Perverse incentives of vibe coding

The first and most important question to ask here is: are you using a coding agent? A lot of times, people who aren't getting much out of LLM-assisted coding are just asking Claude or GPT for code snippets, and pasting and building them themselves (or, equivalently, they're using LLM-augmented autocomplete in their editor).

Almost everybody doing serious work with LLMs is using an agent, which means that the LLM is authoring files, linting them, compiling them, and iterating when it spots problems.

There's more to using LLMs well than this, but this is the high-order bit.

Yesterday I gave cursor a try and made my first (intentionally very lazy) vibe coding approach (a simple threejs project). It accepted the task and did things, failed, did things, failed, did things ... failed for good.

I guess I could work on the magic incantations to tweak here and there a bit until it works and I guess that's the way it is done. But I wasn't hooked.

I do get value out of LLM's for isolated broken down subtasks, where asking a LLM is quicker than googling.

For me, AI will probably become really usefull, once I can scan and integrate my own complex codebase so it gives me solutions that work there and not hallucinate API points or jump between incompatible libary versions (my main issue).

I've had the same issue every time I've tried it. The code I generally work on is embedded C/C++ with in-house libraries where the tools are less than useful as they try to generate non-existant interfaces and generally generate worse code than I'd write by hand. There's a need for correctness and being able to explain the code thus use of those tools is also detrimental to explainability unless I hand-hold it to the point where I'm writing all of the code myself.

Generating function documentation hasn't been that useful either as the doc comments generated offer no insight and often the amount I'd have to write to get it to produce anything of value is more effort than just writing the doc comments myself.

For my personal project in zig they either get lost completely or gives me terrible code (my code isn't _that_ bad!). There seems to be no middle ground here. I've even tried the tools as pair programmers but they often get lost or stuck in loops of repeating the same thing that's already been mentioned (likely falls out of the context window).

When it comes to others using such tools I've had to ask them to stop using it to think as it becomes next to impossible to teach / mentor if they're passing that I say to the LLM or trying to have it perform the work. I'm confident in debugging people when it comes to math / programming but with an LLM between it's just not possible to guess where they went wrong or how to bring them back to the right path as the throught process is lost (or there wasn't one to begin with).

This is not even "vibe coding", I've just never found it generally useful enough to use day-to-day for any task and my primary use of say phind has been to use it as an alternative to qwant when I cannot game the search query well enough to get the search results I'm looking for (i.e I ignore the LLM output and just look at the references).

> Is there something I'm missing? Am I just not using it right?

The talk about it makes more sense when you remember most developers are primarily writing CRUD webapps or adware, which is essentially a solved problem already.

They aren't increasing productivity. In the short term.

They are very handy tools that can help you learn a foreign code/base faster. They can help you when you run into those annoying blockers that usually take hours or days or a second set of eyes to figure out. They give you a sounding board and help you ask questions and think about the code more.

Big IF here. IF you bother to read. The danger is some people just keep clicking and re-prompting until something works, but they have zero clue what it is and how it works. This is going to be the biggest problem with AI code editors. People just letting Jesus take the wheel and during this process, inefficient usage of the tools will lead to slower throughput and a higher bill. AI costs a good chunk of change per token and that's only going up.

I do think it's addictive for sure. I also think the "productivity boost" is a feeling people get, but no one measures. I mean, it's hard to measure. Then again, if you do spend an hour on a problem you get stuck on vs 3 days then sure it helped productivity. In that particular scenario. Averaged out? Who knows.

They are useful tools, they are just also very misunderstood and many people are too lazy to take the time to understand them. They read headlines and unsubstantiated claims and get overwhelmed by hype and FOMO. So here we are. Another tech bubble. A super bubble really. It's not that the tools won't be with us for a long time or that they aren't useful. It's that they are way way overvalued right now.

I appreciate you voicing your feelings here. My previous employer requested we try AI tooling for productivity purposes, and I was finding myself in similar scenarios to what you mention. The parts that would have benefitted from a productivity gain weren’t seeing any improvement, while the areas that saw a speedup weren’t terribly mission-critical.

The one thing I really appreciated though was the AI’s ability to do a “fuzzy” search in occasional moments of need. Or, for example, sometimes the colloquial term for a feature didn’t match naming conventions in source code. The AI could find associations in commit messages and review information to save me time rummaging through git-blame. Like I said though, that sort of problem wasn’t necessarily a bottleneck and could often be solved much more cheaply by asking around coworker on Slack.

Probably 80% of the time I spend coding, I'm inside a code file I haven't read in the last month. If I need to spend more than 30 seconds reading a section of code before I understand it, I'll ask AI to explain it to me. Usually, it does a good job of explaining code at a level of complexity that would take me 1-15 minutes to understand, but does a poor job of answering more complex questions or at understanding more complex code.

