The Ongoing Quest for Greater Knowledge
Just as the body hungers for nourishment, the mind thirsts for knowledge. We often measure the value of knowledge by weighing the distance between its acquisition and application. The apprentice trusts that what the master teaches her now, though it may appear to her irrelevant, will reveal its useful application in lessons to come, though possibly distant. There is a principle described here known as milk before meat, in that we can only acquire and understand knowledge of greater degree once we’ve made sufficient application of the knowledge within the degree that we have acquired, and like the law of the harvest, there are no shortcuts.
But what if there was a way to upgrade our velocity from impulse to warp? Narrowing the gap in the window of knowledge application is the task of our age. When we build a world where we can achieve faster, more impactful information in the truly useful, qualifying moments, we all win. Indeed, having what you need when you need it is a tremendous gift, but receiving what you need when you didn’t know you needed it is a quantum leap. We lean into those who know better than we do, and we welcome the positive element of surprise when they lean into us.
The Rise of Intelligently Fine-Tuned Tools and Services
A software engineer’s daily task is to produce a set of solutions to an equal set of problems that will manifest themselves through a sequence of revealed steps. Her work velocity increases in proportion to the reduction in time for her to find and apply a relevant solution at each step. Rarely are those steps forward unique or the trail new. The forest she enters has likely had enough paths cut through to make her journey smoother than she had anticipated.
But where are the trails?
Traditionally, they are known only to those who’ve blazed them. An unknown, unappreciated, and unshared exercise siloed up between the walls of a massive maze of code repositories. All software engineers come to learn that everything from the small victories to the unexpected moments of coding triumph they may experience along the path of a development cycle are, in the vast majority of cases, celebrated alone in the minds of those who pave them. A mansion of code, full of rooms wherein the single occupant has occasionally ‘raised the roof’ between his headphones.
A few months ago, standing at the forest entrance like Everest sherpas surrounded by a throng of boisterous mountaineers, I was introduced to GitHub CoPilot, Amazon Code Whisperer, and Chat GPT.
“We’ve walked all the paths, and we know all of the ways,” they boldly pronounced. “Wherever you want to go, we’ve been there, and we know the quickest and easiest way to your destination,” they paused, smiling. “Oh, and by the way, it doesn’t matter if you don’t tell us where you’re going, we’ll be watching regardless and making our best assumptions based on where you’ve been and where thousands have gone before you.”
I was a little late coming, with doubts following. Were these bold proclamations true? Was I hearing the genuine audible sigh of relief from a group of like-minded forest wanderers? Or was the noise surrounding this new gathering nothing more than faux marketing fanfare produced to elicit a peek at one more curiosity under the AI big top? I very much hoped for the former.
Since that moment, my experience has been a punctuated sequence of one surprise after another, best described as a ghost in the machine who eerily reads my mind and serves, as on a silver platter, a tremendous amount of useful information it continuously anticipates for me, with uncanny timing.
What about Relevant Search?
Web Search continues to play its role as the silent but attentive librarian, willing to point searchers to those who volley and financially pine for their books to be placed nearest the searcher’s attention. But, at the end of an inquiry, one feels they have only touched the quiet shelves of a seemingly endless and static result set. The librarian has done her job, after all, what more can she do? Asking for more is like one who, after having a conversation with a book, complains of getting the silent treatment.
Relevant search will always have her place, but with the rise of tools designed for responsive learning, and the increasing number of services designed for the rapid application of actionable knowledge, she will find herself more and more like a wallflower at the ball, waiting to be asked to dance again.
The Future of Applicable Learning for Corporate Learners
Imagine, however, upon entering the library, you were given the option to have a conversation with a librarian who possessed a photographic memory and had read all of the books. Also, She was willing to have a discussion with you about any topic for any length of time, at any level of detail. What’s more, she didn’t mind producing content for you, be it poetry or prose, code, recipes, itineraries, artwork, mathematical formulae and statistical analysis, language translations, music, or screenplays, she was willing. Again, if she didn’t get it right the first time, she’d iterate with you until you were satisfied. Lastly, she remembered all of your conversations, even the quirky ones, and could pick up again wherever you left off without skipping a beat. She would be all at once your instructor, your collaborator, and your assistant.
That’s the kind of librarian we’ve all been waiting for.