We bought a house! Before moving in, I captured a 3D scan using Polycam (and manually butchering the output file using Blender).
Explore the interactive 3D scan here. You can walk around using WASD keys.
I’m pleasantly surprised by the level of detail and accuracy captured in the scan. It allowed me to more accurately visualize the space from home. The vibe-coded snipped worked out-of-the-gate on my Quest 2 even if the navigation is nausea-inducing.
Turns out a few walls were slightly off from the blueprints. I leaned into the scan along with the original floorplans to 3d-print a few options for the bathroom layout. A nice hoby and a nice snapshot of this moment in time.
Every difficult conversation is really three conversations happening at once:
- What happened - the “truth” or facts of the situation
- Feelings - how we feel about it (emotions)
- Identity - what it means about us
Most arguments fail because we focus only on proving our version of “what happened” while ignoring the feelings and identity threats underneath. The key is shifting from trying to win to being genuinely curious about the other person’s perspective, acknowledging emotions (theirs and yours), and separating your self-worth from the outcome.
Book also comes with hands-on examples that I did not jot down. I’ll likely revisit this book in a year to reflect. My full notes are available on Lucidspark.
Meta: I try making notes to intensionally slow down and, hopefully, get more out of a book. I tried both Miro and Lucidspark but keep coming back to Excalidraw.
Because it is open source I thought I’d try using it to present my notes in a read-only way. It also has a big ceiling for visualizing other things - like auto-generated flow-charts in a much nicer way than Mermaid.
The half-assed demo is available here.
Coding is being disrupted. Can I keep up? Is the code still maintainable? Am I a better employee if I use agentic tools?
WIP is available at /stack-or-llm/ and the rest of the writeup at my github
A while back, I explored what learning a new concept/approach (Genetic Algorithms) in the age of LLMs looks like. I enjoyed it, but I wouldn’t say it sped up my process.
I started with a very bold prompt to create an image generation program. Copilot confidently generated something that worked. Upon inspection, it was just a single iteration - it drew a triangle! I switched my approach to creating a scaffold of the necessary steps. An outline of the code. This helped me tackle the problem abstractly. Lastly I attempted feeding the LLM working Python code and tasking Copilot to rework it using JavaScript and Canvas. It worked, but what did I actually learn?
I started refactoring the code and tweaking it to make it my own. I wanted to speed it up and change the image style. This took me several hours and led to my final verdict - I likely would have implemented it from scratch faster and gained the same amount of understanding. Still impressive, and it has potential as something that will only get better with time.
Now I have a way to generate these little animations from images. Do you recognize any books?
There are more here.