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** [[file:daily/2026-05-01.org][2026-05-01]] ** [[file:daily/2026-05-01.org][2026-05-01]]
** [[file:daily/2026-05-05.org][2026-05-05]] ** [[file:daily/2026-05-05.org][2026-05-05]]
** [[file:daily/2026-05-06.org][2026-05-06]] ** [[file:daily/2026-05-06.org][2026-05-06]]
** [[file:daily/2026-05-12.org][2026-05-12]]

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#+filetags: :books:org:index: #+filetags: :books:org:index:
#+DATE: 2025-05-19 #+DATE: 2025-05-19
#+STARTUP: content #+STARTUP: content
#+PROPERTY: GENERATED_AT 2026-05-08T00:00:01.448061 #+PROPERTY: GENERATED_AT 2026-05-12T00:00:01.126654
* Career * Career
** Clean Code_ A Handbook of Agile Software Craftsmanship - Robert C. Martin :Read: ** Clean Code_ A Handbook of Agile Software Craftsmanship - Robert C. Martin :Read:

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- The Unix Programming Environment by Brian W. Kernighan and Rob Pike - The Unix Programming Environment by Brian W. Kernighan and Rob Pike
- An Introduction to Programming in Emacs Lisp by Robert J. Chassell - An Introduction to Programming in Emacs Lisp by Robert J. Chassell
- GNU Emacs Manual by Richard M, Stallman - GNU Emacs Manual by Richard M, Stallman
* [[https://search.brave.com/search?q=co+intelligence&summary=1&conversation=091312e416c3bbb83c6c6ccc2d0cd4d40875][Co-Intelligence: Living and Working with AI]]

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@@ -11,8 +11,10 @@ In this node lies notes relating to theoretical concepts tying with maths and/or
** ESS ** ESS
- [[id:abe43fdc-e90d-4c2c-9320-cc7929f0c99a][ESS]] - [[id:abe43fdc-e90d-4c2c-9320-cc7929f0c99a][ESS]]
- [[id:0b6e7dc0-1171-4dc4-982e-a5d95765e09c][SEB Search Improvement — Couchbase Caching]] - [[id:0b6e7dc0-1171-4dc4-982e-a5d95765e09c][SEB Search Improvement — Couchbase Caching]]
** AI Training:
- [[id:ceeb2ad1-b091-49d8-8cd6-752f28a6fd86][Data Camp AI Training]]
* Mathematical Concepts * Mathematical Concepts
Part of being a software engineer is having a good grasp of mathematical concepts. Here are some notes on various mathematical concepts that I find useful. Part of being a software engineer is having a good grasp of mathematical concepts. Here are some notes on various mathematical concepts that I find useful.

