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."

When building at the frontier of AI, it's a valid strategy to ship imperfect, "vibe-coded" features. This approach assumes that rapid, near-future model improvements will clean up imperfections, making it better to launch an imperfect product now rather than wait for perfect model performance that is just around the corner.

The rapid pace of technological change, especially in AI, renders multi-year design visions useless. Instead of creating detailed decks, design leaders should focus on building simple prototypes that point the team in the right direction for the next 3-6 months.

To create a breakthrough AI product, design its capabilities around the projected power of models six months out. This means accepting poor initial performance, but ensures you'll be perfectly positioned when more capable models are released.

The "bitter lesson" of AI applies to product development: complex scaffolding built around model limitations (like early vector stores or agent frameworks) will inevitably become obsolete as the models themselves get smarter and absorb those functions. Don't over-engineer solutions that a future model will solve natively.

In the age of AI, perfection is the enemy of progress. Because foundation models improve so rapidly, it is a strategic mistake to spend months optimizing a feature from 80% to 95% effectiveness. The next model release will likely provide a greater leap in performance, making that optimization effort obsolete.

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.