> 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.
> 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.
> 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.
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.
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.