PH Deck

Product Managers and Makers often experience difficulty in getting started on various tasks due to the complexity and breadth of their roles. They struggle with prompt engineering, which is crucial for effectively using GPT-based tools, leading to inefficient task execution and productivity loss.

Teams prototyping new generative AI features with LLMs face a complex and technical challenge in composing prompts with product data, leading to difficulty in quickly and effectively prototyping generative AI features.

SaaS products often face challenges such as low user engagement, suboptimal pricing strategies, and difficulty in leveraging the latest AI technologies, which leads to decreased customer satisfaction and revenue.

Product managers often struggle with efficiently managing their product lifecycle, from customer discovery to go-to-market planning and product execution, which can lead to delayed product development and market entry times. Struggle with efficiently managing their product lifecycle

Aspiring and current product managers often struggle to gauge their knowledge and proficiency in the field, lacking a structured way to assess their skills and identify areas for improvement.

Engineers often struggle with efficient communication, market research, and project planning during product development, hindering their ability to innovate effectively.

Freelancers often face creative blocks and inefficiencies in their workflow, leading to a decrease in productivity and quality of work. The drawbacks include time wasted on overcoming creative hurdles and a lack of inspiration.

Product Managers often struggle to adapt and overcome challenges in the rapidly evolving field of product management due to a lack of insights and data-driven strategies.

Traditional prompt engineering is complex and inaccessible for those without significant AI experience, making it challenging for users to effectively interact with large language models (LLMs) to obtain useful responses. The complexity and inaccessibility of traditional prompt engineering are the main drawbacks.

Users interested in leveraging GPT-3 for product development face challenges due to lack of coding skills or understanding of GPT-3's capabilities, leading to barriers in innovation and application development. The lack of coding skills or understanding of GPT-3's capabilities significantly hinders the ability to innovate or develop applications.