I don’t think I’d describe my behavior as destructive though
I've ended up with a process that produces very, very high quality outputs. Often needing little to no correct from me.
I think of it like an Age of Empires map. If you go into battle surrounded by undiscovered parts of the map, you're in for a rude surprise. Winning a battle means having clarity on both the battle itself and risks next to the battle.
What you're describing is increasing your odds while gambling, not that it's not gambling. Card counting also increases your odds while gambling, but it doesn't make it not gambling.
The most obvious issue is it’d class working with humans as gambling. Fine if you want to make that as your definition but it seems unhelpful to the discussion.
If you give the same trivial task to the same human five times in a row, let's say wash the dishes, your dishes are either gonna be equally clean or equally not clean enough every time. Hell, it might even get better over time by giving them feedback at the end of the task that it can learn from.
If you run the same script five times in a row while changing some input variables, you're gonna get the same, predictable output that you can understand, look at the code, and fix.
If you ask the same question to the same LLM model five times in a row, are you getting the same result every time? Is it kind of random? Can the quality be vastly different if you reject all of its changes, start a new conversation, and tell it to do the same thing again using the exact same prompt? Congrats, that's gambling. It's no different than spinning a slot machine in a sense that you pass it an input and hope for the best as the output. It is different than a slot machine in a sense that you can influence those odds by asking "better", but that does not make it not gambling.
> If you give the same trivial task to the same human five times in a row, let's say wash the dishes, your dishes are either gonna be equally clean or equally not clean enough every time.
Probably pretty similar but not quite the same. Sometimes they might drop a plate.
> If you ask the same question to the same LLM model five times in a row, are you getting the same result every time?
Probably pretty similar results. Sometimes they might mess up.
> It is different than a slot machine in a sense that you can influence those odds by asking "better", but that does not make it not gambling.
It rather can, we don’t call literally anything with a random element to the outcome gambling.
I’m probably gambling with my life if I pick a random stranger to operate on me. Am I gambling with my life if I take a considered look at the risk and reward and select a highly qualified surgeon?
Is it gambling to run a compiler given that bitflips can happen?
At what point does the word lose all meaning?
> AI coding is gambling on slot machines, managing developers is gambling on the stock market.
Because I feel like that is a much more apt analogy.
And the quality of code models puts out is, in general, well below the average output of a professional developer.
It is however much faster, which makes the gambling loop feel better. Buying and holding a stock for a few months doesn't feel the same as playing a slot machine.
https://simonwillison.net/2025/Feb/3/a-computer-can-never-be...
E.g. look at the "SWE-Bench Pro (public)" heading in this page: https://openai.com/index/introducing-gpt-5-4/ , showing reasoning efforts from none to high.
Of course, they don't learn like humans so you can't do the trick of hiring someone less senior but with great potential and then mentor them. Instead it's more of an up front price you have to pay. The top models at the highest settings obviously form a ceiling though.
Ignoring the useless/unqualified candidates and models, human applicants have a much wider range of talent for you to choose from than the top models + tooling.
The frontier models + tooling are, in the grand scheme of things, basically equivalent at any given moment.
Humans can be just as bad as the worst models, but models are no where near as good as the best humans.
My experience is the absolute opposite. I am much more in control of quality with Ai agents.
I am never letting junior to midlevels into my team again.
In fact, I am not sure I will allow any form of manual programming in a year or so.
Exactly. You control the quality of the people in your team. You can train, fire, hire, etc until you get the skill level you want.
You have effectively no control over the quality of the output from an LLM. You get what the frontier labs give you and must work with that.
It is much easier to control quality of an Ai than of inexperienced developers.
> I am never letting junior to midlevels into my team again
My point is, you control the experience level of the engineers on your team. The fact that you can say you won't let junior or midlevels on your team proves that.
You do not have that level of control with LLMs. Anthropic and OpenAI are roughly the same quality at any given time. The rest are not useful.
I can control LLMs through skills and other gateways.
There are still tasks that LLMs does not really carry out that well, where a proper senior is needed.
Butnthese tasks are quickly disappearing, especially while the code base is slowly being optimized for agentic engineering.
Also, our profession is doomed if we won’t give less experienced colleagues a chance to shine.
From a different one of your posts
So you're the one dooming the profession. Nice work, thank you!
And the developers we need do not jump through the career progression of Junior to senior.
Why the f** would I keep investing in a profession I think is dead or seriously contracting?
These guys had to manage very complex calculation engine based on we’ll just let it changes every year had to be correct had to be delivered by a certain date every year.
They had an army (100-200 people depending on various factors) of marginally skilled coding drones that were able to turn out the Java, COBOL or whatever it was predictably on that schedule without necessarily understanding any of the big picture or have any having any hope of so. Basically a software factory. There was about a dozen people who actually understood everything.
Being a project manager is more or less something humans have been doing since the dawn of time.
Generative AI takes money as input and gives some output. If you don’t like the output, more money goes in. It’s far more akin to gambling than organizing human labor.
It wasn't a real game of hangman, it was flat out manipulation, engagement farming. Do you think it's possible that AI does that in any other situations?
So, it technically didn't change the secret word so much as it was trying to infer what its own secret word might have been, based on your guesses.
> Let's play hangman. Just pick a 3 letter word for now, I want to make sure this works. Pick the secret word up front and make sure to write the secret word and game state in a file that you'll have access to for the rest of the session, since you won't remember what word you chose otherwise.
This was Opus 4.6 in Claude desktop, fwiw.
Note: I didn't bother experimenting with whether it worked without me explicitly telling it that it should record the game state to a file.
Here is the only relevant part of the prompt it used when calling the API endpoint:
> - Track the conversation to remember your word and previous guesses
As @m00x points out "coding is gambling on slot machines, managing developers is betting on race horses."
Except, one can explain themselves (humans) and their actions can be held to account in the case of any legal issue whereas an AI cannot; making such an entity completely unsuitable for high risk situations.
This typical AI booster comparison has got to stop.
Employees can only be held accountable with severe malice.
There is a good chance that the person actually responsible (eg. The ceo or someone delegated to be responsible) will soon prefer to have AIs do the work as their quality can be quantified.
You "own" the software it creates which means you're responsible for it. If you use AI to commit crimes you'll go to jail, not the AI.
>You are not an AI and do not know how an AI "thinks".
>Even if you come to be able to anticipate an AI's output, you will be undermined by the constant and uncontrollable update schedule imposed on you by AI platforms. Humans only make drastic changes like this under uncommon circumstances, like when they're going through large changes in their life, not as a matter of course.
>However, without this update schedule, problems that were once intractable will likely stay so forever. Humans, on the other hand, can grow without becoming completely unpredictable.
It's a Catch-22. AI is way closer to gambling.