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The team avoids traditional product roadmaps, which they find awkward and difficult. They focus on concrete 8-week sprints for immediate goals and a high-level "vibe" for their long-term vision. The medium-term is considered too unpredictable to plan effectively.
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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.
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.
In the fast-moving AI space, rigid long-term planning is futile. Lovable uses a flexible six-month product roadmap, while ElevenLabs uses quarterly initiatives for alignment but gives its foundational research teams total freedom from timelines to foster innovation.
In the fast-moving AI space, long-term roadmaps are obsolete. Anthropic uses lightweight monthly planning for execution and creates 3-6 month vision prototypes—not static decks—to provide directional alignment without creating a rigid plan that will quickly become outdated.
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.
Avoid overly detailed, multi-year roadmaps. Instead, define broad strategic 'horizons.' The shift from one horizon to the next isn't time-based but is triggered by achieving specific metrics like ARR or customer count. This allows for an agile response to market opportunities while maintaining strategic focus.
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.
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.
Most product orgs focus on the 6-12 month medium term, which is the hardest to predict and control. Shopify's design teams are pushed to ignore this messy middle and focus only on the very long-term North Star and the very short-term actions they can take today, creating a more effective planning process.
