Energy, Learning, and Optimization
For the last few months, I’ve worked on Gigglebot, an iOS app for instantly putting AI images in your text messages. Starting with no experience in Swift or iOS app development, it’s been a huge learning experience, and I wanted to share some of the insights I’ve learned along the way. » Read More
In the last post I spoke about how there will be a brief shiny period of AI solo-unicorns. This post examines what happens beyond that era of high AI valuations, as we enter a world where more companies with tiny AI-empowered teams are are competing with each other. » Read More
As AI agents have gained traction over the past year, there’s a buzz in the Bay Area: Someone, somewhere, sometime soon, might have the first one-person company with a $1 billion valuation: 1-person-1-billion, 1P1B, or the solo-unicorn.
AI-first companies have already had some impressive exits (Base44 sold for $80M in June 2025), » Read More
At a hackathon in 2023, I worked alongside a rising college Junior majoring in Computer Science who was worried that he should switch majors because AI would eliminate software development jobs. At the time, I brushed off his concerns, as I expected most of the usefulness to be in written language, » Read More
I took part in the SF10X hackathon in early August, and ended up winning second place and $1500 for a project which allowed for scalable visualizations of what the city will look like under the proposed rezoning.
The project was mentioned in the SF Standard’s coverage of the SF10x hackathon, » Read More
When my girlfriend was shopping for a new car in late 2024, I advocated getting an Electric Vehicle- until I realized that the effective carbon abatement cost would be $1,200 / tonne CO2-e abated, more than twice the cost of carbon capture and sequestration (per Charm Industrial). » Read More
This blog has been quiet the last 4+ years while I was working at Teza Technologies, a quantitative hedge fund based in Austin. A combination of financial regulations, company policies, and a culture of secrecy keeps people from talking about life at quant funds- but now that I’m out, » Read More
For years, data-driven tech companies have used customers as their raw material: Facebook, Google, Amazon, and others track our moves across the web in order to sell that information and target advertisements. For a long time, users found this an acceptable tradeoff- but in the wake of the 2016 election and amidst the changes brought about by the General Data Protection Regulation (GDPR), » Read More
Machine learning has exploded as companies find ways to draw actionable insights from the data which consumers feed them. However, the efficacy of artificial intelligence algorithms is dependent on the size of the data pool- giving big companies like Facebook and Google a formidable advantage over small scrappy startups. » Read More
Early blockchains served as decentralized ledgers: creating trust by guaranteeing that each new entry securely built on previous entries. Smart contracting systems like Ethereum added intelligence to on-chain operations, making it possible to run simple computer scripts. » Read More