6/DD/2024

The title of this post is a play of Apace DevLake which is a tool for gaining insight into your repositories for engineering excellence. For example, Apache DevLake provides a dashboard with statistics on the health of your Repository for example average close time of open issues.

Here I would like to discuss a tool to for DevRel excellence.

This tool (which would have a better name than Apache Dev(Rel)Lake)  would aid in data driven DevRel. There are parallels here with data driven marketing (right person, right product, right time).

The tool will have integrations into platforms where the company and users interact (GitHub (where the code is stored), Kaggle (how people use your library), Slack (what questions the users ask), Discord (what questions the users ask), Discourse, documentation page views, company website click through, E-mails, Teams calls, etc.). A lake is fitting name from a collection of unstructured data. It has never been easier to query such data thanks to LLMs and their multi-modal abilities. 

The data could be used for a variety of DevRel purposes such as:

• Identifying the most important users.

• Gain insights into users pain points and identify where users fall off trying your product and move to an alternative product.

• Generate unique content to each user based on their interests e.g. what API are they most interested in or what sector of industry do they come from? This could also help in event planning to understand which tutorials would benefit which people.

• Automate the boring stuff such as welcoming new users and pointing them to tutorials which are of interest for them. Create a model that points users to other 

• Create roadmaps for the most requested features.

I have created a few dashboard for communities I am interested in: