feat

ADGEfficiency · ADGEfficiency · commit 64a4ee0fefdb · 2025-10-11T01:54:55.000+13:00
diff --git a/README.md b/README.md
@@ -178,6 +178,8 @@ Honeypot documentaries:
 
 [Falsehoods Programmers Believe About Falsehoods Lists](https://kevin.deldycke.com/2016/12/falsehoods-programmers-believe-about-falsehoods-lists/)
 
+[Falsehoods programmers believe about time, in a single list](https://gist.github.com/timvisee/fcda9bbdff88d45cc9061606b4b923ca)
+
 ## Blogs & Blog Posts
 
 [Test Double | Insights and Blogs](https://testdouble.com/insights)
@@ -443,6 +445,10 @@ Nicolas Loizeau
 
 ## Courses
 
+[Computer Science from the Bottom Up](https://bottomupcs.com/index.html)
+
+[Composing Programs](https://www.composingprograms.com/)
+
 [CSE 20289 - Systems Programming](https://www3.nd.edu/~pbui/teaching/cse.20289.sp20/)
 
 [codecrafters-io/build-your-own-x](https://github.com/codecrafters-io/build-your-own-x) - master programming by recreating your favorite technologies from scratch.
diff --git a/bash-and-unix/README.md b/bash-and-unix/README.md
@@ -62,6 +62,10 @@ Concise GNU Bash: An Introduction to Advanced Usage - James Panacciulli @ LinuxF
 
 [The Challenges of Integrating the Unix and Mac OS Environments](https://www.usenix.org/legacy/publications/library/proceedings/usenix2000/invitedtalks/sanchez_html/sanchez.html)
 
+### Interactive
+
+[Command Challenge!](https://cmdchallenge.com/)
+
 ### Courses
 
 [DataCamp Introduction to Shell for Data Science - Datacamp Course](https://www.datacamp.com/courses/introduction-to-shell-for-data-science)
diff --git a/clis.md b/clis.md
@@ -1,5 +1,9 @@
 [Things I’ve learned about building CLI tools in Python](https://simonwillison.net/2023/Sep/30/cli-tools-python/)
 
+Consistency is everything 
+
+Include usage examples in --help
+
 [Command Line Interface Guidelines](https://clig.dev/)
 
 [Building the future of the command line](https://github.com/readme/featured/future-of-the-command-line)
diff --git a/computer-science/README.md b/computer-science/README.md
@@ -29,3 +29,5 @@ To get started, I recommend the following resources:
 [Operational transformation - Wikipedia](https://en.wikipedia.org/wiki/Operational_transformation) - a technology for supporting a range of collaboration functionalities in advanced collaborative software systems. OT was originally invented for consistency maintenance and concurrency control in collaborative editing of plain text documents.
 
 [E.W. Dijkstra Archive: On the cruelty of really teaching computing science †EWD 1036‡ - EWD1036.v4.pdf](https://www.psy.gla.ac.uk/~steve/educ/dijk/EWD1036.v4.pdf)
+
+[Open Data Structures (in pseudocode)](https://opendatastructures.org/ods-python/)
diff --git a/data-science/anomaly-outlier-detection.md b/data-science/anomaly-outlier-detection.md
@@ -86,7 +86,7 @@ modified_z_score = 0.6745 * (x - median) / mad
 
 Masking - outliers causing other outliers not to be detected
 
-Swamping - outliers outliers causing other outliers to be detected when they shouldn't
+Swamping - outliers causing other outliers to be detected when they shouldn't
 
 Masking & swamping can occur with other methods
 
@@ -144,7 +144,6 @@ Visualizing
 Boxplots bad with multimodal data
 
 Categorical
-
 - rare combinations based on absolute count
 - rare combinations based on marginal probabilities
 
@@ -297,7 +296,6 @@ Tree data structures again
 
 [RnR - bunch of other detectors]
 
-
 # Other Libraries
 
 alibi-detect library - https://github.com/SeldonIO/alibi-detect
diff --git a/data-science/visualization.md b/data-science/visualization.md
@@ -1,3 +1,4 @@
+
 One chart = one takeaway: when looking at your chart, I should be able to infer your message in a snap
 
 Names in US over time - [gif](https://i.imgur.com/DQ2Jhp3.gif)
@@ -13,6 +14,50 @@ Matplotlib Tips and Demos - [notebook](http://nbviewer.jupyter.org/urls/gist.git
 
 [cxli233/FriendsDontLetFriends](https://github.com/cxli233/FriendsDontLetFriends) - Friends don't let friends make certain types of data visualization - What are they and why are they bad.
 
