iterate on tactics constantly.