Due to the rapid pace of AI-driven development, Ramp has abandoned annual or multi-year planning. They now operate on a three-month horizon, which is considered a long time because it allows them to accomplish what previously took three years, making long-term roadmaps obsolete.

Committing to a quarterly roadmap is futile when the AI landscape and customer needs change daily. Instead of detailed feature plans, leaders should set broad strategic objectives and focus on short-term, validated learning cycles. This approach builds a foundation that can adapt to rapid market shifts.

In an era where AI capabilities improve 20-30% monthly, Snowflake's CEO argues long-term plans are futile. Instead, he advises leaders to maintain a "childlike" discovery mindset, treating new model releases like real-time traffic data that can instantly render previous routes—and strategic plans—obsolete.

The rapid pace of technological change requires a new strategic planning cadence. Upwork's CEO has shortened planning cycles, arguing that if you're executing the same plan in month 11 as in month 1, "something's probably wrong." The new model is to set big goals but only plan one step at a time.

The speed of AI-driven change, which outpaces human comprehension, makes traditional long-term planning impossible. Axios CEO Jim VandeHei notes that even six-month plans are fantasy; leaders must now focus on what they can be highly confident about in the next 6-7 weeks.

The pace of change in AI has been so rapid that any business plan or set of assumptions established before mid-2023 is likely invalid. Founders must re-evaluate their entire strategy, from tech stack and team composition to funding needs, or risk being 'dead on arrival.'

The current pace of AI development is not just accelerating progress, it's a time compression event. Innovations previously projected for the 2030s and 2040s are being realized now, fundamentally shortening strategic planning horizons and forcing companies to adapt at an unprecedented speed.

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.

While the current AI era shares similarities with the birth of the internet, the key difference is the sheer velocity of change. During the dot-com era, companies had more time to adapt. Today, the acceleration is so intense that companies that wait on the sidelines risk becoming obsolete.