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It might be a bias in terms of the probability of events, but I'm not so sure this is a market inefficiency in terms of actual trading strategy. If true odds are 1% and the event is priced at 4%, I can sell NO for a 3% edge... but lose 100% once out of a hundred. Doesn't seem worth it!

Which I'm confused about - wouldn't decreasing the cache TTL increase compute demand?

AI is a floor raiser, not a ceiling raiser

> you're going to end up systematically misinformed on political topics that people find outrageous.

That sounds... fine?

I vibe coded a charting library for excalidraw that I’m working into my blog:

https://github.com/tombedor/excalicharts

VC can spend all the money in the world and it won't matter if the cost of switching providers is effectively zero.

If I want to switch from Windows to Linux, I have to reconsider a whole variety of applications, learn a different UX, migrate data, all sorts of annoyances.

When I switch between Codex and Claude Code, there is literally no difference in how I interact with them. They and a number of other competitors are drop in replacements for each other.

That is 100% what I think is going to happen.

I wrote about it here: https://tombedor.dev/open-source-models/

> people might luck into something genuinely good and worth sharing from time to time.

A) it would be impossible to find in a sea of AI generated slop

B) even if it were to be recognized as good, it would be instantly copied by other AI’s such that it would be very shortly thereafter be also considered slop

For any work to gain traction with an audience, there needs to be scarcity. Art and artists are valued because they are unique in some way, something about it or them cannot be replicated by others. The ability to instantly produce a piece of “art” negates any artistic value, at least as far as audiences are concerned.

> Claude code is starting to develop one as people start to build things that require Claude Code specifically, not just any LLM.

I hate to be a "source?" guy, but I'm curious if you have any examples of this. Skills and MCP are really the only extensions on CC itself I'm aware of, and these are both supported in Codex.

Things like Dispatch / remote sessions is something CC has that Codex does not, but these features are quite easy to replicate (and I expect Codex to do so in short order).

Nothing about AI mindshare is durable. As Anthropic tightens rate limits and/or raises prices, everyone will move to something else.

This week I’ve been hitting CC rate limits, and I switched to Codex with virtually no disruption to my workflow. It’s not good for Anthropic that I was able to do that!

Both companies have the same issue: the unit economics are bad, and there’s no moat.

I’ve been primarily on Claude for the last 6 months or so, but have been hitting rate limits. I switched work to Codex seamlessly, just like I could switch to any other provider seamlessly

Curious if you agree that local is where Apple's bet is long term - it's out of reach now, but I found the jump in capability for the top line laptop interesting. Presumably chip development hasn't focused all that much on running LLM's for all that long, I'm wondering what kind of jump we'll see two or three releases down the line.

Would be interested in collaborating! My email is in my bio

I’m really, really uninterested in reading AI content that other people have generated. If I’m on Twitter, I’m looking for what humans have to say.

I've been playing with something similar! Curious how you are interfacing with Chess.com / lichess.org, are you having people paste their PGN's?

Why do you think that? Senior, staff, principle levels are pretty standard across the industry, even if some companies call them different things

The upgrade to the native installer gave me some issues, I had Claude fail to return any responses and continuously eat memory until my computer crashed! The only fix I could figure out is nuking my entire .claude dir, losing all my history etc with it

What else does "regime change" as a goal refer to?

This scenario always imagines that the people getting bombs rained down on them will somehow determine that their actual friends in the world are those dropping the bombs.

Even accepting this, how exactly are these peaceful, western friendly civilians going to withstand a war better than their country's army?

It's very depressing to see this playbook credulously trotted out yet again. When has this worked?

> But the entire economic surplus of Europe, Asia and North America was basically dedicated to (or extracted towards) making things that were reasonably expected to be destroyed within the year.

This is no longer necessary to inflict the catastrophic destruction we're really referring to when talking about a hypothetical WWIII

> The unix commandline tools being the most efficient way to use an LLM has been a surprise. > I wonder the reason.

Because they are really, really well designed for humans.

Everyone is trying to reinvent the wheel and create "agent interfaces", but there is fundamentally no difference between what makes a text based interface easy for a human to use and what makes it easy for an agent to use.

Tech has been trying to "gobble up" legal, medical, etc for decades. I'm quite skeptical a newcomer with a powerful model will be able to penetrate them, especially while selling those incumbents access to the same models they are building on.

Why would we assume the remote providers are going to be cheaper? They are burning cash, and Claude is already jacking up prices.

"Local" is the means to an end, not the value prop itself. The value prop is "fast, private, and free", which I think is going to be very compelling.

My main takeaway from this episode is that anonymity on the web is getting harder to support. There are some forums that people want to go to to talk to humans, and as AI agents get increasingly good at operating like humans, we're going to see some products turn to identity verification as a fix.

Not an outcome I'm eager to see!

If you can generate a song with a two sentence prompt, so can anyone else. Music and art is only interesting when there’s originality or a point of view being expressed.

I really think art (as in art that’s made for it’s own sake, as opposed to jazzing up a PowerPoint slide or whatever) is by definition something AI will not make inroads in

The only refinement there is I think a command runner like `just` works really well for making scripts easily available. That also has the same benefit of helping agents by helping humans

I recently read Origins of Efficiency by Brian Potter, and one of the interesting things it talks about is the path of the Model T.

Ford invested heavily in an in-house, highly optimized production pathway for the Model T. Other manufacturers sourced a lot of their parts from vendors.

This gave the Model T a great advantage at first, but they had a lot more trouble than competitors in coming up with new models. Ford ended up converging with the rest of the industry in sourcing more of their parts externally.

The lack of new Tesla models makes me feel like a similar pivot is what Tesla needs. My suspicion is that they probably need a less terminally distracted Musk to pull it off.

It's a very reasonable concern. My solution is to have the bot classify what the message is talking about as a first pass, and have a relatively strict filtering about what it responds to.

For example, I have it ignore messages about code freezes, because that's a policy question that probably changes over time, and I have it ignore urgent oncall messages, because the asker there probably wants a quick response from a human.

But there's a lot of questions in the vein of "How do I write a query for {results my service emits}", how does this feature work, where automation can handle a lot (and provide more complete answers than a human can off the top of their head)

I read through it, scanning sections that seem uncontroversial and reading more closely sections that talk about things I'm less sure about. The output cites key lines of code, which are faster to track down and look at than trying to remember where in a large codebase to look.

Inconsistencies also pop up in backtesting, for example if there's a point that the llm answers different ways in multiple iterations, that's a good candidate to improve docs on.

Similar to a coworker's work, there's a certain amount of trust in the competency involved.

That was true for me, but is no longer.

It's been especially helpful in explaining and understanding arcane bits of legacy code behavior my users ask about. I trigger Claude to examine the code and figure out how the feature works, then tell it to update the documentation accordingly.