Issue 01 · 2 min read
Learning fast, building next
The first issue. What I learned this fall, what I made, and what I am building next.
01 · What I learned
Four ideas I keep coming back to
- Think unconventionally. Unusual results take unusual paths. Asking "why" five times turns a broad topic into a problem worth solving.
- Stay curious. I finished an 18-module course on AI, from how neural networks work to what AI means for people.
- Bias to action. Most decisions are two-way doors you can walk back through. Try it, learn, adjust, try again.
- Seek understanding. I rewrote 28 lessons on synthetic biology and longevity as a plain-language study guide. Explaining it simply was the only way to know I understood it.
02 · What I made
A deck and my first article
- AI and robotics in the physical world. A presentation with Elian, Oskar and Ignacio. The surprise was construction: productivity has grown about 10% since 2000, against 90% in manufacturing. That gap is a huge opening for robots.
- How drones navigate without GPS. My first long-form article, on how a drone inside a collapsed building keeps track of where it is once the satellite signal is gone. Version 1 is done and has feedback on it.
03 · Lesson of the week
What presenting taught me
The feedback was blunt and useful: open with energy, lead with a clear hypothesis instead of a general topic, skip the table of contents, and speak without a script. I am keeping that list for every talk from now on.
04 · Everything else
Praxelis and the pool
At Praxelis I pushed Meridian forward with better onboarding, a cleaner interface and new features. In the water, training kept going around school.
Next week
- Write version 2 of the drone article.
- Get an expert to check my thinking before I build.
- Run my first experiment and write it up, failures included.
One ask
If you know someone who works on drones or robotics and would give me 15 minutes of feedback, I would love an intro.
Thanks for reading.Benjamin