It's a moderately useful tool for me. I suspect the people that get the most use out of are those that would take more than 1 hour to read code I would take 10 minutes to read. Which is to say the least experienced people get the most value.

I find it's incredibly helpful for prototyping. These tools quickly reach a limit of complexity and put out sub par code, but for a green field prototype that's ok.

I've successfully been able to test out new libraries and do explorations quickly with AI coding tools and I can then take those working examples and fix them up manually to bring them up to my coding standards. I can also extend the lifespan of coding tools by doing cleanup cycles where I manually clean up the code since they work better with cleaner encapsulation, and you can use them to work on one scoped component at a time.

I've found that they're great to test out ideas and learn more quickly, but my goal is to better understand the technologies I'm prototyping myself, I'm not trying to get it to output production quality code.

I do think there's a future where LLMs can operate in a well architected production codebase with proper type safe compilation, linting, testing, encapsulation, code review, etc, but with a very tight leash because without oversight and quality control and correction it'll quickly degrade your codebase.

Agreed, I've been thinking about the first assertion a lot recently as I've been using Cursor to create a react app. I think it's more prevalent in frontend development because it tightens the feedback loop considerably, and the more positive feedback you get, the more conditioned you get to reach for it anytime you need to do anything in code.

I think there's another perverse incentive here - organisations want to produce features/products fast, which LLMs help with, but it comes at the cost of reduced cognitive capabilities/skills in the developers over the longer term as they've given that up through lack of use/practice.

I don't believe there are perverse incentives yet, right now it's arms race burn money and operate at a loss days. There is no moat only quality and price per token and the leader moves around too quickly. Also Author should really look into Cursor at $20 with unlimited slow requests, I imagine paying per token hurts when it spits out garbage even when you've thought you provided enough context but it wasn't enough.

Someone needs to make a plugin to count lines of discard code and prompts

Something I caught about Andrej Karpathy’s original tweet, was he said “give into the vibes”, and I wonder if he meant that about outcomes too.

> It really captures how little control one has over the process, while simultaneously having the illusion of control.

This is actually a big insight about life, that in some eastern philosophies, you are supposed to arrive to

We love the illusion of control, even though we don’t really have it. Life mostly just unfolds as we experience it

But just like gambling, there are ways to do it correctly.

Yes, there are the grandmas in a trance vibe-gambling by shoving a bucket of quarters in a slot machine.

But you also have people playing Blackjack and beating the averages by knowing how it's played, maybe having a "feel" for the deck (or counting cards...), and most importantly knowing when to fold and walk away.

Same with LLMs, you need to understand context sizes and prompts and you need to have a feel for when the model is just chasing its own tail or trying to force a "solution" just to please the user.

> When you run the software yourself, or the model yourself, the incentives aligned: use less power, use less memory, use less disk, etc.

But my team's time is soooo valuable. It's sooo sooo sooo valuable. Oh and we can't afford to hire anyone else either. But our time its sooo valuable. We need these tools!

My favourite example of this is the recent trend towards “wide events” replacing logs and metrics… spearheaded and popularised by companies that charge by the gigabytes ingested.

What you are talking about is the "proper" way of vibe coding. Most of the issues with vibe coding stem from user misunderstanding the capabilities of the technology they are using. They are overestimating the capabilities of current systems and are essentially asking for magic to happen. They don't give proper guidance, context or anything of value for the coding IDE to work with. They are relying a mindset of the 2030's to work with systems from 2025. We aint there yet folks, give as much guidance and context as you can and you will have a better time.

Well, the article mentions that this reduces accuracy. Do you hit that problem often then?

Gemini on the other hand has a tendency for super-defensive coding.

It'll check _EVERY_ edge case separately, even in situations where it will never ever happen and if it does, it's a NOP anyway.

>Trying to get Image Generators to do what I want has a very "gambling-like" quality to it.

Especially when you try to get them to generate something they explicitly tell you they won't, like nudity. It feels akin to hacking.

it's not like gambling, it is gambling. you exchange dollars for chips (tokens -- some casinos even call the chips tokens) and insert it into the machine in exchange for the chance of a prize.

if it doesn't work the first time you pull the lever, it might the second time, and it might not. Either way, the house wins.

It should be regulated as gambling, because it is. There's no metaphor, the only difference from a slot machine is that AI will never output cash directly, only the possibility of an output that could make money. So if you're lucky with your first gamble, it'll give you a second one to try.

Gambling all the way down.

Same with anything though? Startups, marriages, kids.

All those laid off coders gambled on a career that didn’t pan out.

Want more certainty in life, gonna have to get political.

And even then there is no guarantee the future give a crap. Society may well collapse in 30 years, or 100…

This is all just role play to satisfy the prior generations story driven illusions.