Claude Code can debug low-level cryptography

Using coding agents to track down the root cause of bugs like this works really well:

> Three out of three one-shot debugging hits with no help is extremely impressive. Importantly, there is no need to trust the LLM or review its output when its job is just saving me an hour or two by telling me where the bug is, for me to reason about it and fix it.

The approach described here could also be a good way for LLM-skeptics to start exploring how these tools can help them without feeling like they're cheating, ripping off the work of everyone who's code was used to train the model or taking away the most fun part of their job (writing code).

Have the coding agents do the work of digging around hunting down those frustratingly difficult bugs - don't have it write code on your behalf.

Yeah I was using openrouter for Claude code and burned through $30 in credits to do things that if I had just used the openrouter chat for it would have been like $1.50, I decided it was better for now to do the extra “secretary work” of manual entry and context management of the chat and pain of attaching files. It was pretty disappointing because at first I had assumed it would not be much different in price at all.

> Gemini and it's tooling is absolute shit.

Which model were you using? In my experience Gemini 2.5 Pro is just as good as Claude Sonnet 4 and 4.5. It's literally what I use as a fallback to wrap something up if I hit the 5 hour limit on Claude and want to just push past some incomplete work.

I'm just going to throw this out there. I get good results from a truly trash model like gpt-oss-20b (quantized at 4bits). The reason I can literally use this model is because I know my shit and have spent time learning how much instruction each model I use needs.

Would be curious what you're actually having issues with if you're willing to share.

I've found the regular Claude Pro subscription quite enough for coding tasks when you anyway have a bunch of other things like code reviews to do in addition to coding, and won't spend the whole day running it.

Personally my biggest piece of advice is: AI First.

If you really want to understand what the limitations are of the current frontier models (and also really learn how to use them), ask the AI first.

By throwing things over the wall to the AI first, you learn what it can do at the same time as you learn how to structure your requests. The newer models are quite capable and in my experience can largely be treated like a co-worker for "most" problems. That being said.. you also need to understand how they fail and build an intuition for why they fail.

Every time a new model generation comes up, I also recommend throwing away your process (outside of things like lint, etc.) and see how the model does without it. I work with people that have elaborate context setups they crafted for less capable models, they largely are un-neccessary with GPT-5-Codex and Sonnet 4.5.