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Comment by XCSme

17 hours ago

> I’m only saying that you can’t ignore the code for anything beyond a toy app

I thought the same, but I do disagree with this now. Future software development will be mostly just creating black boxes and describing what the box should do, without ever caring what is inside the box. For now, we still have to guide the AI and tell what architecture it should likely use, or which libraries should use (just for the sake of performance and ease of development), but in the future this probably won't matter either. I honestly believe code does not matter anymore. What matters is knowing what to test when building an app, how to define performance metrics and knowing what is good/possible when developing an app. I know I won't be able to create a shooting game that supports 1 million CCU on a single vCPU. But I know that the input latency should feel good, and game should run smoothly at start and over time, to tell it to implement tests to check for memory leaks and avoiding JavaScript GC pauses, use object pooling when possible, etc. The complexity moves from telling how/what to code, to knowing exactly to tell it how things should behave and what's a good outcome. If I tell it "make sure bullets are object pooled", it will likely implement it properly, as object pooling is a very common pattern that exists in its training data, and it usually either works or doesn't, when it doesn't work there are obvious issues like objects shown at the wrong positions or not spawning properly, so the issues with the code would be reflected in e2e testing anyway.

2. That was both motivating and demotivating to be honest. The app was my "baby", having spent a lot of time designing everything, optimizing, carefully choosing libraries and make cool implementation decisions. Now I feel like all the newly added features are not really mine, and it doesn't even feel like my product anymore that I can proudly say: "hey, I wrote all the code for this app". It is a really demoralizing feeling, but at the same time, I like how all my ideas can now be materialized. And it actually works. And it works well. I am still getting used to the fact that I won't have full control or understanding of how the code works, and it pains me that this is the case, but there is no way I could achieve better results by manually coding. I would rather have a feature having 90% of the ideal possible performance and UX, than not having that feature at all. Plus, that 10% is still doable, it just requires a bit of testing and asking the AI. The problem is that most of the times that effort is not really worth it, not for me, not for the clients. There are a lot of other low-hanging fruits that must be addressed, and that's how software development always worked. Now I am happy that I can actually do nice things that before I would have never spent the time on, like making sure a specific settings menu has better UX on mobile (before I would have probably just made an element smaller to fit mobile, for ok usability, but now I can tell it to design an entire new UI tailored to mobile for that specific feature).

It is definitely addictive, as it comes with instant gratification, as opposed to slowly coding and spending hours before you see any results.

I agree with your linked post, and that is sort-of a big issue (even though, most of the times, those guards are not there for the functionality itself, but for the AI, so that in case things break, it gets a more clear error of what went wrong and it knows how to fix it better). This is my entire system prompt, which I assume fixes some of that defensiveness issue:

    # Engineering style
    
    - Prefer simple, readable data flows and strong invariants over layers of defensive checks, fallback branches, assertions, and recovery mechanisms.
    - Validate at real trust boundaries, then let well-typed internal code rely on those validated contracts. Fix the source of invalid state instead of spreading null checks and guards through consumers.
    - Keep code concise and add useful comments that explain intent, ownership, or non-obvious constraints. Do not add speculative protection, tests, or abstractions without a demonstrated failure mode or requirement.
    - Use ASD-STE100 Simplified Technical English when you talk to me or caveman-like concise speech, be really direct

That just doesn’t work with current AI beyond a very small scale. I know. I’m on the team that spends our time fixing the vibe coded messes caused by people who think code doesn’t matter anymore.

I have a practically unlimited AI budget and I use it all day long. We have entire teams of very smart people trying to make it possible for PMs to turn jira tickets into features.

We ain’t there yet.

My strong suspicion is that we won’t get there without something close to AGI. And if we get there, there won’t be any white collar jobs left much less software developer jobs.

If AI can take your raw idea and turn it into code with no input from you, it will be able to generate the ideas too.

> I agree with your linked post, and that is sort-of a big issue

This was last week with frontier models. Practically what it means is that I need to audit the code. Approximate changes don’t work when you move past very small scale projects.