In a blog post from Dave Cheney, open source contributor to golang, he writes that it’s always better to talk about a bug/feature/change then writing code. This avoids hurt feelings (when a change isn’t accepted) and ensures the change lands the first time.

Generally, pull requests are the wrong place to have a lengthy discussion. Dave recommends starting with a GitHub issue or design doc if it’s more complicated. Communication early prevents misunderstandings and leads to a smoother process for everyone.

Read the blog post

A talk given by Brian Moriarty, a renowned game designer/developer, that encourages listeners to dedicate themselves to the pursuit of making something awe-inspiring.

His examples range from Bach to Shakespeare and the meta game that transcends their original works of art.

In Bach’s compositions, numerology intertwined in the music that adds a hidden layer of meaning that requires multi-layer recursion to fully comprehend.

In the case of Shakespeare, countless people that dedicate untold hours to studying his works and unraveling the mystery of whether he was a group of people or just Sir Francis Bacon. After all, how could one man create all that?

It’s a reminder to recognize the pure and deserving admiration that comes from creating something that sparks genuine awe.

Listen to the talk

See also:

• Richard Hamming’s call to scientists to work on significant problems to be important in his lecture ‘You and Your Research’

An essay from Niklas Luhmann about learning to read and how there are different kinds of books that require different approaches.

Novels require a temporal dimension for the reader. They are continually reminded what they don’t know (e.g. the ending/resolution of the book). We can define novels to be in two states with regards to the reader–already read and not yet read.

Poems are different. They do not have a temporal dimension, but instead have many aspects that alter the meaning to the reader. Style, tone, word choice, metaphor, rhythm, and more. This requires ‘multi-layer recursion’, to think on each word, sentence, section repeatedly to unlock it’s implied meaning. It’s like the meta game, but in writing.

Theoretical texts (e.g. text books, non fiction) have different demands. The reader is looking to learn and must uncover what is important and what must be learned. This needs short term memory as well as long term memory. Short term to interpret and long term to recall connections with other references/memories.

Connecting information often looks like attaching the information and grouping it as is the case with attributing key ideas to the author. Notes are similar in trying to capture information to better retain it, but often fails (covered more exhaustively in his essay about Zettelkasten: ‘Communicating with Slip Boxes’).

An Emacs library that recreates Roam (software that implements a Zettelkasten-like system) using org-mode.

All notes are stored as individual files addressed by {timestamp}-{underscore_separated_title} and can be backlinked to create a graph of notes which can be generated using graphviz.

Read the docs

See also:

• Querying stats from org-roam
• Reflections on writing 500 notes
• My emacs config for org-roam

NOTE: Many things have changed about org-roam in v2. Code snippets and issues are likely out of date.

Problems with org-roam

• Auto completion is finicky (case sensitive, not fuzzy matching)
• Can’t search for content in the body of notes when adding backlinks
• Synchronizing between mobile and desktop is difficult e.g. Beorg on iOS can’t support a template that doesn’t have a title (org-roam’s template just has a #+TITLE tag)
• You can’t export to HTML in a built in way (looks like you need to use ox-hugo with a config header in each note which is ugly)
• Buffers don’t wrap text by default
• Distinguishes between backlinks and ‘cite backlinks’ which is confusing
• Automatically changes the file name if you change the title (these should be decoupled if you plan to publish notes)

org-roam v2

The downside of using ID links in org-roam

V2 is less portable than v1 now that links use `org-id`.

DONE Integrating org-roam [8/8]

DONE Use helm-rg for fuzzy full text searching notes

Add a keymap entry for it when in org-roam

DONE Use helm-rg to find notes to make connections to using full text search

• Add an action to insert a file link to the highlighted result Use helm-add-action-to-source to add the action. See github.
• Add link anchor words into it (maybe from title?)

(use-package helm-rg
  :ensure t
  :config
  ;; Add actions for inserting org file link from selected match
  (defun insert-org-mode-link-from-helm-result (candidate)
    (interactive)
    (with-helm-current-buffer
      (insert (format "[[file:%s][%s]]"
                      (plist-get candidate :file)
                      ;; Extract the title from the file name
                      (subst-char-in-string
                       ?_ ?\s
                       (first
                        (split-string
                         (first
                          (last
                           (split-string (plist-get candidate :file) "\\-")))
                         "\\.")))))))

