Surface

AI Leadership Assistant | Enabling Managers to Lead and Develop High-Performing Teams Many managers lack at least one of three things required to lead and develop high-performing teams effectively: insights, capacity, or skills. 1. Insights: Leaders often lack a true understanding of what is happening within their teams. Hierarchies naturally create information asymmetries, and feedback does not flow equally in both directions. Employees may hesitate to openly communicate problems, concerns, or feedback upward, leaving managers without the insights they need to act early and effectively. 2. Capacity: Even great leaders have limited time. Individually understanding, coaching, and developing every employee requires continuous attention and regular one-on-one interaction, which becomes increasingly difficult as teams and organizations grow. 3. Skills: Even when managers have the right insights and enough time, they may not always have the leadership knowledge or experience required to know what action to take, how to coach a specific employee, or how to develop their team effectively. We are building an AI leadership assistant to solve these three problems. Over the past eight months, we have built our first working MVP and conducted a proof of concept with a Swiss SME generating more than CHF 1.2M in annual revenue. We are now developing the next version, with another potential customer already interested in testing the product in approximately two months. Our current technical partner, a Cornell CS Master’s graduate who recently joined Palantir full-time, is moving into a technical advisory role. We are therefore looking for a Founding Engineer who wants to take strong ownership of building the next version of the product and potentially grow into an even larger technical leadership role as the company develops. We are still early, but that is exactly what makes this stage exciting. The product, technology, and company are still being shaped, and we are looking for someone who wants to genuinely build with us rather than simply execute a predefined roadmap.