[The following was copied and pasted from GPT-4o when I gave it the transcription of a 30 second ramble I had walking to the gym and asked it to turn it into a 500 word blog post]

Planning for the future, especially when you're trying to save money, can be challenging and often feels counterintuitive. Consider, for example, a construction project. It's well-known that projects tend to run over budget, often by about 20%. If you're trying to prepare for this possibility and want to set aside an additional 20% for any potential overages, the question becomes: how much of the total project budget should you actually plan for?

Many people might instinctively think the answer is 80%. They assume that if they save 20%, they should just subtract that amount from 100%, leaving 80%. However, this is a common mistake that stems from a misunderstanding of percentages and fractions. If you were to stop at 80%, thinking that you've saved 20%, you'd actually be setting aside 25% for overages, not 20%. This happens because 20% of 80 is one-fourth, or 25%. So, by budgeting only 80%, you end up with more money set aside than intended.

To illustrate this more clearly, think of it this way: the correct amount you should budget for is actually closer to 83.33%. If you allocate 83.33% of your budget for the project, then 20% of that 83.33% is exactly the amount you'll save for overages, aligning perfectly with your goal. It may seem strange or unintuitive, but when you work through the numbers, the logic becomes clearer. Imagine you have a total project amount of 6 units. If you save 1 unit (which is 20% of 5 units), you're left with 5 units for your project, and the 1 unit saved represents the 20% overage amount perfectly.

So, when thinking about budgeting in this way, it's easy to see why many people make mistakes. The math involves fractions that don't immediately make sense. However, once you look closely at the numbers, you begin to understand the truth. This example from construction management demonstrates a common mathematical misunderstanding, where simple calculations can lead to significant differences in planning and saving. Recognizing these small but crucial details can make all the difference when preparing for the unexpected.

[The following was copied and pasted from GPT-4o when I gave it the transcription of a one minute ramble I had walking to the gym and asked it to turn it into a 1000 word blog post]

When we observe the universe, there’s a tendency to focus on what we know, on the predictable, on the well-trodden paths that science has meticulously mapped out for us. But often, the universe throws a curveball—a moment or a phenomenon that defies our expectations, and in those moments, we find a deeper beauty and a richer understanding. One such example is the way sunlight interacts with clouds, a phenomenon that might seem ordinary at first glance, but reveals a fascinating complexity upon closer inspection. This interaction is not just a simple matter of light traveling through space; it’s a dance of photons, bending, refracting, and creating illusions that challenge our understanding of the natural world.

Consider the way sunlight appears to curve around the edges of clouds. At first, it seems like an optical illusion—a trick of the eye. But there’s more to this phenomenon than meets the eye. When sunlight reaches the edge of a cloud, it encounters a boundary between two different mediums—air and the water droplets within the cloud. This boundary causes the light to bend, a process known as refraction. As light passes from one medium to another, its speed changes, causing the light to change direction. This bending is subtle, yet it’s enough to make the light appear as though it’s curving around the cloud.

This bending of light is governed by the principles of diffraction and refraction, where the change in the light’s speed as it moves from one medium to another causes it to deviate from its original path. The degree of bending depends on the wavelength of the light and the angle at which it strikes the boundary between the two mediums. The result is a subtle yet perceptible curving of light around the cloud, creating an ethereal halo or a bright outline that seems to defy the expectation that light should always travel in straight lines.

Yet, despite this apparent curving, if we were to zoom in on the process, we would see that the light is still traveling in straight lines. This is the paradox at the heart of this phenomenon—the light appears to curve, but it is actually following a series of straight paths, each one bending slightly as it crosses the boundary between air and cloud. It’s a reminder that what we perceive isn’t always a straightforward reflection of reality. Our minds are wired to seek patterns, to find order in chaos, and sometimes this leads us to see things that aren’t there, or to miss the subtle complexities that are.

