Hi, my name is Eli-Henry Dykhne. As a Software Engineer Co-op at Architech, I’ve picked up more than just technical skills. For all newcomers to Architech, I’ve made this short guide to help you settle in. Without further ado, here are my Architech Do’s and Don’ts!
Do: Grab a protein bar from the middle drawer of the kitchen in the morning for a filling breakfast. If you‘re like me and don’t always eat breakfast, eating a bar after you arrive can be a much more pleasant experience than forcing yourself to eat when you don’t want to, or being hungry (or hangry) until lunch.
Don’t: Go into overlong explanations during standup. Since standup is for brief updates, in–depth discussion of your work should be stowed for after the meeting unless you’re directly asked for it.
Do: Come to the lunch & learns and lightning talks to take advantage of the opportunity to learn something that might be outside your field of work. It’s also often a great chance to see what other teams have been working on or learn about events you were unaware.
Don’t: Assume that your lead developer knows the answer to every problem. They‘re not your TA and have not seen the “answer sheet”. When working with new libraries, it’s entirely possible that you have the most experience with it on your team.
Do: Update your timecard daily. Trying to remember what you did on Monday while filling out your timecards on Friday is rarely an easy task. For those who ignored the above advice, checking your commit history for each day is often a good way to jog your memory.
Don’t: Be afraid to ask for help. In this industry, there’s almost always someone in the company who has experienced the same problem you‘ve run into. If you truly seem stuck, look to someone who may have worked on something similar. After all, one of Architech’s core values is “Be Open and Collaborate”.
I hope my guide helps as you get to know the rest of Architech!
Software Engineer Co-op Student
Eli Henry is a Computer Science student at the University of Guelph, with a passion for cloud technologies and Machine Learning.