Sorry boss, it looks like we need to hire more software engineers since the AI route still isn't mathing.
Well, Anthropic sure thinks that you should. Number go up!
Pros:
- Saved Time!
- Scalable!
- Big Bill?
Cons:
- Big Bill
- AI written codeEven better if you use an LLM with Hook support, just have the hook run formatters on the file after each edit.
Same here. It's either capable of working unsupervised or not. And if not, you have to start wondering what you're even doing if you're at your keyboard, running tools, editing code that you don't like, etc.
We're still working out the edge cases with these "Full" self driving editors. It vastly diminishes the usefulness if it's going to spend 20 minutes (and $) on stupid simple things.
> We're still working out the edge cases
Sure the air is 3 dimensions, but driving is too dynamic and volatile. Every single road is different, and you have to rely on heuristics meant for humans.
It's stupid easy for humans to tell what is a yellow line and what a stop sign looks like, but it's not so easy for computers. These are human tools - physical things we look at with our eyes. Not easy to measure. Whereas measurements in the air are quite easy to measure.
On top of the visual heuristics, everthing changes all the time and very fast. You look away from the road and look back and you don't know what you're gonna see. It's why texting and driving is so dangerous.
> I think automating driving is much harder than automating even air travel.
First, I want to summon my car. Then, when leaving, if I’m in a dense area with lots of shopping, the roads can be a pain. You have to exit right, immediately get into the left lane, three lanes over, the second of the right turn only lanes, etc
My guess is that context = main thing + somewhat unrelated thing is too big a space for the models to perform well at this point in time.
The practical solution is to remove the need for the model to figure it out each time and instead explicitly tell it about as much as possible before hand in CLAUDE.md.
They take less than a second to run, can run on every save, and are free
You could say I've seen A LOT of poorly written human generated code.
Yet, I still trust it more. Why? Well one of the big reasons is exactly what we're joking about. I can trust a human to iterate. Lack of iteration would be fine if everything was containerized and code operates in an unchanging environment[0]. But in the real world, code needs to be iterated on, constantly. Good code doesn't exist. If it does exist, it doesn't stay good for long.
Another major problem is that AI generates code that optimizes for human preference, not correctness. Even the terrible students who were just doing enough to scrape by weren't trying to mask mistakes[1], but were still optimizing for correctness, even if it was the bare minimum. I can still walk through that code with the human and we can figure out what went wrong. I can ask the human about the code and I can tell a lot by their explanation, even if they make mistakes[2]. I can't trust the AI to tell an accurate account of even its own code because it doesn't actually understand. Even the dumb human has a much larger context window. They can see all the code. They can actually talk to me and try to figure out the intent. They will challenge me if I'm wrong! And for the love of god, I'm going to throw them out if they are just constantly showering me with praise and telling me how much of a genius I am. I don't want to work with someone where I feel like at any moment they're going to start trying to sell me a used car.
There's a lot of reasons, more than I list here. Do I still prompt LLMs and use them while I write code? Of course. Do I trust it to write code? Fuck no. I know it isn't trivial to see that middle ground if all you do is vibe code or hate writing code so much you just want to outsource it, but there's a lot of room here between having some assistant and having AI write code. Like the OP suggests, someone has got to write that 10-20%. That doesn't mean I've saved 80% of my time, I maybe saved 20%. Pareto is a bitch.
[0] Ever hear of "code rot?"
[1] Well... I'd rightfully dock points if they wrote obfuscated code...
[2] A critical skill of an expert in any subject is the ability to identify other experts. https://xkcd.com/451/
What makes you think that agents can't iterate?
> I'm going to throw them out if they are just constantly showering me with praise and telling me how much of a genius I am
You can tell the agent to have the persona of an arrogant ass if you prefer it.
Think of it like an append only journal. To correct an entry you add a new one with the correction. The LLM sees the mistake and the correction. That's no worse then mutating the history.
You put in its context window some more information, then roll the dice again. And it produces text again token by token. Its still not planning ahead and its not looking back at what was just generated. There's no guarantee everything stays the same except the mistake. This is different then editing in place. you are rolling the dice again.
It is, though. The LLM gets the full history in every prompt until you start a new session. That's why it gets slower as the conversation/context gets big.
The developer could choose to rewrite or edit the history before sending it back to the LLM but the user typically can't.
> There's no guarantee everything stays the same except the mistake
Sure, but there's no guarantee about anything it will generate. But that's a separate issue.
Plus, the entire session/task history goes into every LLM prompt, not just the last message. So for every turn of the loop the LLM has the entire context with everything that previously happened in it, along with added "memories" and instructions.
> What makes you think that agents can't iterate?
Can they? Yes. Will they reliably? If so, why would it be better to restart...
But the real answer to your question: personal experience
TFA says:
Engineers use Claude Code for rapid prototyping by enabling "auto-accept mode" (shift+tab) and setting up autonomous loops in which Claude writes code, runs tests, and iterates continuously.
The tool rapidly prototypes features and iterates on ideas without getting bogged down in implementation details
I know it's a long article and the top comment is hard to find, so allow me to help
> Treat it like a slot machine
>
> Save your state before letting Claude work, let it run for 30 minutes, then either accept the result or start fresh rather than trying to wrestle with corrections. ***Starting over often has a higher success rate than trying to fix Claude's mistakes.***
Takes no time at all.
Not only can you, some providers recommend it and their tools provide it, like ChatGPT Codex (the web tool). Can’t find where I read it but I’m pretty sure Anthropic devs said early on that they kick off the same prompt to Claude Code in multiple simultaneous runs.
Personally, I’ve had decent success from this way of working.
Except the power and cooling demands of the current crop of GPU's means you are not fitting full density in a rack. There is a real material increase in fiber use because of your now more distributed equipment. (because 800gbps interconnects are NOT cheap).
You can't capitalize power costs: this is now a non-trivial cost to account for. And the more power you use for compute the more power you have to use for cooling... (Power density is now so high that cooling with something other than air is looking not just attractive but like it is going to be a requirement.)
Meanwhile the cost of lending right now is high compared to recent decades...
The accounting side of things isnt as pretty as one would like it to be.
https://archive.nytimes.com/www.nytimes.com/books/97/05/18/r...?
https://en.wikipedia.org/wiki/William_Ophuls#Leviathan_or_ob...