This phenomenon is a perfect example of how the universe often defies our expectations. We’re used to thinking of light as something that moves in straight lines, something predictable and constant. But in reality, light is as dynamic and complex as the universe itself. It interacts with its surroundings in ways that can be surprising, even counterintuitive. And in those moments when our expectations are challenged, we have an opportunity to learn something new, to see the world in a different light—literally and figuratively.

The beauty of the universe lies not just in its order, but in its ability to surprise us, to show us things that we didn’t expect. It’s in those moments of surprise, when our understanding is challenged, that we grow, that we deepen our understanding of the world around us. The phenomenon of sunlight curving around clouds is just one example of this. It’s a reminder that the universe is full of wonders, many of which are hidden in plain sight, waiting for us to notice them, to question them, to explore them.

The more we explore these unexpected phenomena, the more we realize that the universe is not just a static, predictable place. It’s dynamic, full of surprises, and infinitely complex. Every time we think we have it figured out, it throws something new at us, something that challenges our understanding and forces us to think in new ways. And that’s what makes the study of the universe so fascinating. It’s not just about learning facts and figures; it’s about opening our minds to the possibilities, to the unexpected, to the things that don’t fit neatly into our preconceived notions of how the world works.

In a way, the universe is like a great puzzle, with pieces that don’t always fit together in the way we expect them to. But it’s in the process of trying to fit those pieces together, of trying to understand the unexpected, that we gain new insights, that we see the world in a new way. The bending of sunlight around clouds is just one small piece of that puzzle, but it’s a piece that can teach us a lot about the nature of light, of clouds, and of the universe itself.

So next time you see sunlight streaming through the clouds, take a moment to appreciate the complexity of what you’re seeing. It’s not just light traveling in a straight line; it’s light interacting with the world in a way that’s both simple and complex, both predictable and surprising. It’s a reminder that the universe is full of surprises, and that the most interesting things often happen when our expectations are challenged, when we see something that doesn’t quite fit with what we thought we knew.

And in those moments, when we’re faced with the unexpected, we have a choice. We can either dismiss it as an anomaly, something that doesn’t matter, or we can embrace it, explore it, and see what it can teach us. Because it’s in those moments of surprise, of unexpected beauty, that we find the true magic of the universe. It’s in those moments that we realize just how much there is left to learn, and how exciting that journey of discovery can be.

I’ve always loved reading book summaries.

Even if the summary of a book emphasized things that were different from what I thought was important when I read it, I still love seeing someone else’s perspective. 

So I’m always thankful of the virtuous people that freely share their book summaries online – and one of the best that I’ve found at it is Blas Moros, who publishes on his site blas.com. I could never read as many books as Blas has. Just as impressive, he seems to always capture the "most important" and wisdom-packed parts of a book; put succinctly - he don't miss much.

Five years ago, I had a lot of free time and wanted to learn as much as I could, so I decided to create a system that would help me digest this mountain of highlighted information. On 2/14/19:

• I went through all the books that Blas had reviewed up until that point
  

• Downloaded PDFs of each of their highlights separately

• Merged 125 PDFs together into a single, mega-highlight PDF

• It can be found here: Link

• Can be found here: Link
• It's from 5/31/19
• I’m sure there is some Blas-induced bias in the original highlights, just like I'm sure that there’s Cory-bias in my Hi^2
• The hashtags here is me trying to organize the highlights of highlights better into topics

I would normally stop there since that's more enough to organize and ultimately understand; yet in this case, I still had over 100 pages of information! So I decided to dive a little deeper:

• Made a Hi^3 version (highlights of highlights of highlights) which groups them by book then by tagged topic

• Can be found here: Link

• It's from 6/4/19 and is 81 pages long

• The tags here are more specific and tried to be more accurate within each book for each Hi^3 (but still has some errors obviously)

• Made a Hi^4 version (you get the picture) which groups the highlights by tagged topic across books

• Can be found here: Link

• It's from 6/5/19 and is 79 pages long

• The network graph at the top is what I used to decide the story, as these meta topics ended up being the “most important” (central) when graphed, as evidenced by their bubble size and text size
  

