The technical priorities of a startup

There should be none. I mean, sure, there should be some, but just enough to get over the hump of creating testable hypotheses. The hypotheses, should in turn, be iterations on your product – and they should be in the hands of your users.

There are just so many other things that cause a startup to fail, that optimizing the technology stack is just the wrong place to spend any resources. This doesn’t mean you shouldn’t use promising technologies if they can solve clearly anticipated problems. It does mean that you don’t want to waste resources in premature scaling. This, of course, applies to all aspects of your startup – tech, sales, support, etc. 

As far as tech is concerned, pick the best tools for the job, and then move forward quickly. Don’t worry about being perfect (in fact, don’t be). Get traction first – no one cares how amazing your backend is.

The tech stack of the startup

This post is about startups and technology. Of course, nothing will help you if you don’t have a market, or traction, or a business model, or an actual product, or good people. Those are conversations for another day, but now, here’s what I’d use if I’m starting a startup today:

Programming languages:

Data stores:

Data processing:

Machine learning:


Version control:



Functional testing:

Project management:

Am I missing stuff?