Links

Think of me as a web crawler with taste.

Questions About AI

Casey Handmer:

A model I’ve long been interested in is the Corporation as a stand in for AGI. We need some non-human autonomous legal and economic entity. A corporation is just that. The Fortune 500 are already non-human super-intelligence. They operate 24/7/365 according to inscrutable internal logic, routinely execute feats of production unthinkable for any human or other biological organism, often outlive humans, can exist in multiple places at once, etc etc.

∙ AI

The Weekly Mind Meld

James Stanier:

The key is that you engage with your daily activities mindfully in a way that keeps your weekly update in mind. What I mean by this is that you are always on the lookout for:

  • Direct experiences that you have had that would be valuable to share with the team. This could be anything from conversations with customers to shareable summaries of closed-door meetings such as executive reviews.
  • Events that can be celebrated, such as a big project shipping, a long-standing bug being resolved, or performance improvements that have been rolled out.
  • Things that could be improved, such as an incident that happened, an inefficient process that is causing friction, or data that highlights a problem that needs to be fixed (e.g. a drop in performance or an unexpected increase in infrastructure costs).
  • Events that are happening in the near future that you want to remind people about.
∙ Communication, Management

How Swift's Server Support Powers Things Cloud

Vojtěch Rylko and Werner Jainek:

Our legacy Things Cloud service was built on Python 2 and Google App Engine. While it was stable, it suffered from a growing list of limitations. In particular, slow response times impacted the user experience, high memory usage drove up infrastructure costs, and Python’s lack of static typing made every change risky. For our push notification system to be fast, we even had to develop a custom C-based service. As these issues accumulated and several deprecations loomed, we realized we needed a change.

They chose to rewrite using Swift on the server.

∙ Software Engineering

How Simon Willison Uses LLMs to Help Him Write Code

Simon Willison:

Using LLMs to write code is difficult and unintuitive. It takes significant effort to figure out the sharp and soft edges of using them in this way, and there’s precious little guidance to help people figure out how best to apply them.

If someone tells you that coding with LLMs is easy they are (probably unintentionally) misleading you. They may well have stumbled on to patterns that work, but those patterns do not come naturally to everyone.

I’ve been getting great results out of LLMs for code for over two years now. Here’s my attempt at transferring some of that experience and intuition to you.

∙ AI, Tools

Life Lessons From the First Half-Century of My Career

David A. Patterson:

I started my career at Hughes Aircraft in 1972 while working on my Ph.D. at the University of California, Los Angeles (UCLA). After designing airborne computers for four years, I graduated and then taught and did systems research at UC Berkeley for the next 40. Since 2016, I’ve helped Google with hardware that accelerates artificial intelligence (AI).

At the end of my technical talks, I often share my life story and what I’ve learned from my half-century in computing. I recently was encouraged to share my reflections with a wider audience, so I’ve captured them here as 16 people-focused and career-focused life lessons.

∙ Advice, Career

A Practitioner's Guide to Wide Events

Jeremy Morrell:

Adopting Wide Event-style instrumentation has been one of the highest-leverage changes I’ve made in my engineering career. The feedback loop on all my changes tightened and debugging systems became so much easier. Systems that were scary to work on suddenly seemed a lot more manageable.

∙ Software Engineering