Skip to main content

52 week money challenge: select a week version

I'm guessing you already read 52 week money challenge and it's reversed version.

Now comes another version since I don't have the patience to be steady(except when driving).

I call it: Select-A-Week version

How it works?


  1. Just choose the amount depending on what you have and what's highest amount that week
  2. Set aside the amount
  3. Cross out the week
  4. Wait for another week
  5. Repeat.
Let's take the chart below as an example


If this week, you were able to save Php300, then cross out the 7/25/2014. So, you don't have to just set aside Php50.00. The bigger you set aside, the easier it will be to save in the future. The following week, you were able to save Php1000.00 then cross out 10/31/2014. Now, you have Php300.00 and Php1000.00 crossed out. Let's say you save another Php300.00 the following week, since you already crossed the Php300.00, you'll just have to cross out Php250.00. That leaves you extra Php50.00, which you can also cross out or spend depending on what you fancy.

Happy Saving!
Labels:

Popular

Contextual Stratification - Chapter 21: No Theory of Everything

  The Most Seductive Dream There is a dream that haunts physics, philosophy, and the human imagination itself: one equation. One framework. One truth that explains everything. Einstein spent the last decades of his life searching for it, a unified field theory that would reconcile gravity with electromagnetism, that would show all forces as manifestations of a single underlying reality. He failed, but the dream didn't die. String theory arose promising eleven dimensions and one fundamental entity, vibrating strings from which all particles and forces emerge. Loop quantum gravity offered another path. M-theory suggested a framework encompassing all frameworks. The quest continues. Physicists still seek the Theory of Everything (TOE) the final equation that would subsume quantum mechanics and relativity, explain all particles and forces, predict all phenomena. The dream is powerful because it promises ultimate understanding. No more mysteries. No more competing frameworks. No more b...
Read more

Agile Transportation System (ATS) Values and Principles

Here’s a draft of the Agile Transportation System (ATS) Values and Principles. ATS Core Values Adaptability Over Rigidity - ATS prioritizes flexible route adjustments and dynamic scheduling based on real-time demand rather than fixed, inefficient routes. Availability Over Scarcity - There should always be an ATS unit available when and where it's needed, reducing wait times and ensuring continuous service. Efficiency Over Redundancy - Every unit must maximize passenger load without compromising speed and convenience, ensuring an optimal balance of utilization. Simplicity Over Complexity - Operations should be straightforward, avoiding unnecessary bureaucracy and ensuring seamless passenger movement. Continuous Improvement Over Static Systems - ATS evolves based on data and feedback, refining operations to enhance reliability and customer satisfaction. Customer Experience Over Just Transportation - The system is not just about moving people; it's about making their journe...
Read more

Prompt Analysis Using First-Principles Thinking (FPT)

Instead of memorizing existing prompt patterns, let’s break down Prompt Analysis from First-Principles Thinking (FPT) —understanding what makes a prompt effective at its core and how to optimize it for better AI responses. Step 1: What is a Prompt? At its most fundamental level, a prompt is just: An input instruction → What you ask the AI to do. Context or constraints → Additional details that guide the response. Expected output format → Defining how the AI should structure its answer. A well-designed prompt maximizes relevance, clarity, and accuracy while minimizing misunderstandings. Step 2: Why Do Prompts Fail? Prompts fail when: ❌ Ambiguity exists → The model doesn’t know what’s truly being asked. ❌ Lack of context → Missing background information leads to weak responses. ❌ Overloaded instructions → Too many requirements confuse the AI. ❌ Vague output expectations → No clear structure is provided. ❌ Incorrect assumptions about AI behavior → The prompt d...
Read more