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.

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.

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.

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 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.

For the first time, engineering cycles, supercharged by AI, are outpacing marketing and sales. The old model of quarterly product updates is obsolete. Go-to-market teams now need a rapid, weekly cadence of demos and updates to stay aligned with the product's actual capabilities.

In the fast-moving AI sector, quarterly planning is obsolete.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

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.

When AI drastically increases engineering efficiency, the critical challenge is no longer shipping speed. The focus must shift to high-quality strategic planning and outcome-driven decision-making to ensure the abundant engineering resources are building the right products.