Startup Technology - Technical Founder Advice

I would like to introduce Jared Frieden, my partner, and his esteemed panel who he will introduce to talk about technology. Thank you. Thank you, Jeff.

Okay, well, I am super lucky to have a very esteemed group of guests with me here today. Everyone on this panel is a tactical founder of a really successful company. Everyone here has built a really cool company in a really amazing technology organization.

We've changed the name of the event for today. It was originally called CTO advice, and on the advice of Lillian, thank you so much, we have changed it to Tactical Founder Advice, which I think is a better description. I'd also like to thank everyone on the Startup School forum who wrote in with questions for the panel. We posted a few weeks ago and solicited questions. We got over 150 responses, so thank you to everyone who wrote in with those questions. We're going to do our best to cover as many of them as we can, and then at the end, we'll open it up to the in-person audience for some questions as well.

Okay, so let's get started. Could we start by having everyone introduce themselves and tell us about your company and about your technology? Like, what's your tech stack? What's some of the interesting technology that you build? How does your technology organization look like today?

Oh, you monster! Hello everyone, my name is Ralph Judy. I'm CTO and co-founder of Plangrid. Plangrid, we're 350 people based out of Mission, San Francisco. We write beautiful, easy-to-use software for the $17 trillion construction industry.

So what that looks like to you: the analogy I often use is we're like GitHub for construction. Construction has blueprints; blueprints change rapidly. Version control is extremely important. If you have changes, that means there are issues that are happening. Issues need to be tracked, and then we build collaboration tools on top of that too, as well as a lot of other tools for the construction industry that go into some deep jargon.

Our stack: we're based on AWS. We used to be based on a variety of other things, and we had to move everything into AWS over time. On our back end, mostly Python; we've got some Go and other things. And then one of our challenges is we actually write native for every platform. So we've got iOS with Objective-C, Android all Java and Kotlin, the web Reacts, and then Windows. We have a full Windows app as well, which has done that.

Hi everyone, I'm Calvin French-Owen, and CTO and co-founder of Segment. Segment is a single API to collect, organize, and adapt all of your customer data into hundreds of downstream tools you might be using, whether that's an analytics tool like Google Analytics or Mixpanel, maybe a customer success tool like Gainsight, maybe an email tool like Customer.io. Segment helps you collect data from where it lives and get it where it needs to be.

In terms of the company overall, we're a little over 300 people right now. We have our headquarters in San Francisco, but we also have offices in Vancouver, New York, and Dublin. The engineering, product, and design team, which is kind of how we build product here at Segment, is a little over 80 or 90 right now.

In terms of our tech stack, we're also built entirely atop of AWS in terms of how we run our infrastructure. We run on top of ECS, Amazon's container service, and pretty much all of our different services are containerized today. We're running about 300 different microservices, which are piping together various Kafka topics and reading and writing, transforming this data, getting it to where it needs to go. Our back-end is primarily written in Go.

Good morning everyone, my name is Diana Hu. I was the founder and CTO for SEO Reality, and we're building the backend for augmented reality. I say I was because my company just got acquired by Niantic, the makers of Pokémon Go.

So what we were building in Escher, and now we actually continue doing it in Niantic, is building this backend technology for augmented reality to enable developers to build AR experiences as easy as possible. So we handle all the complexity with the computer vision rhythm...