Links

Think of me as a web crawler with taste.

Open Source Tests as a Threat to Your Business Model

Simon Willison:

It’s become very apparent over the past few months that a comprehensive test suite is enough to build a completely fresh implementation of any open source library from scratch, potentially in a different language.

This has worrying implications for open source projects with commercial business models. Here’s an example of a response: tldraw, the outstanding collaborative drawing library, are moving their test suite to a private repository.

Direct Current Data Centers

Casey Handmer, Matt Weickert:

This post explains our current views on how humanity will achieve Kardashev Level 1 status by exploiting the full energy resources of an entire planet. More specifically, how pure solar+batteries will power AI scaleup beyond gas turbine manufacturing limits.

Knowledge Creates Technical Debt

Luke Plant:

The “pile of technical debt” is essentially a pile of knowledge – everything we now think is bad about the code represents what we’ve learned about how to do software better. The gap between what it is and what it should be is the gap between what we used to know and what we now know.

No, Your Domains and Bounded Contexts Don’t Map 1 on 1

Mathias Verraes:

In DDD, we reason like this: The engineers need to build, maintain, and evolve secure and performant systems that serve the company. To do that, the engineers need an understanding of the domains and of the software systems. To achieve that, we leave the domains as the organisation sees them, and we draw our own Bounded Contexts to serve our need for understanding. The Bounded Contexts exist primarily for the engineers, and for the engineers’ communication with domain experts and other business functions.

Good Engineering Management Is a Fad

Will Larson:

The conclusion here is clear: the industry will want different things from you as it evolves, and it will tell you that each of those shifts is because of some complex moral change, but it’s pretty much always about business realities changing. If you take any current morality tale as true, then you’re setting yourself up to be severely out of position when the industry shifts again in a few years, because “good leadership” is just a fad.

Covering Teen Wolf: One Coach's Guide

Pasha Malla:

I hope that between us we can keep the lines of communication open and continue to share strategies that seem to work. My feeling is that there’s no team that is completely unbeatable, even if their star transforms into a werewolf before every game.

User Effort in Product Design

Lea Verou:

Treat user effort as a currency. To create a product users love, design the tradeoff curve of use case complexity to user effort with the same care you design your pricing scheme.

Incremental user effort cost should be proportional to incremental value gained.

How Anthropic Decides What to Build Next

Catherine Wu (via Sachin Rekhi):

Step 1: Idea → Prototype Got a feature idea? Skip the spec. Build a working prototype using Claude Code instead.

Step 2: Internal Launch Ship that prototype to all Anthropic engineers immediately. No polish required—just functionality.

Step 3: Watch & Listen Track usage religiously. Collect feedback actively. Let real behavior, not opinions, guide decisions.

Step 4: Data-Driven Prioritization

  • High usage + positive feedback → roadmap priority
  • Low engagement or complaints → back to iteration

I’m increasingly of the opinion that focusing on prototypes first cuts through a lot of what ails many product development processes.

Kagi News

Kagi:

Every day, our system reads thousands of community curated RSS feeds from publications across different viewpoints and perspectives. We then use AI to distill this massive information into one comprehensive daily briefing, while clearly citing sources.

I’ve wanted something like this for a while. I like how the daily update cadence debounces the signal.

I’m keen to see how it works in practice.

Seeing Like a Software Company

Sean Goedecke:

This is why tiny software companies are often much better than large software companies at delivering software: it doesn’t matter that the large company is throwing ten times the number of engineers at the problem if the small company is twenty times more efficient.

Why don’t large companies react to this by doing away with all of their processes? Are they stupid? No. The processes that slow engineers down are the same processes that make their work legible to the rest of the company. And that legibility (in dollar terms) is more valuable than being able to produce software more efficiently.

Why Retention Is So Hard for New Tech Products

Andrew Chen:

The idea really matters.

  • If you want a high retention product, you need to pick a category that is high retention already.
  • You need to pick a product category where you already use an existing product every day.
  • You’re going to build something that directly competes against that.
  • If you win, then you’ll stop using that other product and use your product instead.
  • That’s a high bar, but I think it’s a good start.

This is why I don’t blame folks who have a “Cursor for X” idea, or “Figma for X,” just like the “Uber for X” ideas of the past generation. They’re trying to piggy off some existing markets and behavior so that they don’t have to take crazy market risk.

Well worth a read for those in the tech product subscription business.