I’m a web programmer who prefers Ruby. Working with outfits ranging from the LA Times to the smallest of startups, on projects lasting from weeks to year-long commitments, I’ve run the gamut of the tech stack, from low-level C, unix sysadmin-ing, http daemons and their proxies, Ruby, Rails, and all the way up to css, semantic and standards-based html, Javascript, and Flash. I’ve also worked with Amazon ec2 & s3, all aspects of the Google Maps API, and voip & vxml.
Secretly though, the moments where I get to teach and write tend to be my favourite.
During the day, I am currently happily employed at Shopify.
At night, I organize open data hackfests, help run the Ottawa Ruby group, and write my part of Rails in a Nutshell for O’Reilly.
All that being said, I’d also be pretty happy having a conversation about any of the following in particular:
Finding unknown relationships between fields of knowledge that usually have nothing to do with each other and realizing that their synthesis is totally awesome.
A well composed page with a carefully chosen face is a beautiful thing. While your brain is able to deal pretty well with drastically different fonts and page forms, the right presentation can make all the difference in terms of affecting you emotionally and practically; what if the yellow-pages used 15 different fonts on every page? What if they were curly and cursive? What if names were in orange?
Coming from a more neuroscientific or cognitive psychological feel, typography as an information delivery and filtration system is nuts; a well-tuned human head can skim through reams of information, pick out relevant or interesting ideas, and be thrown off or focused just because of the shape of the letters. (This links into Scott McCloud’s Understanding Comics.)
If we can read words, shapes and schematics, how can we adapt our presentation of information so that it scales with our data and delivers the truth? While statistics, cartoons and graphs are great at condensing information, how do you shape the output to give you a meaningful answer to a variety of abstract questions? How can you make it searchable? How do you leverage the human brain’s ability to spot trends and patterns among noise? How do you relate it to other studies? (Related to Edward Tufte, Martin Kryzwinski, Ben Fry, and John Maeda, among a ton of others.)