• For the graph, the nodes are topics and the connections are highlights of the same topic within the same book (Node A (highlight topic A) and Node B (highlight topic B) are connected by connection C (are in the same book C) - not a perfect reason but a way to connect topics (nodes) across books (connections)

• You can kind of see the shape of the story in the How 3 (EQ, character, and leadership) - What 2 (learning and lifehacks) - How 1 (simplicity) - Why 1 (love)

• Influenced by Simon Sinek’s “Why-How-What” framework, I made a variation that starts and ends with why – why 5, how 3, what 2, how 1, why 1

• 1, 1, 2, 3, 5... Fibonacci-hive assemble!

• Finally I made a Hi^5 version but IMO it was a step too far and I should’ve just stopped at the highlights grouped by tagged topic (the Hi^3 version)

• Not sharing it, as there was nothing really new

• It's from 12/2/20 and is 85 pages long

• Gets too lost in the thick of things

…and that's mostly where the research stopped.

In the end, I didn’t do much with all that glorious highlighted information. Yeah I revisited the Hi^4 version a couple of times and shared it with Blas (he thought it was cool), but I didn't do much else with it. I do love the network graph of the topics and have looked at it a bunch of random times – I find it beautiful.

Recently, I asked Blas if he minded if I shared the project with others, provided he is fine with it. At the very least, I feel like I learned a ton from the research project and hope others can as well.

Have fun getting lost in The Rabbit Hole.

[The following was copied and pasted from GPT-4o after I gave it a 2 minute ramble and asked it to turn it into a 1000 word blog post]

Understanding the concept of the forgetting curve can significantly enhance our ability to combat learning loss. The forgetting curve, first introduced by Hermann Ebbinghaus, demonstrates how information is lost over time when there is no attempt to retain it. This curve typically shows a steep decline in the retention of new information immediately after it is learned, which gradually slows down over time. However, by periodically revisiting the material, the rate of forgetting decreases, making it easier to remember the information long-term.

Imagine you're trying to learn a new language. Initially, you might find it difficult to remember new words and grammar rules. According to the forgetting curve, if you do not review what you've learned, you could forget up to 70% of the material within 24 hours. However, if you review the material after a few days, and then again after a week or two, you'll notice that the information sticks better each time. With each review session, the curve shoots up, and the rate at which you forget the material decreases. After about six or seven repetitions, you will have internalized the information, making it a part of your long-term memory.

The concept of the forgetting curve is not just limited to mental learning; it can also be applied to physical skills such as playing a sport or weightlifting. Just as your brain forgets information, your muscles can lose their performance capacity if you do not engage in regular physical activity. This phenomenon can be thought of as a "physical forgetting curve." Consider the example of playing tennis. If you haven’t played for a few weeks, your muscle memory and overall performance will have declined. The more time that passes without practice, the more pronounced the decline. However, if you practice tennis regularly, your performance curve will stabilize. Just like with mental learning, the key to maintaining and improving your physical skills lies in spaced repetition and deliberate practice.

When it comes to physical activities, combating learning loss involves maintaining a regular practice schedule. Imagine you’re lifting weights. If you lift weights consistently, your muscles will adapt and grow stronger over time. However, if you take a long break, your muscles will weaken, and your performance will drop. By lifting weights regularly and progressively challenging yourself, you can prevent this decline. For example, if you usually bench press 150 pounds, taking a month off might set you back to lifting 130 pounds when you return. But by gradually increasing your weight and intensity, you can surpass your previous limits.

This concept can be extended to any physical skill. For instance, if you’re learning to play the guitar, regular practice is essential. Each practice session reinforces your muscle memory, making it easier to play complex chords and melodies. Over time, with consistent practice, you’ll find that you can play more effortlessly and with greater precision.

