xwowsersx

This is really quite lovely. I shelved a few books. Very nicely done UX. Thanks for this.

I'm building an app that generates lifting mesocycles and tracks every set and rep. Each week, it uses feedback from the previous workouts to adjust training volume and intensity. It's replacing an app I currently pay $25/month for.

Study seem to have addressed point #2 in several ways.

1. They measured maternal vitamin D before supplementation began. They explicitly adjusted for these preintervention levels.

2. the two groups started at essentially the same vitamin D levels.

3. They specifically tested whether baseline vit D status changed the effect of supplementation

Intuit has a pretty broad financial software portfolio, not just a tax company.

Also, yes the actual arithmetic at the end should be handled by deterministic code. I doubt anyone, including Intuit, thinks otherwise. But there's a ton of uses for LLMs before you get to 2+2 = 4, explaining concepts, document extraction, understanding the full financial picture, etc.

Kind of feels like you're criticizing a cartoonish idea of AI's place in their products.

This is the way

Nah. A forcing function creates pressure toward an outcome...a standing meeting just creates pressure toward the meeting. Those aren't the same thing.

The moment you put a recurring block on the calendar, the implicit contract shifts from "we make progress on this work" to "we show up on Tues at 2". The meeting becomes the deliverable. And it always stays long after the original need has passed because nobody wants to be the one who kills it.

What you want is to call a meeting when you need one. When there's a decision to make, a blocker to clear, or a plan to align on... get the right people together and do that thing. A meeting you call as needed stays honest, or at least has a higher chance of staying honest. A standing meeting just becomes calendar furniture and most of the people in it know it.

This looks great. I've been looking for something simple like this...assuming I’m understanding it correctly.

I recently picked up a refurbished Lenovo ThinkStation, and it's an absolute beast. I keep it next to my main work machine and offload all the heavy work to it like running multiple agents, jobs, etc. It's connected via Tailscale, and I’m usually just SSH'd into it.

What I'm missing is a clean, easy way to see what's actually going on on that machine at a glance. Looks like this might fit the bill?

What is the memory system you are referring to? I've been trying Memori with OpenClaw. Haven't had a ton of time to really kick the tires on it, so the jury's still out.

It sounds appealing at first because it flips the trust model... instead of the service initiating contact the user proves control of their email up front That feels cleaner and arguably more robust against certain classes of abuse

But from a UX standpoint its a nonstarter

Youre asking users to

- leave the site/app

- open their email client

- compose a message or at least hit send

- wait for a reply

- then come back and continue

Thats a lot of steps compared to enter email -> click link. Each additional step is a dropoff point especially on mobile or for less technical users. Many people dont even have a traditional mail client set up anymore, they rely on webmail or app switching which adds even more friction

It also introduces ambiguity

- What exactly am I supposed to send

- did it work

- What if I dont get a reply

From the service side youre trading a simple well understood flow for a much more complex inbound email processing system with all the usual headaches (spoofing parsing delivery delays spam filtering)

In practice most systems optimize for minimizing user effort even if that means accepting some level of abuse and mitigating it elsewhere. A solution that significantly increases friction... no matter how principled...just wont get adopted widely

So while the idea is interesting from a protocol design perspective its hard to see it surviving contact with real users

I feel like we're still stumbling about a bit and don't know all the answers, which is fine. But NVIDIA frames AI agents as the next computing paradigm, but most of what's described here still looks like orchestration + retrieval + tool use on top of LLMs.

What actually has to change at the systems level (data layout, memory, scheduling, storage, networking, etc.) for agents to become a first-class workload rather than just another application pattern on existing infrastructure?

You mean to tell me that increasing supply lowers price? Fascinating.