Part 1 - Pinpoint a flaw and draw reflection
From my last blog, I wrote that I have a hard time with faithfully keeping to a schedule. Essentially this means I have a time management problem. Good news is, I've been naturally getting better at this, especially as I age up; however, it doesn't hurt to take some additional reminders and tips offered by AcademicTips.org.
One of the helpful suggestion it offered is a "personal time survey." This is where I list several of my activities throughout the day and quantify it into hours spent. I multiply that by 7 and I have the total hours spent in a week. One of the the eye-opening moments was seeing the hours of sleep that I had. I usually sleep around 10 or 11pm. I wake up at around 9 or 10 am. Sounds strange when I write it out like this, but the truth is I sleep around 10 to 12 hours a day! That means I am sleeping around 70 to 84 hours a week. Compare this to 56 hours of weekly sleep if I were to sleep 8 hours a day. This means I am missing out on almost 28 hours of productivity per week! Maybe I really should start drinking coffee in the morning instead like everyone else.
Another good tip was simply telling me not to be a perfectionist. I have to shift my mentality more toward "get it done." This will allow me to move onto the next assignment in a timely manner.
Part 2 - Personal learnings and pondering
Some of my favorite topic I learned this week was on Suleyman's and Ng's discussion revolving around AI. Suleyman sees AI not as a tool but rather as a digital companion. He explains AI as possessing a trifecta of IQ, EQ, and AQ (action quotient) which allows the potential to guide through knowledge, "empathy," and action. Interesting perspective. The next video involved Andrew Ng, which I became excited about as I follow him on several of his courses. He introduced the concept of agentic AI (or AI agents). At first I didn't quite understood the difference between that and simply utilizing AI as a workspace. Clarity was offered when he started differentiating the difference between non-agentic zero workflow and agentic workflow. It was interesting to see that AI can serve as a mediator to determine thinking goals to provide to another AI to produce a more accurate outcome. It seems this discourse introduced another layer of stack known as "agentic orchestration layer" within the AI stack hierarchy.
This does bring with it my own personal pondering regarding ethical frameworks that we've learned this week and how they fit into these new developments. If were to shift our mentality of seeing AI as tools to companions, how then do we determine that is right for AI to teach us? Each of us as human come with our own understanding of the world limited by our culture and experience. This is inherently understood and our flaws are viewed as natural. But for an AI, if it is to serve as a companion, what framework do we let it adopt? Do we let it behave in accordance to the Natural Law Theory? Let it adopt a Utilitarianism model? Or since it is suppose to act as our companion, do we let it develop a personalized Care Ethics model?
Part 3 - Reflection regarding "What Every Computer Science Major Should Know"
The reading had quite a lot of suggestions, and for good reasons. One of the discourse I consistently hear is that most new CS graduates "do not know how to code/program." This sounds a bit ironic at first and then it becomes quite clear that this is the truth. Most CS degree programs teach fundamentals and theory but not industry standard practices. Many students therefore are left to figure out how to achieve relevant experiences on their own. Combine that with the fact that many recent students simply utilize LLM to do the coursework for them and you end up with graduates who didn't even achieve a strong foundation in fundamentals to begin with.
This is where the "Portfolio versus resume" section seemed to hit so hard. In order to make software development my career, I must create a code portfolio. The expectations are changing and resumes simply don't cut it anymore. In addition, the Unix philosophy was an interesting reading since it is the first time I've heard of such concept. From what I understand, the philosophy it is talking about is regarding how people should approach software design and development - the kind that was used when Unix and its relevant programs were first created.
Part 4 - Reflection on Integrity
Recently, I've understood integrity as not just a philosophical matter of character purity but as a core component of our software development career. This is a very strong "know it or die" profession. If I cannot produce the thought ability to create my own original code, then what use am I to my company or client? How can I expect to further my skills and knowledge if I let others or a LLM do all the creation for me? The same expectation goes for my cohorts. It is in my best interest to have teammates who are competent and they cannot develop competency if I do the work for them.