Generative AI: A Creative New World with Post-PMF Strategy

Generative AI: A Creative New World with Post-PMF Strategy

In the age of generative AI, a powerful new class of large language models is revolutionizing the way machines create and generate content. From writing and coding to drawing and creating, these AI models are capable of producing credible and sometimes superhuman results. This technology has the potential to bring the marginal cost of creation and knowledge work down towards zero, leading to increased labor productivity and economic value. With billions of workers in the fields of knowledge work and creative work, generative AI has the power to make these workers at least 10% more efficient and creative.

Text generation is currently the most advanced domain of generative AI. However, natural language is notoriously difficult to get right, and quality matters. On the other hand, image generation is a more recent phenomenon but has already gained viral popularity. People find it more enjoyable to share generated images on social media platforms like Twitter than text. This opens up exciting possibilities for generative AI in the realm of copywriting, where there is a growing need for personalized web and email content to fuel sales and marketing strategies, as well as customer support. Language models can serve as writing assistants, helping businesses create compelling and tailored content for their target audience.

Moreover, there is a significant opportunity to develop generative applications for specific end markets. While most writing assistants today are horizontal, there is potential for vertical-specific writing assistants. These specialized applications can cater to various industries, from legal contract writing to screenwriting, offering tailored solutions that meet the specific needs of each sector.

In the realm of coding, GitHub Copilot has already demonstrated its capabilities by generating nearly 40% of code in projects where it is installed. However, the true potential lies in opening up access to coding for consumers. Learning to prompt could become the ultimate high-level programming language, allowing individuals without extensive coding knowledge to create and build their own applications.

Generative AI also has the ability to reshape social media and digital communities. New tools and applications like Midjourney are emerging, enabling users to express themselves in new and innovative ways. These generative tools create new social experiences as consumers learn to create in public and share their creations with others.

To succeed in the world of generative AI, teams must establish a flywheel effect. Exceptional user engagement is the first step, followed by using that engagement to improve model performance through prompt improvements, model fine-tuning, and leveraging user choices as labeled training data. Great model performance can then be used to drive more user growth and engagement, creating a self-reinforcing cycle.

Now, let's shift our focus to the post-PMF (Product-Market Fit) strategy. It's crucial to consider this strategy before expanding a business. A brand is a promise, and building a strong defensibility against competitors is essential for long-term success. Once PMF is proven, competitors are bound to emerge and engage in fierce competition. In this war, maintaining prices becomes challenging, particularly in rapidly evolving industries like IT and software, which include AI, IoT, and Blockchain.

One way to establish defensibility is through proprietary technology. If a company can develop a technology that offers a 10x performance improvement over the closest substitute, it can stand out in the market. However, if the technology itself does not differentiate the business, focusing on a 10x improvement in user experience (UX) can be a viable alternative. Embedding the technology deeply into users' lives or business operations can provide a significant competitive advantage.

In addition to proprietary technology, network effects and economies of scale play crucial roles in building defensibility. Network effects occur when the value of a product or service increases as more people use it. By creating a strong network effect, a company can establish a competitive moat that makes it difficult for competitors to replicate its success. Similarly, economies of scale can provide cost advantages and make it challenging for new entrants to compete on price.

Finally, building a strong brand is essential for post-PMF success. A memorable and trusted brand creates customer loyalty and helps defend against competitors. Investing in brand building activities, such as marketing and customer experience, can pay off in the long run.

In conclusion, generative AI is opening up a creative new world with endless possibilities. By harnessing the power of large language models, machines can generate content, code, and create with incredible results. However, it is crucial to consider the post-PMF strategy to build defensibility against competitors. Whether through proprietary technology, network effects, economies of scale, or a strong brand, businesses must establish a competitive advantage to thrive in this rapidly evolving landscape.

Actionable Advice:

1. Embrace generative AI in your business by exploring its potential for personalized content creation, such as copywriting or vertical-specific writing assistants.
2. Consider investing in proprietary technology that offers a significant performance improvement or focus on delivering a 10x better user experience to differentiate your business.
3. Build a strong brand through marketing and customer experience initiatives to establish customer loyalty and defend against competitors.

Incorporating generative AI and implementing a robust post-PMF strategy can position businesses for success in the creative new world that lies ahead.