Railroad lines are, at any given moment, unidirectional. You can’t veer off the track that has been laid out in front of you, and you can’t make unscheduled stops unless you want the overnight express to run into you. These can be problems if you’re not altogether happy with the direction the track is taking you. Equally so if you would like to make any additional visits alongside the plotted course.

On the other hand, if you just keep your limbs inside the vehicle as advised, you can safely traverse the track at a very high velocity to arrive at your destination faster than with any other means of surface transport. You can watch the boring, mundane wasteland outside go by without needing to interact with it in any way.

So, riding the metaphor for all it is worth, when David Heinemeier Hansson took Ruby and created an opinionated, high-productivity web development framework, is it any surprise he named it Ruby on Rails? The name lays out the deal up front: our way, or the highway.

Could he possibly have been any more explicit? As I’m sure most readers know, DHH is anything but subtle. Yet people seem to keep missing the point.

When Paul Graham’s A Plan for Spam made its dramatic entrance into the anti-spam battle four years ago, it heralded the beginning of the end for spam — as we knew spam back then, anyway. Applying a simple statistical approach, based on word frequency analysis with a naive Bayesian classifier, Graham described how to create a spam filter accurate enough (99+%) that false positives effectively ceased to be an issue.

The central idea of the Graham Algorithm was quickly adopted en masse by spam filters, and as a result, the spam arms race has in the past few years tipped in favor of the good guys. “Successful” spam has devolved into exactly what Graham predicted it would: “some completely neutral text followed by a URL.” For me personally, the combination of good server- and client-side filters has made spam yesterday’s problem. (Well, that, and using Gmail as a front-end for lower-priority e-mail; spam all you want, it’s Google’s problem and they’re up to the task.)

Recently at $WORK, we’ve succeeded in applying similar text classification principles to another unrelated problem area, with the intent of forcing the computer to do the tedious job it was invented for, allowing us super-apes, in turn, to spend more time under a palm tree on the nearby beach, sipping tinto de verano and working out answers to deep existential questions, or whatever else it is that one does on the beach (note to self: need more practice).