https://newsroom-deezer.com/2025/09/28-fully-ai-generated-mu...

I got tired of the increasing AI slop in my YouTube Music feed and switched to Deezer a few months ago. Since then, not a single AI artist I've been able to spot. If a relatively marginal player like that can manage it, why can't Spotify or YTM? My suspicion is simply that Deezer actually actually tries.

It's the same problem with Google and search. Kagi and others have demonstrated that you can produce better results with an infinitesimal fraction of the budget, and Google is still plenty competent where they care to be. This won't start to get fixed until they see a financial incentive to do so.

A text interface is just really damn good at efficient and precise information delivery and interaction, in a way that takes a lot more work for a GUI to match, and they are composable in a way GUIs simply are not. Most users won't - and currently don't - care about terminals, but I doubt it will ever stop being a standard tool for power users.

I don't doubt we'll see new paradigms emerge, but I think they'll come in the form of higher level abstractions for certain classes of task rather than a replacement for the sort of TUIs and GUIs we have today.

And it shouldn't just be one person, unless they are at the very top of a small pyramid. Legal culpability needs to percolate upwards to ensure leadership has the proper incentive. No throwing your Head of Safety to the wolves while you go back to gilding your parachute.

To my thinking, to orchestrate or steer suggests a conductor or driver, an outside entity providing direction. A master agent creating and directing subagents could reasonably be called an orchestrator.

A harness is what the horse wears to pull a cart, or what connects a pilot to a parachute and provides the controls to tug on and steer. It might provide guidance or capability, but not active direction. It's also a fairly common use in hardware ( a wire harness) and software (a testing harness) already.

https://www.theatlantic.com/technology/2026/01/ai-memorizati...

If you've spent time struggling to make ends meet, even median income can feel like previously unimaginable wealth and security, and workplace satisfaction is rarely something that you had a great deal of choice around. If you've spent most of a decade making six figures with benefits, it's easier to decide an extra 10k or even 50k isn't worth the added stress.

Cost of living and personal situation (dual incomes, dependents) can shift that needle around quite a lot too.

Using AI to create an artistic work has more in common with commissioning art than creating it. Just instead of a person, you're paying the owners of a machine built on theft because it's cheaper and more compliant. It isn't really your creativity on display, and it certainly isn't that of the model or the hosting company.

The smallest part of any creative work is the prompt. The blood and the soul of it live in overcoming the constraints and imperfections. Needing to learn how to sing or play an instrument isn't an impediment to making music, it's a fundamental aspect of the entire exercise.

I think the point is well made though. When you're building something like a transactions database, the margin for error is rather low.

Actual engineers have professional standards bodies and legal liability when they shirk and the bridge falls down or the plane crashes or your wiring starts on fire.

Software "engineers" are none of those things but can at least emulate the approaches and strive for reproducibility and testability. Skilled craftsman; not engineers.

Prompt "engineers" is yet another few steps down the ladder, working out mostly by feel what magic words best tickle each model, and generally with no understanding of what's actually going on under the hood. Closer to a chef coming up with new meals for a restaurant than anything resembling engineering.

The battle on the use of language around engineer has long been lost but applying it to the subjective creative exercise of writing prompts is just more job title inflation. Something doesn't need to be engineering to be a legitimate job.

Who do you imagine will be throwing money at all these side-hustle "make money with AI" business you envision? No doubt there will be a few- there already are a few- but as the market gets increasingly flooded with AI slop enterprise with very little value add, that well is going to dry up quick.

It's not different than all those content creators making videos offering to teach you the secrets to easy money... instead of just making all that easy money themselves.

There's a long history of that sort of behaviour. ISPs gaming bandwidth tests when they detect one is being run. Software recognizing being run in a VM or on a particular configuration. I don't think it's a stretch to assume some of the money at OpenAI and others has gone into spotting likely benchmark queries and throwing on a little more compute or tagging them for future training.

I would be outright shocked if most of these benchmarks are even attempting serious countermeasures.

I echo the parent comment. I'm really on a Proton user for email and VPN. The quality drops off rather quickly after that. Calendar, Drive, Pass, and Wallet are all adequate at best; their primary selling point is not being Google rather than being particularly well built or supported. I would rather see them focus on being a truly competitive ecosystem.

I'm also not terribly impressed at the way they've positioned Lumo as a separate service from the existing Scribe AI features, and so conveniently not part of Ultimate plans.

Google's approach works well enough when you're searching for a commodity and you don't care terribly much about the specific source. I get the impression Google, especially post-LLM, wants to divorce satisfying your question from the underlying sources.

I find Kagi is better at finding a specific thing, especially if you're willing to engage with it as a tool, ye olde search engine style. If my query doesn't find what I want, it's usually apparent why and I can reframe it.

Google's case (and Meta and spam calls and others) is at least in part an incentives problem. Google hasn't been about delivering excellent search to users for a very long time. They're an ad company and their search engine is a tool to better deliver ads. Once they had an effective monopoly, they just had to stay good enough not to lose it.

I've been using Kagi for a few years now and while SEO spam and AI garbage is still an issue, it is far less of one than with Google or Bing. My conclusion is these problems are at least somewhat addressable if doing so is what gets the business paid.

But I think a real long term solution will have to involved a federated trust model. It won't be viable to index everything dumped on the web; there will need to be a component prioritizing trust in the author or publisher. If that follows the same patterns as email (ex: owned by Google and Microsoft), then we're really screwed.

But compared to using Kagi, I've found found LLMs end up wasting more of my time by returning a superficial survey with frequent oversights and mistakes. At the final tally I've still found it faster to just do it myself.

I will say I do love LLMs for getting a better idea of what to search for, and for picking details out of larger blocks.