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.

A list of patterns worth understanding from Jason Yip.

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:

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.

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.

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.

Some wonderful photos, like this one by Nichole Ayers.

Instapaper Team:

Our focus for PDFs is to make them more readable, especially on mobile devices, and bring the suite of Instapaper tools to PDFs including highlighting, notes, text-to-speech, etc.

Maybe now I’ll make a dent in my folder of unread PDFs.

Om Malik:

I bring up this recent history because it shows a pattern. Whenever there is a new competitor with a new online and social behavior, Meta management views it as a systemic risk to its attention-based economy. Instead of trying to reinvent, it simply copies and rolls out those features to its massive audience. Thanks to its large audience scale and massive infrastructure, it leaves the smaller rivals and original innovators as nothing more than mere footnotes.

Priscilla Page:

Finally finished this long-gestating essay about Highlander. Obviously, there will be spoilers ahead. Since everyone loves talking about the mismatched accents and there was no place in the essay to insert this information seamlessly, I wanted to mention that no one involved in the production seemed to give a shit. They weren’t exactly aiming for realism. Although Christopher Lambert’s complete inability to speak English was shocking to the filmmakers — they didn’t meet him until after they cast him — but everyone had fun with it.

This was a fun read. I loved Highlander as a kid.

Ben Khun:

In a company like Anthropic, excellent project management is an extremely high-leverage skill, and not just during crises: our work has tons of moving parts with complex, non-obvious interdependencies and hard schedule constraints, which means organizing them is a huge job, and can save weeks of delays if done right. Although a lot of the examples here come from crisis projects, most of the principles here are also the way I try to run any project, just more-so.

Some practical advice on supporting AI agents from Diwank Tomer.

Two things that stood out to me:

1. Asking the AI to embed bits of context in comments for itself so it can reconstitute context on previous decisions.
2. Making the tests purely for humans as a way to give the AI more rope to make changes.

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.

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.

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.