Python might not be the best language for everything, but it’s almost certainly the second-best language for anything. - Peter Wang, PyData SV 2014¹

Ornithorhynchus anatinus, better known as the platypus, has a strong claim to the title of oddest bit of charismatic megafauna on the planet. House-cat sized, looking rather like a beaver with a duckbill grafted on, they also have the distinction of being an egg-laying mammal with venomous claws. Odd ducks² though they are, they are a successful species with major style points.

Platypodes³ also exist in the business world. They are those people with odd backgrounds, either professionally or educationally (or both), that don’t fit neatly into any particular categorization. In particular, platypodes have a STEM background (though are not necessarily CS majors) but major experience in non-engineering roles.⁴ Looked at positively, platypodes can contribute in a variety of roles, often crossing the boundaries between sales, marketing, engineering, design, and/or Management. In a culture of lean startups and lean enterprises that emphasize cross-functional teams they are cross-functional individuals. They’re perfect for starting new departments or doing things that just don’t fit elsewhere.

Platypodes, though, are rarely recognized for these positives. Instead, the typical hiring process will weed them out: they went to school too long; they aren’t focused enough; they aren’t enough of a specialist in anything; they have one of those graduate degrees incompatible with startup-life; they’re going to move onto something else in ...

Customer Success Engineering is the continuation of product development by other means. — Carl von Clausewitz (loose translation)

During my brief time at Jut, I was in marketing as a Customer Success Engineer, which also tends to be known as a Forward Deployed Engineer (and hence they will be used interchangeably throughout). At Jut, this role was under marketing, and I never gave that placement a second thought. Our role was to onboard customers, teach them Jut (and our DSL, Juttle), and basically do whatever was necessary to make them happy with our product. The unspoken corollary is that we took our observations back to Product and Engineering to improve the product/market fit.

Since the dissolution of Jut-as-I-knew-it¹ I’ve talked to several companies about this role in their organization. In almost all cases, the role reports into Sales, and may even include some sales-type KPIs, such as upselling or whatnot.² With all due respect to these companies, I believe this is a mistake. In some cases, they may just be naming (pre-) sales engineers as FDEs/CSEs; however, if they actually mean to have FDEs/CSEs as such, they should not be reporting into Sales. Doing so will gut the usefulness of this role.

I’ve never been very good at defining the difference between sales and marketing, but I think a simple definition for the purposes of this post is this: Sales is going to sell the product they’re given; marketing is going try to ...

Introduction

If you hang out with the cool software engineering kids, you’ll probably hear about isomorphisms. While this term has a formal mathematical definition, for most purposes it’s just a big word with a simple meaning. Specifically, that two different things are functionally identical for some purpose. Pizza and ice cream are very different, but are isomorphic with regard to wrecking a diet.

This piece is about isomorphic experience in tech; that is, work experience that appears unrelated to what a company is looking for when hiring for a role but is really the same as the listed requirement. I focus on my experience in law (specifically patent litigation) and management consulting in this piece, but the general idea applies to candidates with backgrounds in medicine, the sciences, and other areas.

You may be asking at this point why, other than academic curiosity, you should care. Well, if you hire, being aware of isomorphic experience allows you to expand the pool of possible candidates, and capture talent your competitors may have overlooked. Exploiting labor market inefficiencies was one of the main lessons from Michael Lewis’s classic Moneyball - here we are just applying it, well, for lack of a better word, isomorphically - to the tech industry.

Two Case Studies

Law

The beginning of my career was spent almost exclusively as a patent litigator. That means once a dispute led to a lawsuit over patents, I was on the team arguing our client’s side. (The majority of the ...

My piece on IoT prototyping toolkits was published in the IEEE IoT Newsletter this week. Find it here.

Special thanks to Tyler Reid for providing comments on the draft and generally sanity-checking some of the tech details (they were, after all, parts of the stack he worked on when we were both at Cisco). Any remaining errors are, of course, my own.

The piece starts with the knocking of a woodblock which creates a kind of rhythmic gauntlet through which the orchestra has to pass. — John Adams

IN 1986, Michael Tilson Thomas and the San Francisco Symphony commissioned an orchestral work from John Adams for the Great Woods Festival.¹ The resultant fanfare has become one of Adams’² most popular pieces. In 2015, Adams’ work seems like a fitting anthem for the SF/SV startup scene, where many a hopeful donkey straps a horn to its nose and hopes for a myopic venture capitalist to mistake it for an undiscovered unicorn.³, ⁴

This piece came to mind a few Monday’s back, when the startup I was working for, Jut underwent a massive reorganization.⁵ A startup pivoting in San Francisco is fairly unremarkable (unless you work for it and the pivot involves laying off around 80% of the staff). On the other hand, when you were the last hire, 80% of the company is gone, and it was Day 11 for you, the event is a bit more noteworthy, and “Short Ride” takes on an entirely new meaning.⁶

Waiting in line for the Fast Machine

I applied to Jut as a result of a bad Google search. I was looking for a library to make plotting real-time data easier from an Arduino I had streaming JSONs from a sensor. I came across Jut.io, which had nice graphs from streaming data, but required a backend not appropriate for ...