AI doesn't replace creative experts; it elevates their role. Their craft shifts from manually creating individual assets to designing and building robust, reusable AI systems that empower the entire organization to generate on-brand content.
Instead of iterating on prompts for single assets, focus on building reusable systems. This approach ensures brand consistency, saves time, and empowers non-designers to create on-brand assets efficiently by turning complex workflows into simple interfaces.
Today, most AI use is siloed, with individuals prompting alone. The real value is unlocked when AI becomes a team sport, with specialists building systems that are shared, iterated upon, and used collaboratively across the entire organization.
Instead of chasing the latest hyped AI model, focus on building modular, system-based workflows. This allows you to easily plug in new, better models as they are released, instantly upgrading your capabilities without having to start over.
A specialist can build a complex, multi-step AI workflow and then expose only key inputs to the team. This turns their expertise into a scalable, self-serve "app" for marketers, enabling on-demand, on-brand creative generation without direct designer involvement.
A new model for creative services is emerging where solo entrepreneurs invest months building proprietary AI systems. They then sell high-value project packages that can be delivered almost instantly, creating immense leverage and scalability.
Weavey's AI tool go-to-market strategy ignored the mass market to focus on the top 1% of advanced creative users. These power users became evangelists, sharing their complex workflows and creating a powerful flywheel for organic adoption.
Don't accept the false choice between AI generation and professional editing tools. The best workflows integrate both, allowing for high-level generation and fine-grained manual adjustments without giving up critical creative control.
Implementing AI effectively isn't about finding a magic prompt. It requires an R&D mindset: investing time to build proprietary systems. Expect a learning curve and failed experiments; the goal is building a long-term competitive edge, not an overnight fix.