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 traditional cadence of one major strategic bet per quarter is becoming obsolete. By leveraging AI for faster prototyping and feedback, product organizations can dramatically increase their innovation velocity, aiming for a new "big bet" every month or even every week.

In the fast-moving AI sector, quarterly planning is obsolete.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.

While Linear typically prioritizes quality over speed, Karri Saarinen acknowledges that in rapidly changing markets like AI, speed is more critical. Because the problems and workflows are unknown, shipping faster is necessary to get market feedback, find problems, and identify opportunities before the landscape solidifies.

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.

In the fast-moving AI era, Notion maintains a conservative financial plan to monitor its "running speed." However, formal product roadmaps are abandoned because technology and market shifts happen week-to-week, requiring a more fluid, improvisational approach to development.

Traditional roadmapping is too slow for the pace of AI development. Anthropic's team uses a "Just-in-Time" planning model: a simple spreadsheet outlining priorities for the next month, with a quick check-in each week to ensure it's still relevant. This prioritizes adaptability over long-term prediction.