How a website is going to identify your PI as non-fake? Isn't that the entire business model behind Persona which has been in the news for leaks? (There are a few websites I've had to verify my if I with them for)
Meta is a huge competitor. The have less fewer ads for directed searches of course, but know you were browsing products on the web so can spam you all over for the types of things you were shopping for.
Have you seen documentation that the thoughts in Claude Code are slipped out separately, authoritative or otherwise? I've heard this claimed a few times and wondering what they're doing differently from traditional thinking models.
What people typically mean by the GP statement is that the “thinking” mode of these models is loosely analogous to what humans do: a bit of a retrograde reconstruction of how we arrived at a gestalt conclusion that sounds good, but may not accurately reflect the real logic at play.
IME you can see this more easily with less-polished models like Deepseek 3.X, where the reasoning in the thinking traces occasionally contradicts or has zero bearing on the non-thinking output.
But they are actual tokens produced, that are then read by the answer generation as part of the prompt, nonetheless. And the hidden state of course has a ton of logic that may not be apparent by the tokens produced as well!
Unlike humans, this thinking cannot possibly be retrograde, since causal masking means it is strictly generated before the answer and cannot be affected by it (though the model may have some concept of an answer by the time it starts generating the thinking tokens, and there is no guarantee the thoughts generated by thinking are actually attended to by the text generation).
Agreed - I use AWS at work and try and keep the services we use to a minimum. S3 and DynamoDB are ones that somewhat lock us in but the way we use them, they are replaceable (not relying on any niche features). The different queue services would definitely be harder to swap out though.
To some degree IMO big data is still a mindset when it might take a day to process your data in a normal SQL query. Some tech doesn't scale to the data size for all use cases, and you need different solutions.
Writing syntax is still an important part of the experience. It is valuable because it requires you to spend time immersed in the nuts and bolts that hold software together. I'd compare it to cooking, if you have an assistant or a machine do everything and you never actually touch a knife or stir a pot, you'll lose your touch. But there is also something valuable about covering more ground and the additional experience that brings.
Totally! I mean, the same could be said of painstakingly hand coding assembly language - that today's developers haven't done so is what leads us to bloated electron apps, so there is something lost!
But the larger scale system design is stronger than ever. Today, distributed systems, version control, including branching, stacked PRs etc., VMs/containers, idempotency, multimaster ACID databases, all of these things were probably never achievable in the world when the best devs had to spend their time poring over assembly language every day. Losing that skill allowed them more time to build other ones!
Why are you focusing on syntax so much? There's more to that when writing code.
That's why students learn how to write pseudo-code before picking up a programming language. Learning how to think through implementing a solution to a problem is extremely important. It's exactly this experience that helps engineers grow their scope and understand bigger, more complex system.
There's also the tactical components of using programming languages. The only way to know when to use one type of data structure over another, or to debug tricky language-specific behavior is _to actually have used that language._
And it's exactly this knowledge that's being threatened by LLMs given how they are implemented today.
> Sure, there's a very gradual, strictly limited, tightly controlled rollout
By city and ODD, but if you are in the area and your source and destination for the route are both within the ODD they are just as available as an Uber.
At the very least you should give it a non-prod copy of the database, not direct access to the DB actively powering production right now.
I've done work for a hedge fund where the DB ran directly on the manager's desktop. I worked with my local copy and sent an update script, and he had a second copy he ran on to verify.
Even with humans you shouldn't be working directly against the prod DB in these cases!
Yes, I just think there's a sane way to do things that is not "never let LLM agents do things".
For dev/prod staging though, there's that other story on HN right now of an LLM agent that maneuvered it's way to prod credentials and destroyed prod. And backups went along with it. I'm paranoid enough to think backups in this use case means out-of-band uncorrelated storage.
I just think there's more nuance to it. Some things have an implicit RTO/RPO/SLA of say a day. Risk is also correlated to recovery and rollback. And there's levels of LLMs out there.
Surely in the Venn Diagram of things, there's a slot where it's okay let a Claude Opus agent run on a process with good backups/recovery? Where taking the risk of a 1-hour restore job is worth the LLM agent velocity?
For extra paranoia, surely even Opus/Mythos can't figure out how to destroy log level backups to immutable storage.
The only nuance I can see is, does the data matter at all? If it does you shouldn't do this. If it doesn't then who cares, also why even put it in a database.
If the cyclist was doored by an exiting passenger, would t that imply it should further block the bike lane to increase safety as it is not safe for a bike to pass while a passenger is exiting? If the car door opening is what injuries the cyclist it wasn't really in the bike line very far.
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