As someone who has had the opportunity to manage teams of 100 or more individuals, as well as being managed, I have gained some experience and knowledge that I hope can be useful to others. Through trial and error, and a willingness to learn from my mistakes, I have developed a few mental models that have helped me to navigate the challenges of leadership. In this post, I would like to share ten insights with you in the hopes that they may prove helpful in your own professional journey.

As a startup founder, it's important to keep an eye on paradigm shifts in technology because they present opportunities for disruption and the emergence of new winners. In the past, we've seen software displace machines, the internet create software as a service, and mobile-first products overtake the consumer market. Now, we're in the midst of another paradigm shift, and that's the rise of AI.

In the startup world, many conversations stall while discussing compensation. This is unsurprising, given that the upside is composed of cash, stock options, growth prospects, and possibly a bespoke role. As an investor, I find myself stepping in as the matchmaker to overcome this final hurdle and get to a mutually agreed offer. To make this process more repeatable, I have come up with a simple framework to facilitate compensation discussions.

As an exercise, I put together a few risk patterns that I’ve observed over the years. These are low precision proxies, weak on their own. However, the stronger the signal, the likelier the problem. Trust your gut.

When we invest in a new company, I spend the first few weeks getting to know the team to understand their current challenges to help where I can. A common topic is that of the product lifecycle, everything from defining a north star, to developing a written roadmap, to executing and delivering a successful product. Last month, I wrote down some of the key points that emerged during those discussions. In particular, I wanted to highlight some of the most salient points of tension that emerged during these discussions.

Big refactorings often end up becoming a creative endeavor or a quest to add cool new technology, as opposed to a set of well defined, independently valuable, and progressively executed milestones, with concrete and measurable results.