Deliberate practice is a method of practice that involves focused and intentional efforts to improve performance. It’s not just about putting in hours of practice; it’s about practicing with the goal of addressing weaknesses and refining skills. For example, if you’re a runner, deliberate practice might involve working on your stride, improving your breathing technique, and increasing your stamina through interval training. When applied to the forgetting curve, deliberate practice can significantly enhance both mental and physical learning. By identifying specific areas that need improvement and working on them regularly, you can ensure that your performance curve doesn’t just maintain its level but actually improves over time.

Consider the regimen of a professional athlete like Serena Williams. Her training isn’t just about playing tennis matches; it includes a mix of strength training, flexibility exercises, and strategic practice sessions focused on specific aspects of her game. This kind of deliberate practice ensures that she doesn’t just maintain her skill level but continues to improve and refine her abilities. Even during the off-season, athletes like Serena engage in training to keep their skills sharp and to prevent any decline in performance.

Though the forgetting curve applies differently to mental and physical skills, the principles of spaced repetition and deliberate practice are common to both. For mental learning, this means reviewing information at strategic intervals to reinforce memory. For physical skills, it means engaging in regular, focused practice sessions to build and maintain muscle memory. Let’s take the example of a pianist learning a new piece of music. Initially, the pianist might struggle with the notes and rhythm. However, by practicing small sections of the piece repeatedly, the pianist reinforces their muscle memory. Over time, the pianist can play the entire piece smoothly. This process mirrors the way we reinforce mental learning through repeated reviews.

Both mental and physical learning involve overcoming plateaus—periods where progress seems to stall. In mental learning, this might happen when trying to grasp a particularly difficult concept. In physical training, it might occur when your performance levels off despite regular practice. To overcome these plateaus, it’s essential to vary your practice routines. For mental learning, this might involve studying the material in different contexts or using various study techniques. For physical training, it might mean changing up your exercises or increasing the intensity of your workouts. By challenging yourself in new ways, you can push past these plateaus and continue improving.

Understanding the forgetting curve and its implications for both mental and physical learning can greatly enhance our ability to retain information and maintain physical skills. By employing strategies such as spaced repetition and deliberate practice, we can combat learning loss and ensure continuous improvement. Whether you’re learning a new language, playing a sport, or mastering a musical instrument, these principles can help you achieve your goals more effectively. In essence, both mental and physical learning involve a similar process: regular, focused practice to reinforce memory and skills. By acknowledging and addressing the forgetting curve, we can better navigate the challenges of learning and emerge stronger, both mentally and physically.

This post isn’t about why I left teaching for the 2nd time in 9 years (that will eventually require its own lengthy post) but is about how I went about looking for a job outside of education. I’ve done this about 5 times over the last 15 years and have continually gotten better at knowing what I want and how to find it. Similar to how I narrowed down what cities to live in, a central spreadsheet with links and numerical scoring helped a lot.

The spreadsheet can be seen here: SHARED - KCMO Jobs 2024

What I wanted going into the job search:

• job in KC, with less travel being better

• in office and not remote

• Architectural/Engineering/Construction (A/E/C) industries preferable

• project management

• business analyst

• data analyst

• CAD drafter (fallback)

January 2024 - not really wanting a job as spring semester just started, but beginning search

• see a list of 150 companies that have a HQ in KC, search them on Google and get the careers link for each

• combine with a list of 27 architecture companies in KC, search them on Google and get the careers link for each

• combine with a bigger list of the 175 largest employers in KC, search them on Google and get the careers link for each

• create an ALL_companies list from 186 remaining companies after duplicates have been removed

• this list was fairly exhaustive to make, so I did a couple rounds of searching a company and getting their careers page link

• to help break the monotony of going industry by industry, I created a random column and used the rand() formula to switch them all up

• create a smaller list arch_engineering from ALL_companies that has just the 57 companies in the Architecture, Engineering, and Construction industries

• create a spreadsheet of the 62 jobs I found even remotely interesting across those companies with their job specific websites linked

• come back to the list and give each two different scores 1-3 with 3 best for how qualified I felt I was for the job as well as how interested I was in the job, along with some brief summary notes for each