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:PROPERTIES:
:ID: ceeb2ad1-b091-49d8-8cd6-752f28a6fd86
:END:
#+title: Data Camp AI Training
#+filetags: :concepts:notes:career:ai:
*TITLE: Introduction to AI for Work*
* Summary
** Learning Machines
**AI Fundamentals**
- Artificial intelligence enables computer systems to perform tasks typically associated with human intelligence, such as learning, reasoning, and decision-making.
- AI has actually been around for many years and is already integrated into your daily life in ways you might not have realized.
**Traditional Programming**
- Before modern AI, engineers created intelligent systems by explicitly programming step-by-step procedures.
- The challenge is that for many important tasks, we simply can't spell out the procedure—a human expert may excel but can't articulate the instructions for a computer.
**Machine Learning**
- Instead of programming step-by-step procedures, machine learning enables computers to learn from examples.
- AI fundamentally works through pattern recognition..
- During Training: The system recognizes and learns patterns from examples.
- During Operation: The trained system receives new cases and compares them against the patterns it learned during training to make decisions.
** Generative AI
**The Generative AI Breakthrough**
- While AI researchers have been making steady progress for decades, late 2022 was the tipping point when systems like ChatGPT became good enough for public release.
- Generative AI systems generate new content rather than simply analyzing existing information.
**Large Language Models**
- Large Language Models (LLMs) are the most important type of generative AI for your work—the technology powering tools like ChatGPT, Claude, and Gemini.
- They can communicate fluently in natural language. More importantly they exhibit common sense and logical reasoning capabilities.
**How LLMs Work**
- Large Language Models (LLMs) work like other machine learning systems. They learn patterns from data during training.
- What makes them special is scale. Theyre trained on huge amounts of text from the internet, books, articles, and more.
- Because of this broad training, they can handle many different kinds of tasks — writing, summarizing, coding, explaining, etc.
- When you give them a prompt or question, they use learned patterns to generate a fitting response.
**Beyond Language Models**
- Generative AI also includes systems that create and modify images, as well as video.
- Image generation is a key capability for many professionals, including marketing, product design, and documentation.
- Video generation is a new frontier in AI, but it's already being used for training materials and marketing videos.
** The Opportunity
**Understanding AI at Work**
- Today's AI systems excel at doing tasks, not taking over entire jobs.
- AI doesn't boost productivity on all tasks—only those within AI's capability boundaries where it provides significant value.
- Even for tasks where AI helps, producing useful output requires human oversight and judgment.
**The Real Opportunity**
- AI is raising the bar for what any professional should be able to accomplish.
- The real question isn't "Will AI take my job?" but "Will I be one of the people who can work effectively with AI?"
**Significant Benefits**
- When used effectively within its capability boundaries, AI helps you accomplish significantly more, at higher quality, while making work more engaging.
- Most professionals aren't leveraging AI well yet. By being here, you're setting yourself up to be ahead.
** How AI Can Help You
**Execution**
- AI excels at executing knowledge work tasks where you know what needs to be done and the work is at a level you'd delegate to a capable junior teammate
- In practice: You provide clear instructions, AI carries it out, you review the output
- This dramatically reduces time on routine tasks and frees you for higher-value work
**Thought Partnership**
- AI serves as an exceptional brainstorming partner when you don't know what needs to be done—like turning to a creative colleague to think through tough problems
- Particularly effective for diagnosing unclear problems, exploring solution possibilities, and weighing difficult decisions
- Make it a habit to bring AI to the table when facing complex challenges
**Refinement**
- AI helps you improve your work by providing high-quality, objective feedback—pointing out weaknesses and suggesting concrete improvements
- In practice: Share your work, specify what feedback you need, and AI provides specific suggestions
- Make it a habit to seek feedback from AI on your work
**Continuous Learning**
- AI can explain any concept clearly and immediately, adapting its approach until it clicks for you
- AI is an effective teacher: adjusts to your level, welcomes all questions without judgment, and is always available
- Note: AI cannot replace structured learning programs that require expert-designed progressions and hands-on practice
** Working with AI Effectively
**Core Collaboration Principles**
- Think of working with AI as collaborating with a colleague rather than using a tool. This collaboration mindset underlies everything about working effectively with AI.
- Communicate Effectively:
- Use clear, unambiguous language—no special phrases or magic words are required.
- Give AI sufficient detail to accomplish the task successfully.
- Iterate: AI's first output is rarely perfect. Continue the conversation and guide AI toward what you need through multiple rounds of feedback.
**Communication Framework**
- The Ask: What exactly do you want the AI to do? Be specific and clear about the task or outcome.
- The Requirements: What does the output need to satisfy? Include focus, boundaries, format, style, and other specific needs.
- The Context: What does AI need to know about your specific situation? Why you need this, how it will be used, and relevant background details.
- The Examples (optional): What does success look like? Show the AI what you want through concrete examples—especially valuable for visual/structural requirements ( format, layout) and qualitative/subjective requirements (style, tone, quality standards).
**The Practical Test**
- If you walked your request to a competent junior teammate, can they complete the task with the information you provided? If not, AI probably can't either.
**Practical Tactics**
- Content over polish: Focus on including the right information (ask, requirements, context) rather than perfecting the writing. AI handles spelling mistakes, broken sentences, and disorganized thoughts—what matters is having the key details, not perfect prose.
- Start simple and build: Begin with a basic request and add more detail based on what you get back. Don't stress about getting everything right upfront.
- Ask AI what it needs: If unsure what information to provide, ask directly: "What would you need to know to help me with this?"
- Use different modalities: Dictate your requests, provide screenshots or photos, or mix text, voice, and images as needed.
**Practice**
- The best way to get better at using AI is to use AI.
- Start with low-stakes tasks where you can experiment without pressure.
** Working with AI Responsibly
**AI's Limitations**
- Knowledge fabrication: AI can confidently produce false information that sounds completely plausible
- Recency ignorance: AI works with outdated knowledge from its training period
- Biased outputs: AI can unfairly favor or underrepresent certain groups, viewpoints, or aesthetics
- Sycophantic outputs: AI tends to tell you what it thinks you want to hear
**Why These Happen**
- These limitations result from AI's training data, training process, and pattern-matching approach
- AI labs are actively improving these issues with each generation, but they haven't been eliminated
- Your judgment and oversight remain irreplaceable safeguards when using AI
**Review AI Outputs**
- Maintain critical assessment and healthy skepticism with AI outputs
- Verify factual claims (dates, statistics, citations, technical details, recent information)
- Ask AI to search the web and cite sources, especially for factual or recent information
- Watch for bias: Are perspectives missing? Would this be fair to all affected groups?
- Watch for sycophancy: Is AI telling me what I want to hear?
- Calibrate scrutiny to stakes (more rigorous for high-stakes decisions)
**Seek Critical Perspectives**
- Counter bias: Ask AI to consider different viewpoints ("What perspectives might be missing?" "How might this affect different groups differently?")
- Counter sycophancy: Explicitly request critical feedback ("What are the weaknesses?" " What could go wrong?" "What assumptions might be wrong?")
- For important decisions, consult people from diverse backgrounds who can offer genuine pushback
**Privacy Risks**
- Conversations may become training data; databases can be breached
- Follow organizational policies and avoid sharing sensitive information
- You can usually achieve your goal without exposing private details—use generic examples or anonymized data instead
- Use privacy protections (enterprise versions, private modes, opt-out settings)

