Every day I have the paradoxical pleasure of sitting across from two extremely brilliant technologists: Raj, our CTO, and Patrick, our Data Scientist. The paradox is, frankly, that while I can [hopefully] absorb their genius merely by osmosis and/or covertly listening in on conversations, it has the downside of also making me feel like one of the dumbest people on the planet.
There I am – banging away on emails, organizing media dinners, talking up the product to anyone who will listen thinking to myself “I’m the bees knees” – and then someone asks me a technical question. Up to the point that I joined AirPR, “java” was another name for coffee and “ruby” was associated with red slippers. And don’t even get me started on exponential regression or coefficients because last time I checked Algebra 2 was about as far as this girl took it.
This is not a company secret. In fact, not long ago while at a team lunch Patrick quipped that perhaps I should let someone else figure out the tip, as 20% may end up accidentally around 7%. It was, as Tina Fey calls it, a “joke-truth.”
So, being the extremely tolerant team player that I am – who is well versed in passive aggressive behavior – I thought it would be fun to turn the tables on Raj and Patrick and kindly ask them to WRITE a blog post. Ha!
The assignment: 4 things to know about working with a startup
In no particular order, here is the startup world according to Raj and Patrick. Just for fun I have not made any edits and note their clear disdain for periods
#1 Wearing multiple hats (besides engineering):
- Designer: designs won’t be completely specced, you will make decisions about look and functionality
- IT: when your computer breaks you have to fix it yourself
- CEO: make on the fly decisions about features / bugs prioritization as they affect product and users
- Operations: Keeping track of server load / setting up performance monitoring systems / deploy procedures
- Facilities: moving/setting up desks, buying equipment, food, etc
#2 Specs don’t really exist:
You will know the goal of a feature, but rarely be given directions on what to do or how to do it. This can be a big change from larger companies
#3 Finding answers yourself:
When problems come up, there won’t be a standard way of doing things or another person on your team to ask for solutions, so you’ll need to explore the problem space yourself and experiment. This also means you learn more about the problem and think outside the box rather than just following what someone else tells you to do
#4 You will have to code faster:
When you start out at a startup, it seems like it’s constantly crunch time so you may compromise on code quality to meet business requirements. As you continue, you learn (by necessity) to code both elegantly and quickly
#5 Keep expecting the unexpected:
There will always be problems that will hit at the most unexpected times, fires to fight, and new features/approaches that you didn’t think of before. Raj also wants to add that this, combined with the long hours and other challenges of working in a startup makes you a more complete person
You will eat a lot of burritos
Writing emails is more difficult than coding
One more thing guys…I said 4 things not 5. Now who’s bad at math?
Rajagopal Sathyamurthi is the Co-founder and CTO of AirPR. Prior to AirPR, Raj was a Technical Director at Dreamworks Animation and a Software Engineer at Zynga. He has designed, implemented and deployed several web applications, and most recently, an iOS app as well. He holds a Bachelors Degree in Computer Science and a Masters in Mathematics from the Birla Institute of Technology and Science and a Masters in Computer Science from Stanford University with a specialization in Data Visualization and Computer Graphics. While at Stanford, Raj worked as a Research Assistant in the Artificial Intelligence / Robotics Laboratory. As part of this work, he designed and implemented algorithms that simulate local methods for communication in ad-hoc networks.
Patrick Liang is the Data Scientist for AirPR. Most recently, he was a Senior Software Engineer at Zynga focused on backend optimization and infrastructure for large scale text processing and analysis. Other relevant experience and accolades include: creating usage analytics reports for internal project tracking systems at Apple; developing a data API mashup while at Yahoo (for which he also won the grand prize in their internal mobile app contest); and creating a language and encoding detection tool based on n-gram text analysis while working for IAC. Patrick holds a Bachelors Degree in Computer Science from the California Institute of Technology, where he did coursework in learning systems and neural networks and was a teaching assistant for database systems.