A lot of people are aware of public key cryptography or asymmetric encryption, its already supported as identification & authentication method in sensitive places via MTLS. The whole idea of MTLS is about the server verifying the identity of the client and one of the core concepts is validating that the client certificate is issued by some Certificate Authority that can be trusted by the server. Its Phishing resistant, meaning some one cannot trick you into giving them the your credential that they can use by accident. The client certificates could be baked into physical devices (PIC, CAC cards) or Digital certificate on your machine. MTLS is used universally for machine to machine communication, however there is a certain degree of complexity so its not used everywhere for user identity.

1. FIDO is trying to leverage the same concept and trying to make it bit easier for use compared to MTLS. The core idea is to just use it for authentication not identification. It allows the user to authentication as long as the client can prove that they have the private key for a corresponding public key

2. Passkeys were/are target for Enterprise/Workforce users. When a consumer account is hacked the impacted user is just the consumer, whereas when an Employee account is hacked the entire company is at risk.

3. Passkeys/ (WebAuthn+CTAP) have been there for a while. Its still still evolving and everyone (platforms, Browsers, OS, Password managers, IDPs) wants to get something out of it which keeps on making it more complex

Since the client/authenticator is storing the private key, its important to ensure that they are doing it in a uniform and secure way. The authenticator implements a protocol called CTAP and they are supposed to conform to certain tests. The attestation is a means to ensure that the authenticator is doing the least minimum from security perspective.

Personally I do not like the idea of centralization, however as long as the path to attestation for different passkey providers is not locked I would say the attestation is a part of security.

At the same time the things I would worry about would be if the Authenticator provider starts generating a unique attestation for every user in customer identity space (its almost 0 cost in case of software based authenticators). A unique certificate for every authenticator instead of a batch one is where the privacy would be leaked, its akin to fingerprint. Some big companies are already doing it for their employees, thats a valid use case, employees unfortunately do not have a privacy when they are acting on behalf of the company

1. There is no way he the the only one or first one. Chances are that more than likely he was subscribing to some third party services which were offering this feature.

2. He probably took it too far to get noticed and get in limelight

> https://www.githubstatus.com/ Their status page records the outage anywhere between 6 to 17 minutes across the different features. The detailed status page clearly has recorded time of when the errors were escalated, when the fix was applied and when it was assumed that the system has recovered. Its clearly a lot more than 17 minutes, infact its more than an hour.

Unless there is something more to it, these status pages feel like a blatant lie, wondering how long before some one actually sues them cause they are publishing/advertising wrong SLAs.

Another example

> https://www.githubstatus.com/incidents/0rn90wk115q9

> On September 13, 2026, between 08:43 and 10:44 UTC

The status page records the incident outage duration as 1 hour 12 minutes

A bot talking to you directly as if its some one real caters to your thoughts and can take you in a certain direction without you realizing it. I have heard first hand experience from people that they feel more comfortable talking to chatgpt or claude cause it gives a feeling of being on their side and listening to them.

> “Those agents are doing exactly what they’ve been asked to do,” LeCun said. “They were supposed to be in sandboxes, but the sandboxes were leaky and horribly designed.” Many AI labs lack a fundamental understanding of cybersecurity

However it does not changes the fact that some damage was done. There are two things that are happening with the AI evolution which can lead to hard situations

1. Replacing deterministic systems with probabilistic systems in an attempt to get more features

2. Making critical systems available on internet to leverage integration with LLMs (AI agents need to connect with remotely hosted LLMs to be able to work) which were otherwise in DMZ (demilitarized zone)

1. This is a race against time for money, folks are skipping everything possible in this race, Security systems and ensuring guardrails are there is going to take investments both in time and money

2. The narration has been changed by investing PR money into what otherwise should be classified as criminal activity. What exists now is a positive spin to all this and tout it as a capability rather than their lack of good security practices. So much so that every model provider is coming up by themselves to share how their models went rouge. At this point the valuation of the company is tied with what their models can hack so its probably not wrong to say that these companies may actually be incentivized to do this instead of preventing it

> If you have m distinct values in an index, then listing them this way takes m log(n) time, which is fine for many use cases no matter how much data you have.

And NO the runtimes are not right away applicable on machines at scale. You are dealing with DB locks, page sizes, available memory, existing data in memory, queue depth. Experienced folks get paid to short circuit such learnings

Based on my experience queries like these cannot scale, whatever you do. However if you are already on a path where you had invested a lot in such queries then hire a DBA, if you are not far off then hire an architect to model the data for better performance.

What bothers me the the marketing angle which invites skepticism and criticism

> Anthropic invited Matt von Hippel to write this post and compensated him for his time.

If you are paying some one, tailoring the discussions then the end result is always going to be biased one showing yourself as the winner. I understand its somewhat organic, still the ratio of marketing and science needs to be balanced. Marketing has to be correct and the results/outcomes should be reproducible

Few days ago my son was working on a problem which asked if square is a rectangle. Turns out his class teacher and external tutor (who was using AI) had different opinions on it. My wife consulted AI as well and she also came to the conclusion that square is not a rectangle cause AI told her so, AI told the same answer to external tutor. I understand that the context matters and if one probes AI more with additional context it may come up with correct answer, but this depends on the assumption that the person asking AI for something already knows the answer.