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* Bruno * Bruno
Bruno is used for testing the backend API endpoints. It is a simple HTTP client that allows you to send requests to the backend and view the responses. I used the OpenAPI specification to generate Bruno tests for each endpoint. Bruno is used for testing the backend API endpoints. It is a simple HTTP client that allows you to send requests to the backend and view the responses. I used the OpenAPI specification to generate Bruno tests for each endpoint.
* Authentication
The backend exposes public ~/api/auth/register~ and ~/api/auth/login~ endpoints. The website has a login page only; users are created through the API, then the login page stores the returned JWT in the browser.
Protected requests include:
#+begin_src text
Authorization: Bearer <jwt-token>
#+end_src
* Future? * Future?
** Integration with ~notes.zainezq.com~ ** Integration with ~notes.zainezq.com~
As the API is primarily used by ~zainezq.com~, I want to think of ways that ~notes.zainezq.com~ could also use it. This website is used to store all my notes, and they are exported using ~org-publish~ in Emacs. Perhaps I could write an Emacs Lisp package that interacts with the backend API to store and retrieve notes. As the API is primarily used by ~zainezq.com~, I want to think of ways that ~notes.zainezq.com~ could also use it. This website is used to store all my notes, and they are exported using ~org-publish~ in Emacs. Perhaps I could write an Emacs Lisp package that interacts with the backend API to store and retrieve notes.

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#+title: Cloudflare #+title: Cloudflare
#+filetags: :cloudflare:server:networking: #+filetags: :cloudflare:server:networking:
* Go to: https://dash.cloudflare.com/49b791cb8f903fdcab3db1cfa124321b/one/access-controls/apps
This is to edit the access control in the zero trust cloudflare.
* Origin certificate * Origin certificate
#+begin_src #+begin_src
-----BEGIN CERTIFICATE----- -----BEGIN CERTIFICATE-----

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#+AUTHOR: Auto-generated #+AUTHOR: Auto-generated
#+filetags: :recipes:cooking:org:index: #+filetags: :recipes:cooking:org:index:
#+STARTUP: content #+STARTUP: content
#+PROPERTY: GENERATED_AT 2026-05-08T00:00:03.010501 #+PROPERTY: GENERATED_AT 2026-05-12T00:00:01.985436
# How to add notes: under any recipe heading, add :COOKED: <date> to record when you made it, and :TIPS: your tip text to add notes. # How to add notes: under any recipe heading, add :COOKED: <date> to record when you made it, and :TIPS: your tip text to add notes.
# Multiple :COOKED: lines are supported. These are preserved across regenerations. # Multiple :COOKED: lines are supported. These are preserved across regenerations.

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"id": "10483553-b547-47ce-835d-8222441b35ca", "id": "10483553-b547-47ce-835d-8222441b35ca",
"title": "2026-05-06", "title": "2026-05-06",
"url": "/daily/2026-05-06.html" "url": "/daily/2026-05-06.html"
},
{
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"title": "2026-05-12",
"url": "/daily/2026-05-12.html"
} }
], ],
"A": [ "A": [
@@ -241,6 +246,11 @@
"title": "Daily Notes MOC", "title": "Daily Notes MOC",
"url": "/20260421100223-dailies.html" "url": "/20260421100223-dailies.html"
}, },
{
"id": "ceeb2ad1-b091-49d8-8cd6-752f28a6fd86",
"title": "Data Camp AI Training",
"url": "/20260512121806-data_camp_ai_training.html"
},
{ {
"id": "e448cd99-afee-4702-947f-644bb34dc1aa", "id": "e448cd99-afee-4702-947f-644bb34dc1aa",
"title": "Database MOC", "title": "Database MOC",

