There’s an argument that despite the prevalence of search engines, Wikipedia, and large language models (LLMs), we still need to know things. We shouldn’t just look things up.
I think this argument could use better examples. Canonical knowledge, like Newtonian physics and text encodings, is not the best example of something you should memorize. Sure, you’d be faster at solving a problem if you know something relevant to that problem. But in some contexts, predicting what problem you’ll have, and what knowledge you will need, is hard. Knowing how to look up information is nearly as effective as knowing that a million facts are true, and doesn’t require me to adopt the habit of spaced repetition.
I used spaced repetition software (SRS) for five months in 2022. I was looking for a job and not feeling so good. I hoped my job interviews would go better if I had memorized a certain set of facts. I wrote 617 Anki cards, used the app every day, and savored the challenge of writing good cards. I gave up before I got a job.
What actually helped my interviews was focusing on my impact. The real problem was that I didn’t feel confident. I didn’t feel confident because I was telling the story of my previous work in terms of activities rather than impact. I hadn’t made sense of what I’d done before. I didn’t understand what my work meant to hiring managers. In their jargon, I didn’t understand my differentiators.
To me, a differentiator is a circuit element, not an attribute of a job candidate. But I’ve read some Gregory Bateson. I remember his motto:
Information is a difference that makes a difference.
Daniel Dennett has recently examined the idea too.
Dennett used to think you could reduce meaning to propositions, but he changed his mind. He now argues that semantic information generally isn’t propositional. Propositions sometimes usefully approximate meaning. But if you want to get semantic information completely, you can’t assume a proposition will do the job.
In chapter six of of his book From Bacteria to Bach and Back, he connects semantic information to design, and design to research and development (R&D).
So let’s consider, as a tentative proposal, defining semantic information as design worth getting, and let’s leave the term “design” as noncommittal as possible for the time being, allowing only for the point I stressed in chapter 3, that design without a designer (in the sense of an intelligent designer) is a real and important category. Design always involves R&D work of one sort or another, and now we can say what kind of work it is: using available semantic information to improve the prospects of something by adjusting its parts in some appropriate way. (An organism can improve its prospects by acquiring energy or materials—food, medicine, a new shell—but these are not design improvements. Rather, they are just instances of refueling or rebuilding one’s existing design.) One can actually improve one’s design as an agent in the world by just learning useful facts (about where the fishing is good, who your friends are).
The four-strong embedded software team at my company is having a tough time. We maintain a lot of software we didn’t write. We all joined the company within the last three years. Our software is complex. We have the artifacts, but the artifacts are not the same thing as the design (in Dennett’s sense) of the people who created it. It’s hard to for us to improve our design without the original authors around to mentor us.
Our software is not canonical like Newtonian physics. It’s esoteric. There’s public information about it, but it hasn’t benefitted from centuries of cultural evolution. It isn’t private thoughts1, but also isn’t widely understood.
I’ve thought of my job as maintaining, modernizing, or reverse engineering old software. But that understanding has continuously underestimated the difficulty of the job. It keeps getting harder.
Is it software archaeology?
Actual archaeologists use the term “software archaeology” as a joke. Meanwhile, Embarcadero has made it into a Java solution! Software archaeology certainly intersects with reverse engineering, but focuses more on the social context (“Why is it designed like this?”) than the technical artifact (“What is its design?”).
Sometimes software archaeology helps reverse engineering. When it is difficult to glean the design from the artifact, the social context can provide critical clues.
Organizations grow regimens of information. A document in Confluence always has an author, a set of viewers, a set of tags, a comment thread. Teams to chase down what matters with mental models like OKRs. Architecture decision records (ADRs) are hoped to ease archaeology for future people. But I’m astonished at how belabored an ADR is, especially the “status” section. How can you label a decision as “accepted”? Who accepted it? Who didn’t? The ADR in which ADRs are “accepted” is not an architectural decision about software!
Acronym-laden formats, like propositions, have tradeoffs. A rigid data format is consistent and predictable, but sometimes infeasible. Things that matter don’t always fit into a consistent format. Just because you have a consistent format doesn’t mean your readers are free from the burden of interpretation.
People need to learn things, but each person learns for themselves. Learning isn’t the accumulation of information; it is the redesigning of an organism. Knowledge isn’t transferred, it’s only developed.
I want to encourage the development of knowledge. My current hypothesis? As far as formats for semantic information go, stories and dialogues are probably the best you can get. Smullyan’s Is God a Taoist?, my favorite dialogue, doesn’t follow “bottom line up front” (BLUF) or the Minto pyramid. The conclusion is at the end, after inquiry has dug up what matters. Maybe information optimized for fast consumption isn’t a good fit for archaeology.
When somebody has a story worth telling, let them share it. The medium doesn’t matter. Pick something convenient for your situation. Don’t enforce a rigid schema. Encourage semantic information.
When I worked with the Auklet team, I told stories through Jira work logs. My boss loved it and my coworkers found useful info in my work logs.
At my current company, I’ve put a stories/ directory in the main
project repository. This is inspired by the idea of keeping documentation
in the repository. Maybe a story is social documentation. In software
archaeology, social documentation makes a difference.
Sometimes I get the urge to query the web for the location of an object in my house. ↩︎
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© 2024 Karl Schultheisz — source