genidoi

you can use AI to understand something and map it to your own mental map

This "symbiosis" (for lack of better word) of human with AI seems to be an emergent value proposition of AI. In the process of doing stuff with AI, producing artefacts like code diffs, we are continuously able to decide how strong the mental map is of the current stage of the production process.

I could probably have worded this better but I'm sure it's something others have noticed... this choice we are able to make of how high fidelity our own understanding needs to be of the current working problem, and how that choice never really existed prior to AI.

However AI cannot meaningfully handle feedback and learn.

Well this is the central bet of AI coding isn't it? We, the humans-in-the-loop, get better at knowing ahead of time which patterns AI will handle better than others, all the while the models actually get better.

Right? The last month alone has felt like a full year of experience compressed into 30 days.

Starship at $170B is pure option value on technology still in advanced testing.

The argument that Starship is somehow an experimental/unproven technology that might fail to materialise was absurd but plausible sounding before flight 1, there were many new technologies simultaneously being deployed to a single launch system in one go.

But after 3 tower catches of the booster demonstrating centimetres of guided precision of the entire stack, this is becoming a tired argument.

I know the author is not making that case at all here, but it seems like one the core reasons to undervalue SpaceX is that Starship might not work out, and this all sounds exactly like how reusability might not work out for the Falcon 9 from 10 years ago.

Oh it is yeah.

So I asked him. "What is your developer workflow using Copilot?" I was not prepared for the answer he gave me:

I don’t know why I get annoyed when LLM’s and their output are casually referred to as “he/she”, particularly by non-techies, but I do. There’s something about personifying an LLM that seems incorrect. Perhaps it’s a fear being stoked that increasingly, people might actually be thinking of LLM’s as living beings.

We're speculating here but between time correlation, browser fingerprinting and telemetry, the average user attempting to pull off a clean compartmentalisation of two accounts has no chance, even when they think they do.

Makes you wonder if Google models how much revenue they lose specifically to this fear, because it's very real. I would simply never use GCP or Gemini because the idea of being banned from Google for absolutely any long-tail reason is a far greater cost than any benefit I could derive from those services.

There is realistically no way to evade the account correlation systems that Google (likely) has.

That can be solved by filtering out any posts made after November 2022.

Those are all arguments for why Ethereum is a bad cryptocurrency, not for why Ethereum isn’t a cryptocurrency at all.

Especially given the LLM does not trust the user. An LLM can be jailbroken into lowering it's guardrails, but no amount of rapport building allows you to directly talk about material details of banned topics. Might as well never trust it.

No vigilant insider is making a series of "single market predictions with high accuracy" on the same account. They would make unlinkable bets on fresh accounts.

You can't be sure that they are an insider or lucky, just from onchain data.

Past performance is not an indicator of future performance.

Right, you just pay daily in worrying when, not if, youtube will terminate your account and delete your "videos".

Referring to engineers with top secret+ security clearances as "consultants" seems reductionistic.

Atomic clock non-expert here, what does having a fleet of atomic clocks entail and why would the hyperscalers bother?

I didn’t catch it either on the first pass but also felt something was off about the article, as if a human had sanitised most of the AI idiosyncrasies out.

Now I have taken note to auto-distrust any “article” that lacks an author name, who is willing to personally own any accusations of the article being AI slop.

Considering that you chose to not include your name or even a HN username in the byline of the article, there is an argument to be made that you are, in fact, hiding from it.

Also three uses of a semi-colon for no reason. Nobody writes like this.

The log is the truth; the order book is just a real-time projection of this sequence.

The book is fast; the log is truth.

Matching engines can crash; the log cannot.

This is an interesting observation. One possible explanation for a lack of robust first class table manipulation support in mainstream languages could be due to the large variance in real-world table sizes and the mutually exclusive subproblems that come with each respective jump in order-of-magnitude row size.

The problems that one might encounter in dealing with a 1m row table are quite different to a 1b row table, and a 1b row table is a rounding error compared to the problems that a 1t row table presents. A standard library needs to support these massive variations at least somewhat gracefully and that's not a trivial API surface to design.

TUI libraries have sufficiently abstracted away the low-level quirks of terminal rendering that the terminal has become something like a canvas[0] available in the IDE with no extensions. This is quite a nice DevX if you want to display the state of an app that does something to data, without writing the necessary plumbing to pipe that data to a browser and render it.

[0] https://github.com/NimbleMarkets/ntcharts/blob/main/examples...

Imo the fact that an "AWS Certified Solutions Architect" is yet another AWS service/thing that is attainable, via an actual exam[0] for $300, is indicative of just how intentionally bloated the entire system has become.

[0] https://aws.amazon.com/certification/certified-solutions-arc...

where I feel so disconnected from my codebase I'd rather just delete it than continue.

If you allow your codebase to grow unfamiliar, even unrecognisable to you, that's on you, not the AI. Chasing some illusion of control via LLM output reproducibility won't fix the systemic problem of you integrating code that you do not understand.

is absolutely cruel.

What a horrible thing

They offered 6 months severance which dispels any serious notion of 'cruelty'. Substance over form.

The problem with using random real world situations as analogies for niches within Software Engineering is that they're not only (almost) ways wrong, but always misrepresentative of the situation in it's entirety

But honestly what are the examples of people losing their jobs to software?

And furthermore, what is the full causality chain that links the precise PR in provided example software to the employment termination decision? Lacking that, can you really assert the software 'automated' a dev out of the job?

This is too abstract and a concrete example of what this looks like in output is needed.

It often does[0].

[0] https://vfoley.xyz/just/