+[A Guide To Getting Data Visualization Right — Smashing Magazine](https://www.smashingmagazine.com/2023/01/guide-getting-data-visualization-right/)
+
+In the field of data visualization, there are four largely accepted categories of data visualization that relate to different purposes:
+
+1. Comparison
+2. Composition
+3. Distribution
+4. Relationship
+
+Some charts can fall into multiple categories
+
+[10 Years of Open-Source Visualization](https://observablehq.com/@mbostock/10-years-of-open-source-visualization)
+
+Teaching is the most impactful aspect of tool building
+- Documentation, tutorials, and especially examples scale knowledge transfer
+- Examples inspire and teach but can foster copy-paste dependency instead of fluency
+
+Support is a powerful means of research
+- Helping users reveals flaws and gaps in understanding
+- Q&A interactions inspire new features and tutorials
+- Danger of burnout: can’t help everyone, and issue trackers can be overwhelming
+
+Beware bells and whistles: interaction, animation, and other technical whizbangery have a cost
+- High “wow factor” but adds complexity and can hide insights
+- Static graphics often communicate better
+- Interaction works best in exploratory contexts, not explanatory
+
+Visualization is a spectrum: from exploratory to explanatory
+- Exploratory = for finding insights quickly, can cut corners
+- Explanatory = for communicating insights clearly, must provide context
+- Designers should know where on the spectrum they are working
+
+In most cases, working with data should be 80% of the work
+- Data cleaning, joining, and modeling are the hardest parts
+- Visualization often gets disproportionate credit compared to data wrangling
+
+10% of code causes 90% of bugs
+- Bug-prone areas are those with asynchronous, interactive behavior (zoom, drag, brush)
+
+Don’t go it alone
+- Build a trusted group of peers for validation and support
+- Collaborative spaces (like Observable) help avoid isolation
+- Counteracts the negative impact of online criticism
+
 ## Cool visualizations
 
 [Electoral College Decision Tree / Observable | Observable](https://observablehq.com/@observablehq/electoral-college-decision-tree)
@@ -42,3 +87,5 @@ https://www.d3-graph-gallery.com/
 docs - https://docs.streamlit.io/en/stable/
 
 [random axis: A Subway Map of Maps That Use Subway Maps as a Metaphor](https://randomaxis.blogspot.com/2012/10/a-subway-map-of-maps-that-use-subway.html)
+
+
diff --git a/docker/README.md b/docker/README.md
@@ -90,3 +90,5 @@ Docker starts to become super useful when you have an application you are deploy
 1) elasticsearch, if you need real-time indexing and search capabilities. Alternatively you can just spin up a dedicated API that leverages full text search for your database container from 3)
 
 I prefer docker compose to Kubernetes because I am not a megacorp. You just define your different services, let them run, expose the right ports, and then things should "just work"
+
+[Best Practices Around Production Ready Web Apps with Docker Compose — Nick Janetakis](https://nickjanetakis.com/blog/best-practices-around-production-ready-web-apps-with-docker-compose)
diff --git a/git-github/git.md b/git-github/git.md
@@ -336,6 +336,8 @@ Why git repos would struggle with large binary files: as every change is stored
 
 [Things I think everyone should know about Git](https://perl.plover.com/classes/git-tips/) - [Things I wish everyone knew about Git (Part II)](https://blog.plover.com/prog/git/tips-2.html)
 
+[Git from the Bottom Up](https://jwiegley.github.io/git-from-the-bottom-up/)
+
 ## Criticism
 
 [What’s wrong with Git? A conceptual design analysis](https://blog.acolyer.org/2016/10/24/whats-wrong-with-git-a-conceptual-design-analysis/)
diff --git a/languages/go.md b/languages/go.md
@@ -46,6 +46,14 @@ Go language design philosophy debate
 
 ---
 
+## Go for Python Devs
+
+dev tools
+
+no default values in functions
+
+no keyword arguments when calling a function
+
 ## Learning Go
 
 [10 week plan to master Go: GetStream’s onboarding plan : r/golang](https://www.reddit.com/r/golang/comments/1eiea6q/10_week_plan_to_master_go_getstreams_onboarding/?share_id=0YbvpMNHBGrElxcp8jznD&utm_name=androidcss)
diff --git a/lessons-learnt/lessons-learnt.md b/lessons-learnt/lessons-learnt.md
@@ -1,3 +1,5 @@
+[Essays on programming I think about a lot | benkuhn.net](https://www.benkuhn.net/progessays/)
+
 ["Yes, Please Repeat Yourself" and other Software Design Principles I Learned the Hard Way : r/programming](https://www.reddit.com/r/programming/comments/1cckf07/yes_please_repeat_yourself_and_other_software/?share_id=xGL4Z8cYSQZXJjUNUmMkE&utm_name=androidcss)
 