• I have a 1/23/24 look into ALL of the companies

February 2024 - still not wanting a job right away but convinced that I won’t be teaching again

• start with January’s list of jobs, create a copy for February and see which jobs from January are no longer available in February and delete them

• once or twice in the month look up any new jobs in the A/E/C list as well as select companies from the bigger ALL list (really no organized way but it wasn’t all of them)

• end up with 56 jobs in February list

• take the qualified and interested scores 1-3 and multiply them to find a quick overall score for the jobs out of 9 possible points

• sometime around here I thought to have GPT-4 help me out, so on the sheet initial_gpt_suggestions is a list of jobs after I uploaded by resume PDF and the list of jobs I was interested in and asked it to create a list of best possible jobs

• I then revised this list by giving each an interest level score 1-10 with 10 max and prompting GPT-4 to revise it based on my interest score

March 2024 - starting to get really interested in finding another job and would consider leaving before the school year was done

• I updated February’s list in March and didn’t create a separate sheet, I don’t really know why

• I have a 3/3/24 look into random companies and not just A/E/C but didn’t get through all of them

• I found the first job (and company) that I researched pretty good into and eventually applied: Orange EV

• fast growing company in KCK that gave me SolarCity vibes

• they manufacture industrial electric vehicles, specifically electric terminal trucks which are the trucks that move trailers around distribution centers

• applied for EV Process Engineer role that was sort of trying to streamline their engineering department workflows and reminded me of SolarCity process improvement

April 2024 - definitely was more serious about finding a job, applied a couple times throughout the month and debated quitting once state tests were finished at the end of the month (and leaving a month early)

• create a copy of February list and see which are no longer available and delete them

• added new jobs from the ALL list randomly, ended with 43 jobs

• added a column for scoring how good the company was 1-3 and then multiplying that score with the scores from the qualified and interested scores for a new overall job score out of 27 possible points

• applied to 6 jobs throughout the month (rough month of school for me):

• 4/10 - another job at Orange EV, this time a Business Analyst role

• 4/10 - a Building Enclosure Specialist job at BranchPattern, an engineering company

• 4/23 - a Mechanical Engineer job at ME Engineers

• 4/23 - a general interest job posting with bnim, an architecture company

• 4/23 - a Civil Engineer EIT job at Wallace Design

• 4/26 - a Project Engineer job at Centric, a construction company

• a friend in KC is a Project Manager and has always raved about his company and sent over the job as he thought I would be a good fit for the role

May 2024 - was ready to leave at any point but also was determined to finish the school year, partly because I was so close but also selfishly because of a stipend bonus

• copied April’s list and revised for jobs no longer available and any random new jobs I came across, ending up with 42 jobs

• another teacher’s spouse worked at Taliaferro & Browne as a Project Manager and I applied and had an in-person interview for a Entry-Level Engineer/Inspector position

• the teacher’s spouse PM was great to talk to and I could definitely work with him

• the company seemed nice but the office was very sleepy and empty and not somewhere I could see myself working from

• the position would have entailed the first 6 months being in the field overseeing road construction inspections, which didn’t seem too interesting

• I decided to not pursue it further

• I had an in-person with Centric for the Project Engineer position in mid May

• the company seemed more and more impressive the more I learned about it, the office was busy and seemed somewhere I could work from

• the role was more entry-level Project Manager type work, which was interesting to me and a career path that I was very interested in

• one thing about the role was it was usually Construction Management new grads so I was a little bit out of the experience range but that’s ok

• the interview went well I thought, they were very knowledgeable and nice to talk to

• I thought that I had a 50/50 shot at getting the position

• I didn’t follow up after the interview because I thought they would reach out after the interview (I was a little over-confident likely) and honestly I was a little hesitant as I thought I’d start right away, and all I was focused on was finishing the school year and enjoying summer a little bit

• I didn’t get the job, was a little surprised but a little relieved, as I’d get to enjoy summer in June

