jeeeb

I’ve gotta say my experience has been the opposite. I’ve been consistently surprised at how much mileage I can get out of the $20 plan.

My usage is pretty simple. I just use codex with an AGENTS.md to point it in the right direction. I have no MCPs and use Sol on medium thinking as the main model.

For longer sessions I tell it to launch a sub agent to make changes. Otherwise I just reset my context for each new task.

And Japan isn’t either. They are requiring that by the time you retire you’ll have paid at least 30 years into the pension system or have equivalent financial resources any gap.

I don’t think this is a very good use case. You could do it better with a strong LLM and structured outputs.

The problem is that you want the model to carefully reason about the goal and code.

Zero shot classification with an approach like this isn’t going to do that. It’ll answer on first pass vibes.

Why? What business is it of yours?

They were probably under an agreement not to reveal the buyer or amount.

Meta in turn probably wouldn’t have wanted news to get out and people forerunning them to claim other online properties just to sell them back.

That cuts both ways. US entities own huge amounts of overseas assets including debt.

A more appropriate saying would be cutting off your foot to spite your leg.

Thankfully no one has done that yet.

We have a subscription at work. They have a CLI agent that works pretty well. Lately I mostly use it with grok, which is actually quite a capable model.

Aider (and probably others) came well before CC.

No. Japan certainly doesn’t. If you want to renew your visa you go apply at the local immigration department and they mail you your renewal notice a month or two later. No need to leave the country at all.

It’s not really clear what you mean. 100kWh is more than the entire battery capacity of the EV.

Agree. Another consideration is that input token costs are effectively quadratic with the number of conversation turns. The minute you get into a long conversation you can see the costs shoot up.

You can get far more gas out of even a $20 plan of you’re careful to break things up into relatively small discrete steps, clear context regularly and give the model plenty of information to work with.

My workflow for bigger features is to write out a plan document and then proceed in smaller implementation steps, reviewing as I go. If I find something odd, I ask the agent why and often that leads to discovering a new dimension to the problem, which in turn is an opportunity to adjust the approach.

I have T1 diabetes and wear a GCM so have a continuous view of my blood sugar levels. I also go to the gym and exercise otherwise.

My experience is somewhat different. Even walking is more effective than chess presses or arm exercises for immediately reducing blood sugar.

After an hour or so of more intense aerobic exercise I find it basically impossible to avoid a hypo (low blood sugar).

Simplistically if the effect of exercise on blood glucose is roughly proportional to Volume of muscle engaged x Length of time engaged, things like running should be very effective. The bulk of your muscle is in your lower body and you’re continuously engaging it.

I suspect any decently intense exercise can have a moderate lowering effect on blood sugar levels after the immediate drop seen when you’re exercising, but the effective isn’t huge.

This is simultaneously amazing and horrifying.

I feel like we’re at the stage where if AI decides it needs to delete your production DB to solve the user login problem, then it’ll find a way to do just that.

If anything, it’s a very conservative estimate. Short of a major turn of events it seems very unlikely Anthropic’s revenue growth is going to slow to zero.

I think the government should make the new 0% tax rate optional. Stores can either continue to collect 8% or drop the rate to 0%.

I think that might help motivate these companies to move things a long a lot quicker. They might even find it doesn’t take 1 year after all.