 [Good software development habits | Zarar's blog](https://zarar.dev/good-software-development-habits/) - [Good software development habits : r/programming](https://www.reddit.com/r/programming/comments/1fdkv8n/good_software_development_habits/?share_id=gGIZJ7lIneZA4WErZcuYT&utm_name=androidcss) - [Good Software Development Habits | Hacker News](https://news.ycombinator.com/item?id=42165057)
diff --git a/llms/README.md b/llms/README.md
@@ -18,6 +18,8 @@ The LoRA method works by attaching extra trainable parameters into a model(that
 
 [A statistical approach to model evaluations \ Anthropic](https://www.anthropic.com/research/statistical-approach-to-model-evals)
 
+[Frequently Asked Questions (And Answers) About AI Evals – Hamel’s Blog](https://hamel.dev/blog/posts/evals-faq/)
+
 ## Codellama
 
 [Code Llama: Llama 2 learns to code](https://huggingface.co/blog/codellama)
@@ -74,3 +76,28 @@ That said, it's still a gamechanger that I can do it at all.
 3. I am a bit more hyped than the author that this is a game changer, but like them, I don't think it's going to be the end of the world. There are some jobs that are going to be heavily impacted and I think we are going to have a rough few years of bots astroturfing platforms. But all in all I think it's more of a force multiplier rather than a breakthrough like the internet.
 
 IMHO it's similar to what happened to DevOps in the 2000s, you just don't need a big special team to help you deploy anymore, you hire a few specialists and mostly buy off the shelf solutions. Similarly, certain ML tasks are now easy to implement even for dumb dumb web devs like me. 
+
+---
+
+[Tao on “blue team” vs. “red team” LLMs | Hacker News](https://news.ycombinator.com/item?id=44711306)
+
+Blue team (generative/constructive) creates initial output while red team (critical/evaluative) finds flaws and weaknesses
+- This pattern exists in mathematical proof creation vs checking, software development vs testing, and other domains
+- LLMs may be better suited for red team roles due to their unreliability - unreliable contributors cause less damage when attacking than when defending
+
+Fundamental asymmetry between offensive and defensive roles
+- Defensive systems only as strong as weakest component - single vulnerability can compromise entire system
+- Offensive systems benefit from multiple attack vectors - only need one successful approach
+- This asymmetry suggests placing unreliable AI tools in red team roles minimizes potential damage
+
+Testing philosophy and quality concerns dominate discussion
+- Legacy codebases suffer when tests become source of truth but may document bugs as features
+- Brittle tests slow development by requiring maintenance on every code change regardless of functional impact
+- Many enterprise testing practices generate bureaucratic overhead without meaningful safety improvements
+- Human review remains essential for distinguishing meaningful behavioral requirements from implementation artifacts
+
+Economic and organizational dynamics shape AI adoption
+- Organizations may use AI to accelerate low-value bureaucratic tasks rather than improve core outcomes
+- Productivity gains often illusory when applied to pointless work that scales infinitely
+- Capital allocation favors blue team AI applications despite red team potentially being more suitable
+- Quality of AI assistance correlates with user expertise - top performers benefit while others produce lower quality work
diff --git a/llms/coding-tools.md b/llms/coding-tools.md
@@ -1,3 +1,5 @@
+[hesreallyhim/awesome-claude-code: A curated list of awesome commands, files, and workflows for Claude Code](https://github.com/hesreallyhim/awesome-claude-code)
+
 [Field Notes From Shipping Real Code With Claude - diwank's space](https://diwank.space/field-notes-from-shipping-real-code-with-claude)
 
 Never let AI write tests
diff --git a/llms/prompt-engineering.md b/llms/prompt-engineering.md
@@ -1,3 +1,69 @@
+ask for plan
+
+relevant to interative prompting sessions
+
+prompt eng = mostly about context
+
+the most useful thing you can add to any prompt is relevant context
+
+even if llm has been trained on something, adding additional info about that thing might help
+
+imagine how useful it is when you add stuff that it was never trained on?
+
+## LLMs are Random
+
+temperature
+
+model weights can change
+
+cloud infra problems - optimizations that break model quality intermittently
+
+-> each session is independent, and you should expect behaviour to change over time
+
+## Context Window is not all made equal
+
+## Context
+
+- bring in documentation
+
+## Examples
+
+## Repeat Important Bits (top & bottom of prompt)
+
+## Kill poisoned sessions
+
+## scrap / not sure
+
+what to ask for
+- do the task
+- build a tool to do the tasks
+
+good engineers build tools, so should LLMs
+
+---
+
+[Prompting 101 | Code w/ Claude](https://youtu.be/ysPbXH0LpIE?si=WPLISRdrYsLRbpHo)
+
+Separate sections with `<guide> <example>` etc
+
+Task context
+
+Tone context
+
+Background data, documents, images
+
+Detailed task description & rules
+
+Examples
+
+Conversation history
+
+Immediate task description or request
+
+Output formatting
+
+Prefilled response
+
 [anthropics/prompt-eng-interactive-tutorial: Anthropic's Interactive Prompt Engineering Tutorial](https://github.com/anthropics/prompt-eng-interactive-tutorial)
 