  (helm-add-action-to-source "Insert org-mode link"
                             'insert-org-mode-link-from-helm-result
                             helm-rg-process-source))

DONE Toggle truncate lines in org-roam buffers

Make org-mode always use wrapped lines (setq org-startup-truncated nil)

DONE Set up exporting to html

• Use ox-hugo to export to md and generate html using hugo Add #+HUGO_BASE_DIR: ~/Projects/zettel and #+HUGO_SECTION: ./ to the front matter of each note
• Update the capture template to include hugo tags
  • org-capture docs
  • org-roam capture template docs
  • Add entry to org-roam-capture-templates
• Write a fn to batch export org files from a directory (since each note is it’s own file)

https://github.com/alexkehayias/emacs.d/blob/master/init.el#L715

DONE Cloud backup

• iCloud is nice since all my devices could use it without any additional software, but you can’t symlink directories so an app can’t use the same data directory as another. This makes it difficult to use multiple apps as an input source to zettel notes.
• Dropbox does sketchy things to desktops and used to cause random CPU spikes that would eat through laptop battery life. Not sure how much that’s changed.
• Github might work, but once the number of files increases that might become unwieldy.
• Decided to use icloud for now for syncing a file between Beorg to be processed into notes. On desktop, will use github to backup the exported notes until I can figure out something better for the underlying org mode files.

DONE Ignore any notes from hugo export that are tagged as private

https://github.com/alexkehayias/emacs.d/blob/master/init.el#L715

DONE Ignore any backlinks that are tagged as private

https://github.com/alexkehayias/emacs.d/blob/master/init.el#L715

DONE Update org-roam journal template to include private

(setq org-roam-dailies-capture-templates
      (quote (("d" "Default" plain (function org-roam--capture-get-point)
               "%?"
               :file-name "%(format-time-string \"%Y-%m-%d--%H-%M-%SZ--journal\" (current-time) t)"
               :head "#+HUGO_BASE_DIR: ~/Projects/zettel\n#+HUGO_SECTION: ./\n#+TITLE: %<%Y-%m-%d>\n#+ROAM_ALIAS:\n#+ROAM_TAGS: private\n"
               :unnarrowed t))))

A sub field of artificial intelligence (AI) concerned with helping agents generate valid and coherent plans of actions to reach a goal.

Approaches were divided into state space planners and planning space planners. State space would be something like ‘the door is open’ where plan space would be ‘open the door’. Generally plan space planners are faster (there tends to be fewer actions than states) to search when looking for a solution.

One limitation is that problem domains for use with planning algorithms must be known in advance. This limits the applications to domains you can fully specify and isn’t resilient to change (e.g. the actions or effects change dynamically).

Another limitation is searching for an answer tended to be slow. For example, in the least efficient case a search for a plan devolves to an exhaustive, brute force search. GraphPlan is a much faster approach that generates graph data structure that trims the search space.

Applies a result (usually favorable) to an activity e.g. learning (the activity) is valuable because of the outward effect on, for example, being better at one’s job and earning more money

See also:

• inherent value

A sociologist famed for his prolific output–he wrote 70 books and 400 scholarly articles on a wide range of topics. He came up with the Zettelkasten system as a “second brain” to work through connections of ideas.

Acclaimed author that looks at the world in a unique way that’s very entertaining.

See also:

• Interview with Tim Ferris where he talks about his approach, advice to writers, and tools

These days I wake up very early for the puppy ~5:45 AM so between getting the dogs ready and starting work I have about three hours.

I begin with a new journal entry recorded which captures recent articles I’ve read, things on my mind, and anything else (it’s not very structured). I review my short term notes and cut new notes for anything I’m interested in recalling in the future. As I write the new note I flesh out the idea some more, often going back to the source material to make sure I really understand it. This is also when I add links to existing notes. I publish the notes to this site, it’s a great feeling to publish just a little bit every day.

I do ~20 minutes of exercise, usually cardio (running or indoor biking) interspersed with low-impact yoga every two days or so. I need to do this every day to maintain my mental health and I have not missed a day in 6 months. Cardio clears my head and leaves me feeling like I did something good for myself—it’s a successful day even before I’ve done anything else.