12
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:PROPERTIES:
:ID: e69fd1ff-562d-4bb3-a27b-96d29ac5f56a
:END:
#+title: 2026-05-12
* https://en.alukah.net/shariah/1/5657/
* https://archive.org/details/MaidensOfJannah/page/n31/mode/2up
Maidens Of Jannah
by Abdullah Nana
* https://www.booking.com/hotel/gb/voco-st-johns-solihull.en-gb.html?aid=304142&label=gen173nr-10CAEoggI46AdIM1gEaFCIAQGYATO4ARfIAQzYAQPoAQH4AQGIAgGoAgG4AtDbjNAGwAIB0gIkMWM1ZGRmNTQtMDI3My00YTIyLTlkMDMtZDkxY2I5ZDgzODcz2AIB4AIB&sid=f49a9ab900609169e59c1aca6159ea89&all_sr_blocks=3564558_95157122_2_34_0&checkin=2026-08-14&checkout=2026-08-17&dest_id=2638&dest_type=region&dist=0&group_adults=2&group_children=0&hapos=18&highlighted_blocks=3564558_95157122_2_34_0&hpos=18&matching_block_id=3564558_95157122_2_34_0&nflt=ht_id%3D204&no_rooms=1&req_adults=2&req_children=0&room1=A%2CA&sb_price_type=total&sr_order=popularity&sr_pri_blocks=3564558_95157122_2_34_0__26900&srepoch=1778594232&srpvid=bbf4605193671898&type=total&ucfs=1&
* https://www.booking.com/hotel/gb/novotelbirmingham.html?ssne=Birmingham&ssne_untouched=Birmingham&highlighted_hotels=219993&ss=Birmingham&dest_id=-2589989&dest_type=city&hp_avform=1&origin=hp&do_availability_check=1&label=brave_brand_organic_trigger_368e70e6-53f0-4cac-a7ac-7bbafac5437e_0&aid=2405329&lang=en-gb&sb=1&src_elem=sb&src=hotel&checkin=2026-08-21&checkout=2026-08-24&group_adults=2&no_rooms=1&group_children=0#availability_target
* https://www.booking.com/hotel/gb/ac-birmingham-marriott-lifestyle.html?ssne=Birmingham&ssne_untouched=Birmingham&highlighted_hotels=218128&ss=Birmingham&dest_id=-2589989&dest_type=city&hp_avform=1&origin=hp&do_availability_check=1&label=brave_brand_organic_trigger_368e70e6-53f0-4cac-a7ac-7bbafac5437e_0&aid=2405329&lang=en-gb&sb=1&src_elem=sb&src=hotel&checkin=2026-08-21&checkout=2026-08-24&group_adults=2&no_rooms=1&group_children=0#availability_target
* https://www.booking.com/hotel/gb/burlingtonhotel.html?ssne=Birmingham&ssne_untouched=Birmingham&highlighted_hotels=117739&ss=Birmingham&dest_id=-2589989&dest_type=city&hp_avform=1&origin=hp&do_availability_check=1&label=brave_brand_organic_trigger_368e70e6-53f0-4cac-a7ac-7bbafac5437e_0&aid=2405329&lang=en-gb&sb=1&src_elem=sb&src=hotel&checkin=2026-08-21&checkout=2026-08-24&group_adults=2&no_rooms=1&group_children=0#availability_target

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Cleaning output directory...
rm -rf output/
Generating the JSON output...
/usr/bin/python3 search-index.py
Generating search-index.json with links...
search-index.json generated (177 entries).
Loaded 177 entries from /home/zaine/master-folder/org_files/org_roam/output/search-index.json
all-files.json generated → /home/zaine/master-folder/org_files/org_roam/all-files.json
Building project (full rebuild with search index)...
emacs -Q --script lisp/build.el
Emergency (magit): Magit requires transient >= 0.13,
but due to bad defaults, Emacs package manager, refuses to
upgrade this and other built-in packages to higher releases
from GNU Elpa.
To fix this, you have to add this to your init file:
(setq package-install-upgrade-built-in t)
Then evaluate that expression by placing the cursor after it
and typing C-x C-e.
Once you have done that, you have to explicitly upgrade transient:
M-x package-install transient RET
Then you also must make sure the updated version is loaded,
by evaluating this form:
(progn (unload-feature 'transient t) (require 'transient))
If this does not work, then try uninstalling Magit and all of its
dependencies. After that exit and restart Emacs, and only then
reinstalling Magit.
If you dont use the package package manager but still get
this warning, then your chosen package manager likely has a
similar defect.
Loading /home/zaine/master-folder/org_files/org_roam/lisp/macros.el (source)...
Starting full rebuild at 2026-05-09 01:24:23
🎬 Scanning /home/zaine/master-folder/org_files/org_roam/assets/ for .mov files…
(no .mov files found)
✅ Full rebuild complete in 9.68 seconds
Generating the JSON output 2...
/usr/bin/python3 generate_sidebar_tree.py
Generating sidebar-tree.json...
sidebar-tree.json generated (11 folders, 177 files)
→ /home/zaine/master-folder/org_files/org_roam/output/assets/sidebar-tree.json