 [(336) AI prompt engineering: A deep dive - YouTube](https://www.youtube.com/watch?v=T9aRN5JkmL8&t=877s)
@@ -27,7 +93,7 @@ do this
 
 but don't do this
 
-return format 
+return format
 ```
 
 [Prompt Engineering Guide](https://www.promptingguide.ai/)
@@ -89,7 +155,7 @@ Examples [optional]
 [Optional: 1-3 well-defined examples with placeholders if necessary. Clearly mark where examples start and end, and what the input and output are. User placeholders as necessary.] [If the examples are shorter than what a realistic example is expected to be, make a reference with () explaining how real examples should be longer / shorter / different. AND USE PLACEHOLDERS! ]
 Notes [optional]
 
-[optional: edge cases, details, and an area to call or repeat out specific important considerations] 
+[optional: edge cases, details, and an area to call or repeat out specific important considerations]
 ```
 
 ---
@@ -102,7 +168,7 @@ In what pre-ChatGPT world did "write clearly and provide ample information" incl
 
 * Specify the desired length of the output
 
-It's able to infer through quite a large amount of sloppiness. The much larger gains come from guiding it into a model of the world, as opposed to direct it to respond to lean perspectives like, "What do I eat to be better?" 
+It's able to infer through quite a large amount of sloppiness. The much larger gains come from guiding it into a model of the world, as opposed to direct it to respond to lean perspectives like, "What do I eat to be better?"
 
 ---
 
@@ -119,15 +185,15 @@ All of these best practices are great for managers dealing with their staff as w
 3. Split complex tasks into simpler subtasks
 4. Give time to "think"
 5. Use external tools
-6. Test changes systematically 
+6. Test changes systematically
 
 ---
 
 I find that working with LLMs feels closer to the skills of managing a team than to coding itself. Intuitions about how to divide work and understanding strengths and limitations seem to go far.
 
 ---
 
-That's a really cool insight-- it's not coding. It's dispatching tasks to a team 
+That's a really cool insight-- it's not coding. It's dispatching tasks to a team
 
 ---
 
@@ -174,7 +240,7 @@ There's an unfortunately common take on AI that goes basically like this:
 
 "I tried it and it didn't do what I wanted, not impressed."
 
-My suggestion is to tune out the noise and really try experimenting with these tools – and know that they're rapidly improving. Even if ultimately you have criticisms or decide one way or another, at least really investigate them for your own use-cases rather than jumping on a bandwagon that's either "AI is bad" or the breathless hype-machine at the other end. 
+My suggestion is to tune out the noise and really try experimenting with these tools – and know that they're rapidly improving. Even if ultimately you have criticisms or decide one way or another, at least really investigate them for your own use-cases rather than jumping on a bandwagon that's either "AI is bad" or the breathless hype-machine at the other end.
 
 ---
 
diff --git a/python/advanced.md b/python/advanced.md
diff --git a/security.md b/security.md
diff --git a/web-development/README.md b/web-development/README.md
diff --git a/web-development/htmx.md b/web-development/htmx.md

Original file line number	Diff line number	Diff line change
`@@ -1,3 +1,5 @@`
	`1`	`+[Essays on programming I think about a lot \| benkuhn.net](https://www.benkuhn.net/progessays/)`
	`2`	`+`
`1`	`3`	`["Yes, Please Repeat Yourself" and other Software Design Principles I Learned the Hard Way : r/programming](https://www.reddit.com/r/programming/comments/1cckf07/yes_please_repeat_yourself_and_other_software/?share_id=xGL4Z8cYSQZXJjUNUmMkE&utm_name=androidcss)`
`2`	`4`
`3`	`5`	`[Good software development habits \| Zarar's blog](https://zarar.dev/good-software-development-habits/) - [Good software development habits : r/programming](https://www.reddit.com/r/programming/comments/1fdkv8n/good_software_development_habits/?share_id=gGIZJ7lIneZA4WErZcuYT&utm_name=androidcss) - [Good Software Development Habits \| Hacker News](https://news.ycombinator.com/item?id=42165057)`