Day 5 - Impromptu Lightning Talk (Tokyo Python)

Yesterday was quite productive. I was able to shut my computer down at the end of the day thinking that I did a lot.

During the first part of the day I was procrastinating on working on my flashcards for the knowledge graph but I cleaned up and consolidated a lot of documents I had been working on.

After I had no more documents to clean up, I started working on the different LLM prompts that would help me refine my flashcards and create metadata. I ended up making them for the following:
-Identifying flashcards where wording created conflicts
-Identifying concepts and constraints (e.g., triggers, prerequisites, conflicts)
-Identifying domain and difficulty rating
-Identifying mandatory/optional tag

I still need to turn my features into flashcards and work on the nodes and relationships for the knowledge graph but I like the foundation I am building so far.

Tokyo Python

For the early evening, I had registered for a Tokyo Python event. I was choosing between this event and another one for vLLMs but picked the Python event because the description mentioned the option for a lighting talk. What this usually means is that the event opens up the stage to the audience to present a topic. I have two different demos in 'my back pocket' for such occasions. The host said that the topic could be indirectly related to Python so I raised my hand and was given 2 minutes to present.

I presented to the group my two versions of the app. V1 was just an app with all these features I wanted. And how I kept getting the advice that it was too complicated and that I should focus on just one thing. V2 was a UX redesign - but I did not lose any features. And the reception to this change has been positive at every event I have presented. I was able to change the narrative of my app without removing any features!

Every time I present it's been such a good experience. This is the third impromptu talk I give to a room full of engineers. And after the talk I had a few people come up to me to discuss. These are the topics we discussed and our talking points.

Why build a wellness app when there are competitors?
-Fitness apps are divorced from nutrition. Nutrition apps ignore fitness. Mindfulness and recovery apps only focus on their own domains.

Aren't you doing a little too much? Why not just focus on one domain?
-You need a little bit of everything to create long-term habits for change.

Why use a knowledge graph vs. a defined database schema
-With a defined database schema, you have to assume all the potential future relationships that your users will have with your app and their data. With a knowledge graph, you leave a wide room for error since you are using natural language to see relationships. This conversation in particular solidified my belief that a knowledge graph could be a strong tool for my app.

Are you doing this because you want to implement your idea or cause you want to make money?
-I think that my solution is something that could work for people. And I want to make money.