Catching Stars – finding customers and hires from your GitHub stargazers (blog.val.town)

Val Town has launched a new tool designed to automate the process of identifying potential hires and customers through GitHub stargazers. This innovation addresses the manual effort typically required for lead qualification, allowing seed-stage B2B founders who code to efficiently research potential candidates by leveraging an OpenAI-powered agent capable of web searching. The tool assesses public GitHub repository activity, such as stargazers and forks, and generates leads based on a defined ideal customer profile. By utilizing LLM capabilities, the results often exceed those from traditional enrichment services. This development is significant for the AI/ML community as it demonstrates a practical application of AI in streamlining workflows within tech startups, combining machine learning with smart automation. The core system employs a simple polling method to gather GitHub activity while utilizing OpenAI’s agent SDK to perform detailed research. With a customizable dashboard and daily email digests, the tool not only enhances lead generation but also exemplifies the trend toward "end-programmer programming," empowering users to modify the application as needed. This model positions AI as a valuable asset in the tech hiring and sales landscapes, prompting a thoughtful approach to outreach and engagement.