[ryan29]

I wonder how it works and how much heavy lifting "supervising" is doing. Whenever I try to use AI, the outcome is about the same.

It's good at non-critical things like logging or brute force debugging where I can roll back after I figure out what's going on. If it's something I know well, I can coax a reasonable solution out of it. If it's something I don't know, it's easy to get it hallucinating.

It really goes off the rails once the context gets some incorrect information and, for things that I don't understand thoroughly, I always find myself poisoning the context by asking questions about how things work. Tools like the /ask mode in Aider help and I suspect it's a matter of learning how to use the tooling, so I keep trying.

I'd like to know if AI is writing code their best developers couldn't write on their own or if it's only writing code they could write on their own because that has a huge impact on efficiency gains, right? If it can accelerate my work, that's great, but there's still a limit to the throughput which isn't what the AI companies are selling.

I do believe there are gains in efficiency, especially if we can have huge contexts the AI can recall and explain to us, but I'm extremely skeptical of who's going to own that context and how badly they're going to exploit it. There are significant risks.

If someone can do the work of 10 people with access to the lifetime context of everyone that's worked on a project / system, what happens if that context / AI memory gets taken away? In my opinion, there needs to be a significant conversation about context ownership before blindly adopting all these AI systems.

In the context of Spotify in this article, who owns the productivity increase? Is it Spotify, Anthropic, or the developers? Who has the most leverage to capture the gains from increasing productivity?

[Nextgrid]

There's no definitive way to tell if some code is written by AI or not; thus their statement doesn't have to be true. Usage of AI itself is nebulous, it could mean anything from OpenClaw-style automated agents to someone prompting an LLM via chat to an engineer manually writing code after wasting hours trying to get an agent to do it (that still counts as "usage", even if not ultimately productive).

The market currently rewards claims of usage of AI, so everyone is claiming to be using AI. There is no way to prove one way or another, and the narrative will be changed down the line once the market swings.

When it comes to productivity claims, I have yet to see it. If AI is truly providing significant, sustained productivity improvements across the software development lifecycle I'd expect products to be better, cheaper, or get developed faster (all of which happened with other industrial breakthroughs). I do not see that in software at large and especially not in Spotify's case.

[yndoendo]

Existing large market products and services most likely will not bring down the price of their goods and services even if AI reduces the cost to produce.

There is a saying in sales, "Money left on the table". People are already willing to pay current market value prices so they will keep doing so. Why decrease your profits when people are already willing to pay? Keeping the same pricing would maximize profits and stock, a bonus.

New companies that start producing alternative solutions would most likely be the ones to utilize the reduction in cost for producing with AI. It would be their way to get a foot in the door and start building market.

Organizations that focus on providing a good or services to the vulnerable would be an exception. Some companies that market on cost would be in that mix too.

[Nextgrid]

Fair, but in this case you'd still expect LLMs to be a massive boon to startups wanting to compete with the established players?

I'm not seeing any of that happening either, which I'd expect if the AI productivity claims were true and anyone could just vibe-code an entire sustainable business.