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Claude Code Unpacked : A visual guide

ccunpacked.dev

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Re: Claude Code Unpacked : A visual guide

#371
post #345

A 500k line codebase for an agent CLI proves one thing: making a probabilistic LLM behave deterministically is a massive state-management nightmare. Right now, they're great for prompting simple sites/platforms but they break at large enterprise repos. If you don't have a rigid, external state machine governing the workflow, you have to brute-force reliability. That codebase bloat is likely 90% defensive programming;…

The time is ripe for deterministic AI; incidentally, this was also released today: https://itsid.cloud/ - presumably will be useful for anyone who wants to quickly recreate an open source Python package or other copyrighted work to change its license.

Can you please explain the use here? I tried the demo, and cat, cp, echo, etc... seem to do the exact same thing without the cost.

Their demo even says:

   `Paste any code or text below. Our model will produce an AI-generated, byte-for-byte identical output.`

Unless this is a parody site can you explain what I am missing here?

Token echoing isn't even to the lexeme/pattern level, and not even close to WSD, Ogden's Lemma, symbol-grounding etc...

The intentionally 'Probably approximately complete' statistical learning model work, fundamentally limits reproducibility for PAC/Stastical methods like transformers.

CFG inherently ambiguity == post correspondence problem == halt == open domain frame-problem == system identification problem == symbol-grounding problem == entscheidungsproblem

The only way to get around that is to construct a grammar that isn't. It will never exist for CFGs, programs, types, etc... with arbitrary input.

I just don't see why placing a `14-billion parameter identity transformer` that just basically echos tokens is a step forward on what makes the problem hard.

Please help me understand.

Re: Claude Code Unpacked : A visual guide

#372

I know it seems counter-intuitive but are there any agent harnesses that aren’t written with AI? All these half a million LoC codebases seem insane to me when I run my business on a full-stack web application that’s like 50k lines of code and my MvP was like 10k. These are just TUIs that call a model endpoint with some shell-out commands. These things have only been around in time measured in months, half a million L…

[flagged]

Re: Claude Code Unpacked : A visual guide

#373

Earlier quoted context omitted.

I started that very personal project on Monday, waiting with baited breath, make sure to add a sponsor me a coffee link.

Just posted it here: https://news.ycombinator.com/item?id=47601608 Thank you so much for the coffee offer, that genuinely made my day! I don't have a sponsor link set up. Honestly, the best support is just hearing if this actually helps you ship your personal project faster without losing your mind to prompt engineering. I really hope it gives you your sanity back. Let me know how it goes!

Some of your comments have already been marked as "dead" oddly enough that just seemed like normal comments explaining your rationale.

edit: Also seems like peoples replies are getting downvoted to hell and getting marked as dead and dissapear. Someone must not like your idea :-)

Re: Claude Code Unpacked : A visual guide

#374

Earlier quoted context omitted.

Your claim was that they could implement the same app in 50k lines of code. A cursory glance at the codebase shows that it's not just a wrapper around a few APIs.

Yes, because they've vibed it into phenomenally unnecessary complexity. The mistake you continually make in this thread is to look at complexity and see something that is de facto praiseworthy and impressive. It is not.

[dead]

Re: Claude Code Unpacked : A visual guide

#375

I know it seems counter-intuitive but are there any agent harnesses that aren’t written with AI? All these half a million LoC codebases seem insane to me when I run my business on a full-stack web application that’s like 50k lines of code and my MvP was like 10k. These are just TUIs that call a model endpoint with some shell-out commands. These things have only been around in time measured in months, half a million L…

Who cares about LoC? Its a metric that hasn't mattered since we measured productivity in it in the 1980s. For all we know they made these design choices so they could more easily reuse the code in other codebases. Ideally you'd build the library to do that at the same time, but this is start up time constraints to repay loans and shit.

Bugs and vulnerabilities are roughly linear to lines of code in a project.

Re: Claude Code Unpacked : A visual guide

#376
post #318

Earlier quoted context omitted.

"Even I would have scored that goal" == "I would never ever have created a bloated mess like Anthropic" You just repeat the same statement. That bloated mess is what got them to the Champions League. They did what was necessary to get them here. And they succeeded so far. But hey, according to some it can be replicated in 50k lines of wrapper code around a terminal command, so for Anthropic it's just one afternoon of…

> Even I would have scored that goal" == "I would never ever have created a bloated mess like Anthropic" Since you keep putting words in my mouth that I never said, and keep being deliberately obtuse, this particular branch is over. Go enjoy Win11 written by same level of champions or something. Adieu.

[dead]

Re: Claude Code Unpacked : A visual guide

#378

Earlier quoted context omitted.

> they break at large enterprise repos. I don't know where you get this. you should ask folks at Meta. They are probably the biggest and happiest users of CC

You mean the company where engineers ask chat bots to write chess games in their spare time in order to hit their AI usage requirements? That Meta?

idk why you bring this up. this is irrelevant to whether CC actually works at big corps

Re: Claude Code Unpacked : A visual guide

#379
post #337

Pardon me, but I think it's rather obvious that it worked this way? The real value of Anthropic is in the models that they spent hundreds of millions training. Anyone can build a frontend that does a loop, using the model to call tools and accomplish a task. People do it every day. Sure, they've worked hard to perfect this particular frontend. But it's not like any of this is revolutionary.

Is this what perfection looks like?

[deleted]

Re: Claude Code Unpacked : A visual guide

#380

A 500k line codebase for an agent CLI proves one thing: making a probabilistic LLM behave deterministically is a massive state-management nightmare. Right now, they're great for prompting simple sites/platforms but they break at large enterprise repos. If you don't have a rigid, external state machine governing the workflow, you have to brute-force reliability. That codebase bloat is likely 90% defensive programming;…

There seem to be multiple mechanisms compensating for imperfect, lossy memory. "Dreaming" is another band-aid on inability to reliably store memory without loss of precision. How lossy is this pruning process?

It's one thing to give Claude a narrow task with clear parameters, and another to watch errors or incorrect assumptions snowball as you have a more complex conversation or open-ended task.

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