I’m back on my learning guitar jag. This set of theory videos are great.

Charity Majors:

The mandate is one way of putting organizational muscle behind a decision. It’s a funding mechanism. It works by acknowledging that “hey, we are all going to be a little slower for a bit while we figure this out, and it will be annoying and expensive and we accept that.”

Without funding and a mandate, you’re effectively telling your employees to build these skills in their spare time, if they can and if they feel like it. Which is the same as telling them “this is NOT a priority, we are NOT willing to fund it.”

Ben Thompson:

What Karp is driving at is the flip-side of the points I am making above: the challenge for enterprises when it comes to using the frontier models is not simply that tokens are expensive, but that they are potentially giving valuable data to the labs who, in the long run, have an economic imperative to move up the stack and own the customer directly.

Chad Fowler:

Why are humans allowed to edit the output at all? If you care about provenance—about being able to trace every line of code back to a decision—then manual edits are a problem. They break the chain. They introduce code that has no record, no explanation, no origin you can inspect. So you end up in an uncomfortable place: You don’t just prefer that agents write the code. You require it. Not because agents are better programmers. But because they are the only way to guarantee that every change passes through a process that can be captured, inspected, and replayed. Humans don’t stop participating. They just move up a level. They define intent. They shape constraints. They review outcomes. But they don’t write the code directly anymore. Because the moment they do, the system forgets how it got there.

Kore Nordmann:

This shape matters because the single biggest cost of the SPA model is that it duplicates the server. State lives twice, once in the database and once in the client store. Rendering logic lives twice, as templates on the server and components on the client. And between the two halves you must now build and version an API which exists only to feed your own frontend. For an application which is genuinely client-state-heavy, like a collaborative editor or a design tool, this duplication buys responsiveness you cannot get any other way, and it is worth every line. For a catalog with a search box it is pure overhead.

I keep my agent skills and plugins minimal. This set of software development agent skills hits a sweet spot.

Handy to connect your listening history to an LLM to generate some custom playlists.

Sean Goedecke:

When a product manager says that something is critical, engineers generally have to shrug and say “sure, I guess”. This obviously requires a lot of trust. What’s a little less obvious is that this trust is continually broken by both sides. Every single product manager has been told thousands of times that technical task X is technically impossible or would be disastrous, only for that task to end up being done fairly smoothly and successfully. Every single engineer has been told thousands of times that requirement X is absolutely critical and worth going to enormous effort for, only for that requirement to be silently dropped or changed with no apology.

A handy utility for controlling Elgato lights.

The feature to switch your lights on and off with your camera state is killer.

David Poblador i Garcia:

Which is to say, after two decades and forty-four meters of build tools and bundlers and hydration schemes, the industry sprinted in a giant circle and arrived, slightly out of breath, back at something that looks an awful lot like the file you uploaded over FTP. The instinct didn’t expire. The ground moved, for real reasons, and then it moved back.

A journey in and out of the heart of darkness.

A nicely laid out story of how we got where we are in software product design.

Mitchell Hashimoto:

This is my journey of how I found value in AI tooling and what I’m trying next with it. In an ocean of overly dramatic, hyped takes, I hope this represents a more nuanced, measured approach to my views on AI and how they’ve changed over time.

Derek Thompson:

Stalin and Hitler: Both terrible, but also mutually destructive. Cancer and Alzheimer’s: Also both terrible and also, weirdly, mutually destructive. Apparently—and I never knew this—Alzheimer’s patients rarely have cancer. Doctors have studied the association for years without understanding the root cause. Maybe it’s mere selection effect, where people who don’t get cancer survive long enough to get dementia. Or maybe something more interesting is happening.

decryption:

Over a decade ago I got into FIRE - Financial Independence, Retire Early. I’m currently in the position where I’m closer to the end of a FIRE journey than the start, so here’s a big dump of knowledge on various finance topics relevant to me. This post exists primarily so I can get it out of my head and stop thinking about it.

A well written summary with loads of references.

Cate Hall:

It’s easy to extend this framework to explain burnout. You can think of the rider and the elephant as having agreed to a sacred pact: In exchange for doing what the rider asks, the elephant is promised certain rewards. When things are going well, the needs of both rider and elephant are satisfied, even if the balance isn’t exactly even day-to-day.

Burnout results when the rider asks the elephant, over and over again, to commit a tremendous amount of energy to a task, but then fails to provide the reward the elephant is expecting. As a result, the link between effort and reward breaks for the elephant, with catastrophic consequences for the rider.