User experience is subjective which makes improvements in UX difficult to calibrate since we need to rely more our collective taste and/or talking to users.

Are there more empirical measures of UX?

What are the nearest approximations that provide directional guidance in how to improve the experience? For example, if you lowered UX entropy would that reliably correlate with a better subjective user experience?

Talk given by Richard Hamming as part of the art of doing science and engineering course.

Transcript of the lecture via paulgraham.com

A talk given by Richard Hamming about the art of doing science and engineering.

Watch the lecture

A lecture from Richard Hamming about creativity and how to cultivate it.

Video link

See also:

• The Incomplete Guide to the Art of Discovery (Hamming mentions continental drift and tectonics as an example of knowing something, but not receiving credit until new tools existed to re-discover what was already known)

A way of predicting what a system is going to do next when you don’t have exact information (like most real-world things).

Examples: smoothing GPS location data, altitude estimation

See also:

• Detailed breakdown and illustrations of the math behind Kalman filters

Welcome to my notes! I regularly publish notes to better understand what I’ve learned and to explore new ideas. I would love to hear from you—leave a comment or reach out on Bluesky @alexkehayias.com or find me on LinkedIn.

Something that would be valuable even in the absence of outward effects e.g. knowledge is not inherently valuable—if a fact existed, but no one could ever access it, there is no value.

Similar to Neil Gaiman’s remarks about a fountain pen and writing there are ways that enhance the feeling of a craft.

Examples:

• A mechanical keyboard improves the typing experience with satisfying tactile feedback
• Fast feedback loop of making a code change and observing the result
• Tools for refactoring
• A REPL that let’s you grow your program
• Debug tools that let you better understand what’s going on

The sum of the tools (hardware and software) used while writing code is the hand feel. We don’t spend enough time thinking about the hand feel and often view it through the utilitarian lens.

What’s the fountain pen for enterprise software? Green field projects?

See also:

• Neil Gaiman’s interview with Tim Ferris

So much of technology is solving the problem of inter-operating between disparate systems e.g. cpu architectures, operating systems, language runtimes.

Humans provide the greatest interop layer unknowingly. We seamlessly work between different technologies without missing a beat. We interoperate between our desktops and mobile devices, weaving together broken legacy systems at work to operationalize a task, and speak different languages (and computer languages). We manage an enormous amount of complexity without thinking about it.

The process of generating a range input values based on some constraints to fully explore a programs handling. For example, fuzzing a function that takes a numerical value might reveal it does not properly handle negative numbers even though it’s an allowed value.

Usage examples:

• Detecting security vulnerabilities e.g. memory bugs

Disorder in a system that tends to increase over time until reaching an equilibrium. Factors of entropy include heat, time, and the number of things in the system.

Entropy is measured by the number of macro states (e.g. arrangement of molecules) the system can be in where a value of 1 would be a single state (i.e. crystal structure).

The reason discussions of social problems and correctness are difficult is because there is no safe way to fail and learn from feedback about a point of view. When someone is called out, they tend to not engage in social issues for fear of backlash or become defensive and angry, strengthening their belief.

By analyzing frontend analytics events we can derive the ‘hot paths’–sequences of actions users often take. If we also know the user’s goals we can then calculate the state space and optimal path (e.g. A* pathfinding). With that we can calculate the frequency in which users choose an optimal path.

What might the results of this kind of analysis mean for the user experience?

• A high cardinality of unique paths to a goal might reveal there are too many ways to do the same thing
• A large percentage of users on an suboptimal path could indicate an opportunity to help users perform an action faster

See also:

• Measuring UX

Researcher who focuses on how to improve the productivity of knowledge workers.

Works:

• Quantum country, an experiment on reading retention and spaced repetition

See also:

• Zettelkasten (Andy has a system of networked notes he pieced together with Evernote and some scripts)

Transforms a language into data by lexing (separating the words into a sequence of tokens) and parsing (applying syntactical rules to the tokens).

Once in a data structure, you can programatically analyze or even modify the language by iterating over the tokens.

Examples:

• Writing a linter for TypeScript
• Detecting usage of unsafe in Rust crates