k9294

I'm a big fun of elixir, haven't seen they working on this, very cool!

But again, it's very far from being a simple serverless micro server that scales infinitely and is super easy to use.

To kill celld and potential competitor early? AFAIK, there is no a single Durable Objects alternative at the moment? It's better that way I guess.

> Say no to drugs. Kind of a metaphor, but not quite.

I think AI is even worse than drugs. On the one hand, it has some elements of a slot machine (when you have irregular success with the process, it creates a more powerful cycle of dopamine release on success). On the other hand, it makes work easier, and humans are just wired to choose the easier road. It's like walking or driving a car when you have to travel 10 miles each day. I don't see how, on a civilization scale, AI won't transform our civilization for better or worse.

+1 waiting for the blog post!

The part that scares me the most is that OpenAI researchers who manage this experiments sometimes (according to the HF hack investigation) don't know what agents do.. So they run RL to reinforce this unknown behavior (lying/cheating/hacking) and god knows what else...

And if this already happened at least once, how many times it has already happened and was “accidentally” added to the main model?

It's not that I haven't heard of this, it's the reality that you have these constraints when you build applications on modern infrastructure. And let's face it, most of the applications use this infrastructure with these crazy prices for egress.

100%, but this means we are going to move to stateful APIs on the AI provider's end (like OpenAI already does with Codex and Responses API) to make this work.

Yep, but even 0.006 is quite a big improvement. I'm curious now to test the model on some token-heavy tasks, like code exploration before a coding session, to see whether it will decrease the total cost of the task in the end or not.

I'm surprised more people aren't talking about the cache hit price: $0.003 per million tokens. I have a feeling that the price of 1 million tokens transmitted over the internet is more expensive than cache hit. Are we close to making the chat completion API obsolete because the cost of context transfer over network is going to dominate the task total cost?

Here's the same token usage priced at different rates: a real long-running coding task, medium codebase, 447 turns.

  Input           1,026,957
  Output          164,667
  Cache read      36,554,368

GPT-6-astra

  Type      Rate     Cost  Share
  Input   10.000   10.270    19%
  Output  50.000    8.233    15%
  Cache    1.000   36.554    66%
  Total            55.057   100%

DeepSeek v4.1 Flash, $0.003 cache hit

  Type      Rate     Cost  Share
  Input    0.300    0.308    50%
  Output   1.200    0.198    32%
  Cache    0.003    0.110    18%
  Total             0.615   100%

DeepSeek v4.1 Flash, $0.006 cache hit

  Type      Rate     Cost  Share
  Input    0.300    0.308    42%
  Output   1.200    0.198    27%
  Cache    0.006    0.219    30%
  Total             0.725   100%

Hypothetical: same DeepSeek input/output rates, but cache priced so it accounts for 66% of the bill.

  Type      Rate     Cost  Share
  Input    0.300    0.308    21%
  Output   1.200    0.198    13%
  Cache    0.027    0.982    66%
  Total             1.487   100%

This cache it improvement makes the model x2-x2.5 more efficient on a long horizon tasks in terms of cost.

Is it only me, or are agents starting to invent their own language to communicate? It's almost impossible to understand anything from this message board.

Is there any comparison of usage limits for Antigravity plans vs. Codex?

I just ran two light tasks on my codebase and got 100% of the weekly limits of a Pro plan blown away. Is Ultra plan any different? Because on Codex it wouldn't affect my Max plan at all, I think it would have been below 1% othese usage.