Dan Grover

@Anayacs71 I thought it was 么

I parked near a Chinese restaurant while at the gym, and when I came back, I found this symbol on my car. Any idea what it means?

@himbo_urbanist Glenwood Springs, CO!

What's a weird, small, but secretly very cool city that I can get to on Amtrak

I feel like every open source project launch needs to have a rap anthem after trying printingpress.dev.

I'm between using my bespoke Claude Code environment for personal stuff and Hermes and stuck due to model costs on OpenRouter due to how heavily Claude is subsidized. What are people doing to manage this? Just suck it up?

The CEO pronouncements about AI seem to rhyme with the COVID-era pronouncements about remote work.

Eli Goldratt's book, The Goal, was famous for its (then unpopular argument) that keeping every machine running 24 hours a day, the metric most plant managers cared about, was actively making factories worse. I suspect we're seeing the same fallacy in how many people are using AI agents. Goldratt's point was that machine utilization isn't throughput. What you want from a manufacturing plants is making good widgets as cost-effectively as possible. It doesn't necessarily follow that running your machines all the times optimizes that. Picture a three-station assembly line. Stations 1 and 2 each crank out 200 widgets an hour. Station 3 can only handle 100. Running stations 1 and 2 around the clock doesn't ship more product. It just piles up half-finished widgets in front of station 3, ties up cash in inventory, and creates more work managing the pile. He developed the Theory of Constraints to point out that what matters is solving the bottleneck in the system, not increasing machine utilization. I suspect a lot of agent usage right now is the same fallacy at higher resolution. Running 20 Claude Code sessions in parallel can feel productive because something is always happening. But, if the bottleneck in your work is judgment about what's worth doing, more agents just generate more output for you to wade through. This is not to say there aren't workflows running 20 agents in parallel very effectively, I'm sure there are. And, I suspect there's a general retraining we all need to do around evolving historical workflows. But.... The constraint for most knowledge work is deciding what's worth executing and no one is task switching between 20 things at the same time effectively I don't think. I find I can run maybe 2 or 3 things in parallel with maybe 1 or 2 admin-y type things on the side and that is only if I'm very locked in.

@yacineMTB Been pretty happy with my Framework 12.

Is there a non dogshit laptop that has the same perf to power usage out there as the macbooks which I can run linux on? Doesn't have to be same exact perf just good. Like M1 or M2 equivalent. Surely there is something out there? I'm sick of macos its pissing me off

I wonder what an OS would look like if you made agents and their contexts first-class constructs. I spend a lot of time getting stuff from apps/services into a given agent. It feels like updating manual memory allocations for apps on OS 9.

I miss the thing in the old-timey desktop app TurboTax where it flipped around and let you edit the raw forms in fullscreen view so you could see what you're filing.

I keep noticing how much of my muscle memory of how to do a product job from a decade of habits is based on now faulty assumption that engineering teams are like these expensive, slow, cruise ships that it behooves you to be precise about.

every robotics company that died young had a beautiful product roadmap and zero customers willing to yell at them weekly

One of Thiel’s best insights is that companies that are true monopolies will do everything to avoid telling the public that. They will minimise themselves. They will tell us that they are not a monopoly to avoid scrutiny. On the other hand, companies that aren’t, or don’t have defensible markets, will do everything to project the opposite—to brand themselves publicly as monopoly-like powers. A lot to reflect here in the OpenAI/Anthropic narratives. It’s not exactly the same, but the permanent underclass language, the grandiosity, the ‘AI will take all your jobs’ seems close to Thiel’s second category. What’s frightening is how far they’ve taken it, seemingly without considering the weight of their words, and how it’s now putting their lives at risk. I felt Sam’s pain reading that blog post. It’s especially sad to consider that, if Thiel is right, they’ve frightened the public into taking these kinds of actions for a marketing lie.

@therealjfrantz OpenClaw already doing this

LLMs will have message reacts (like iMessage/Slack) within 3mo

After 4y as head of product at Standard Bots, I'm moving on. Proud to have worked with such a talented team and gone from 1 robot to 100s deployed and to have learned so much along the way. Going to take time to chill and eventually figure out what's next. DM's open.

We have figured out how to scale output by a degree that rightfully astonishes all of us but not how to scale and divide accountability for outcomes/last mile stuff.

@antoniogm It is a weird figure to get head around, because the numerator also includes money for 10Kish people in "supportive housing" who are not in denominator, but who otherwise would be homeless.

The first time I got canceled online was when I observed that SF spends more per homeless person than the cash comp of a junior Google engineer. What. A. Dogpile. Also, funny NYC is just doing a SF rerun here.

OpenAI is a Meta cargo cult (makes sense given 700 ex-Meta employees). One breakthrough product innovation that got them distribution and all future success comes from capitalizing on that distribution and copying product innovations from competitors. Stick to what works!

AI can/does help with this stuff too! The angst isn't so much against AI; it is from the people who can see the 20% that takes all the time and directed towards the people who see something passable on first skim and go "oh so its basically done right"

It's similar to hackathon demo/iceberg fallacy: you can get a great hackathon demo if you don't worry about how feature interacts with others, how it scales, bugs/code quality, edge cases, etc.

The good thing with AI is shocking degree to which a task (whether you are an engineer, designer, or PM) can be brought to 80%. The bottleneck then becomes people who can tell the difference between the 80% and 100%.