Sometimes problems you encounter need an outside perspective to help you figure out what to do.

I had previously observed that humans are the great interop layer—we are the glue that fits together disparate processes and tools into usable systems.

When building large complicated things, there are two primary strategies that optimize for different things—layering and chunking.

While large language models are already useful for certain text based tasks, connecting them to other systems that can interact with the outside world poses new kinds of security challenges.

According to a recent presentation by Redpoint, ARR multiples for Series B and C companies dropped sharply from the all-time-high in 2022 (100x) to a more sober 39x, representing a 4x premium compared to public markets.

One of the super powers of large language models is that it can “do what I mean” instead of “do what I say”.

Deeply theoretical fields don’t necessarily translate to highly practical fields. Economists don’t typically do well as investors.

A recent paper looking into the economic impact of large language models found that the legal industry has the most potential occupational exposure from AI including augmentation or substitution.

One of the silver linings of the COVID-19 pandemic is that work and place are decoupling is increasing the radius of economic opportunity.

There are many barriers to adoption for a new programming language looking to go mainstream.

After using it for a few coding projects recently, I find that ChatGPT is a great way to lower the barriers to building smaller, self-contained projects—things that have been hiding in your to do list that take a bit too much effort to attempt but is still a good idea.

I’m messing around with ChatGPT in Emacs and I want to capture the results of a session in org-mode.

There are a few packages and libraries that are being built to use ChatGPT along with Emacs.

This note does not have a description yet. Links to this note AI Is the next Great Interop Layer

One of the limitations of large language models is that it is often missing context when responding.

A global survey that attempts to measure the extent to which people trust or distrust institutions in their country and in other countries.

According to the Edelman Trust Barometer, people trust businesses more than they trust government, media, and NGOs.

A survey of founders by NFX found that 42% of Series A companies are 100% remote which is higher than 38% of seed-stage companies that are fully remote.

It’s becoming clear that remote work isn’t going anywhere. A large portion of the workforce continues to work from home.

A successful business playbook I keep coming across is turning cost centers into profit centers.

There is a range of acceptable employer policies that ranges from unthinkable to popular.

There is a long list of reasons a startup might fail, but running out of money is high among them.

The Hawaii Unemployment Insurance portal becomes unavailable outside of their normal stated business hours.

Product debt is when promises made about functionality exceed what the product can actually do.