• I eventually followed up after about 3 weeks when I knew I didn’t get the job and asked for feedback from the interview after giving my impressions of how I did (good and bad)

• I applied and had a phone interview for a Project Planning Assistant role at Populous, an architecture firm that building sports stadiums around the world (my dream company when I was graduating from my Architectural Engineering undergrad 15 years ago)

• the company (and work) has always been a dream of mine

• the role looked perfect, as I’d be helping Project Managers with various project tasks and be supporting them from a business analysis angle behind the scenes

• they contacted me pretty quickly after applying and I thought I had a decent chance

• the phone interview seems to go decent, I remember being very nervous for it because I loved it so much and talking too fast as I was too excited

• one bad indicator from the phone call was its length, as it ended up only being about 15-20 minutes and I didn’t feel I communicated myself well

• I followed up a week later and they told me that I didn’t get the job

• I was more disappointed on not getting an in-person interview here than I was for not getting the Centric job

• the jobs that are highlighted in pale yellow were ones I was particularly interested in and thought I would apply to

• after those 3 job explorations in May, I decided to pause and enjoy summer in the month of June (I felt that I truly deserved it after teaching) and didn’t look at jobs from mid May to mid June

June 2024 - once I got a couple weeks of relaxation and enjoying the slow paced summer life, I started to get ready to find a job again in mid June and started looking again

• I revised May’s list and ended with 45 jobs

• I revised my qualified ranking for my favorite job posting (was up for a couple of months) and don’t really know why I never applied for it

• Garmin would be fantastic to work for but they’re very big (and I might be lost at first) and the office is pretty far away (>30 minutes)

• the role looked awesome, a Project Manager role that would work on Business Analyst type streamlining

• a friend of a friend works there and I thought about reaching out to get a referral, but never really did

• I did another round of randomization of ALL_companies and started looking at companies outside A/E/C potentially

• I applied for two jobs on 6/17/24:

• a Project Management associate role at an Advertising company, Global Prairie

• an Operations Analyst role at what I first thought was an Architecture company but is really an Industrial Design + Build company, Dimensional Innovations (DI)

And that brings me to some good news: on Monday July 22nd, I’ll be starting my new job as an Operations Analyst at DI!

After my initial application to the job:

• they contacted me the next day to schedule a phone interview two days later

• the phone interview went decent to good, I was worried that I wouldn’t be able to communicate about myself effectively over the phone, similar to the Populous phone interview

• luckily this one was longer (45-50 minutes) and I felt I got more about myself across

• the talent manager explained a lot more about the job, and it sounded better and better with everything that I heard

• I’d be working directly under the Chief Operations Officer (COO)

• I’d be tasked with helping improve processes and assisting project managers, among others

• sounded like a perfect mix of Project Management + Business Analyst + Data Analyst, something that greatly interested me

• I was worried that I was too excited with how I was talking and was just hoping for an in-person interview

• they followed up the next day (Friday) and wanted to schedule an in-person interview for the following Monday, which showed that I didn’t screw up the phone interview too bad and they were interested in me as well

• the in-person interview ended up being directly with the COO and seemed to go really well, and I grew more interested in the role and working with her

• the office was great and a quick tour around it by the COO gave me more insight and respect for what they do

• I followed up with the COO 2-3 days later, saying it was great talking with her and again expressing my interest

• the talent manager emailed and said they wanted to schedule a 3rd interview the following week with some department managers

• the 3rd interview (2nd in-person) with two Directors of Project Management and Production Management seemed to go very well as well and I became 100% convinced that I wanted the job, that I think I’d do well in the job, and that I wanted to work at the company

• a week after the 3rd interview, I got a call from the talent manager and was offered the job

Final tally: 186 companies, hundreds of jobs looked at, 11 jobs applied for, 4 companies interested for initial interview, 3 in-person interviews, 1 job offer.

The role, the people, and the work that DI does all seem very exciting and I don’t think that it could have worked out any better. I’m ready for this new challenge!