Given current locked-down, imperfect enterprise AI, a key differentiator is 'creative solutioning.' This means persistently pushing against tool limitations and governance to find transformative workarounds, rather than giving up when a tool says something isn't possible.

When building consumer AI applications, founders shouldn't be constrained by today's models. The advice is to anticipate rapid model improvement and design products for capabilities that will exist in the near future, a strategy described as "skating to where the puck is going."

In a rapidly changing AI landscape, don't wait to build. Instead, use this litmus test: if a more intelligent future model would make your project better, build it. If a smarter model would render your project obsolete (e.g., a complex rules-based automation), your approach is too fragile and should be rethought.

The conventional wisdom of 'focus on less to achieve more' is inverted by AI. With powerful new tools, the strategic advantage lies in taking on more ambitious projects and exploring ideas that were previously infeasible. AI shaves down the learning curve, making it possible to tackle a wider range of challenges.

A typical human behavior is to abandon a tool after one bad experience. With AI, this is a mistake. The technology's progress is so rapid that a feature that was ineffective months ago may now be incredibly powerful. To capitalize on AI, you must plan for its future capabilities, not its current limitations.

When developing AI-powered tools, don't be constrained by current model limitations. Given the exponential improvement curve, design your product for the capabilities you anticipate models will have in six months. This ensures your product is perfectly timed to shine when the underlying tech catches up.

In the rapidly advancing field of AI, building products around current model limitations is a losing strategy. The most successful AI startups anticipate the trajectory of model improvements, creating experiences that seem 80% complete today but become magical once future models unlock their full potential.

AI is evolving so rapidly that building for today's limitations is a mistake. Leaders should anticipate the state of the technology six months in the future and design products for that world. This prevents being quickly outdated by the pace of innovation.

The innovation team operates on two principles. First, they identify and close the gap between what current AI models can do and how people actually use them. Second, they imagine what models will be good at in six months and start building the products for that future state today.