Recently, I have been brainstorming with early-stage companies in three areas: AI workflows and automation, go-to-market motion, and the data foundation and analytics layer that support GTM.
It has been fun. It also makes sense given the path I took from engineering into sales. I like the point where a technical problem and a commercial problem turn out to be connected.
AI workflows and automation
The first conversation I want is about the work itself. Where does a person spend time moving information, repeating a step, or finding what they need to make a decision?
A useful AI workflow should make that work easier. I am more interested in a specific problem and a useful result than in adding an AI label to a process that was already confusing.
GTM motion and lessons learned
Tools, techniques, and expectations all matter. So do the lessons that come from trying something and discovering that it did not work the way you hoped.
That is the part I want to bring to these discussions. I have worked across different sales environments, and I am still learning. A conversation is often more useful when we can talk honestly about assumptions and tradeoffs instead of pretending there is one perfect playbook.
Data that supports the work
The data conversation belongs here because a team needs to understand what is happening. Which activities are creating useful conversations? Where are people getting stuck? What information would change the next decision?
The goal is a foundation that supports the company's work at its current stage, with a clear reason for each extra layer.
An invitation to compare notes
These are areas I enjoy thinking about, not a promise that I have a universal answer. Every company brings a different mix of people, constraints, customers, and timing.
If you are an early-stage team working through any of these questions, I am happy to chat. Sometimes the most useful outcome is a better question, a clearer assumption, or a connection between two problems that looked separate.