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.

To balance AI hype with reality, leaders should create two distinct teams. One focuses on generating measurable ROI this quarter using current AI capabilities. A separate "tiger team" incubates high-risk, experimental projects that operate at startup speed to prevent long-term disruption.

A dual-track launch strategy is most effective. Ship small, useful improvements on a weekly cadence to demonstrate momentum and reliability. For major, innovative features that represent a step-change, consolidate them into a single, high-impact 'noisy' launch to capture maximum attention.

The rapid pace of AI makes traditional, static marketing playbooks obsolete. Leaders should instead foster a culture of agile testing and iteration. This requires shifting budget from a 70-20-10 model (core-emerging-experimental) to something like 60-20-20 to fund a higher velocity of experimentation.

CEO Mary Barra has transformed GM's strategic planning from a rigid annual event into a more frequent and fluid process. This shift allows the senior leadership team to react quickly to new market data and technological learnings, preventing 'momentum' from pushing a program forward when a pivot is needed, a critical capability in the volatile auto market.

Unlike traditional software where PMF is a stable milestone, in the rapidly evolving AI space, it's a "treadmill." Customer expectations and technological capabilities shift weekly, forcing even nine-figure revenue companies to constantly re-validate and recapture their market fit to survive.

OpenAI operates with a "truly bottoms-up" structure because it's impossible to create rigid long-term plans when model capabilities are advancing unpredictably. They aim fuzzily at a 1-year+ horizon but rely on empirical, rapid experimentation for short-term product development, embracing the uncertainty.

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.

To prevent rigid plans that break, maintain consistency in your high-level strategic pillars for the year. However, build in flexibility by allowing the specific tactics used to achieve those pillars to change quarterly based on performance and new learnings.