What is the number one mistake technical founders make? Why is pricing so important? Should entrepreneurs avoid at all costs having a service component to their business? What is fundamentally new and different in go to market strategies for modern enterprise software startups?
A self-avowed “failed physicist”, Martin Casado is a General Partner at Andreessen Horowitz, and previously was the co-founder and CTO of Nicira, a pioneer in software-defined networking and network virtualization that was acquired by VMware for $1.26 billion.
I have had the pleasure of getting to know Martin through the board of ActionIQ, a great NYC startup in which we are both investors.
Martin joined us for a fireside chat at the most recent edition of Data Driven NYC. The conversation centered largely around one of Martin’s favorite topics, go to market strategies for enterprise startups. There’s plenty of interesting thoughts and directly applicable advice for entrepreneurs in there, as Martin spoke as much from his previous founder experience as he did as a VC.
Here’s the video, and my notes from the chat are below the fold.
Who would be crazy enough to compete head-on with AWS?
The question was almost as obvious seven years ago than it is today. Yet in just a few years since its founding, Digital Ocean, a cloud infrastructure startup based in New York with data centers around the world, has managed to build a very impressive and fast-growing business, successfully competing with the giants of cloud computing.
Ben Uretsky, co-founder of the company (with his brother Moisey and 3 others) and its CEO from 2011 to 2018, stopped by for a chat at Data Driven NYC to tell the story of the company and share some lessons learned.
Here’s the video, and below are my notes from our great chat.
The hedge fund world has been evolving dramatically over the last few years.
Just like in other industries, software, data and AI/ML have been playing an increasingly important, and disruptive, role. Many hedge funds have been scrambling to embrace this evolution – not just to gain an edge, but also to avoid becoming extinct.
Certainly, quantitative hedge funds have been making heavy use of software and data for a while now. The “quant” funds rely upon algorithmic or systematic strategies for their trades – meaning that they generally employ automated trading rules rather than discretionary (human) ones, and they will trade tens or hundreds of assets simultaneously.
But another big part of the industry, the “fundamental” hedge funds, had been operating very differently. Those funds will perform a bottoms up analysis on individual securities to value them in the marketplace and assess whether they are “undervalued” and “overvalued” assets. They’ll often have a much more concentrated portfolio.
In part because the entire hedge fund industry has been performing generally poorly recently (years of performance trailing the stock market), there’s been mounting pressure on hedge funds to evolve rapidly, particularly fundamental ones.