When people say "this is as bad as it's gonna be" and "it only gets better from here" about AI, I have Spotify to show them, no, regression is entirely possible! It used to work better but now it's like wtf and confusing.
But hey, they raised rates numerous times to pay for all those nonexistent new features. I cancelled my membership a week or two ago after yet another rate hike.
The really interesting part is what this system runs on.
Spotify built Fleet Management back in 2022 to apply changes across thousands of repos. Half their PRs were already flowing through it before any AI was involved, but only for mechanical stuff like dep bumps and config updates. Claude Code is what let it understand what the code means, not just its structure.
The thing nobody's talking about is that none of this AI automation works without Backstage doing the boring work of tracking who owns what, how things build, and what depends on what.
> a framework for applying code changes across hundreds or thousands of repositories at once
Statements like this raise fair questions. Is there code duplication across 1,000s of repos, and why respond by increasing surface area further with bespoke tooling?
> The thing nobody's talking about is that none of this AI automation works without Backstage doing the boring work of tracking who owns what, how things build, and what depends on what.
Do you mean that Backstage has the metadata like what services call which other services, and AI needs that to make changes safely? Sounds helpful to both AI and human developers ;-)
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?
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.
The macOS app is literally dead. Before AI invasion, there were frequent updates and features, but now it feels like a corpse - cold and decaying in time.
It means code review, except now you're reviewing code you didn't write, for a system you didn't design, generated by a model that can't explain its reasoning. That's a harder job than writing it yourself, not an easier one.
gck1|18 days ago
They did however, remove many useful ones.
fragmede|18 days ago
speakingmoistly|18 days ago
starkeeper|18 days ago
thegrim000|18 days ago
devhouse|18 days ago
Spotify built Fleet Management back in 2022 to apply changes across thousands of repos. Half their PRs were already flowing through it before any AI was involved, but only for mechanical stuff like dep bumps and config updates. Claude Code is what let it understand what the code means, not just its structure.
The thing nobody's talking about is that none of this AI automation works without Backstage doing the boring work of tracking who owns what, how things build, and what depends on what.
I went through the Anthropic case study, Spotify's engineering blog series, and the full earnings call transcript here https://www.everydev.ai/p/blog-spotify-built-an-ai-coding-ag...
joshribakoff|18 days ago
Statements like this raise fair questions. Is there code duplication across 1,000s of repos, and why respond by increasing surface area further with bespoke tooling?
Taikonerd|18 days ago
Do you mean that Backstage has the metadata like what services call which other services, and AI needs that to make changes safely? Sounds helpful to both AI and human developers ;-)
ryan29|18 days ago
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|18 days ago
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.
msie|18 days ago
Nextgrid|18 days ago
nikolay|18 days ago
wired_devil|18 days ago
kevincloudsec|18 days ago
ludjer|18 days ago
dave_sid|18 days ago
kevin061|18 days ago