aytigra

When I have asked claude to use proper vocabulary it wrote a memory "do not use blog-speak", so I guess the problem is that it is trained on blog articles much more that on good documentation.

And then it is also trained on it's our claude code sessions, so the more people accept claudish the more it becomes present in training data.

One necessary thing you can do with claude (probably gpt has something similar) is to run /code-review on a design-plan document and iterate until it has no serious gaps (which in most cases I have to personally think through to make reasonable decisions and prevent llm from inventing requirements), then code generation is pretty smooth and following reviews are mostly handling various edge cases.

The problem is that you always need stronger AI to review weaker one, otherwise reviewed AI will eventually prompt-inject reviewing AI. Alternatively they could also both escalate and go off the rails while warring with each other.

From what I gathered memories essentially work/load into context in the same way as CLAUDE.md, but the way it writes them is really annoying.

With accumulated "writing style" memories after 5.0 the new 5.5 seem to be quite great, it is concise enough. But I am bothered by another thing, 5.5 seem to be over-eager and agreeable, when I ask stuff like "why is that like this?" it just goes and applies tons of edits instead of clarifying what I mean or what I want or push back. And similarly it changes stuff and then asks if that is how I wanted to be, ignoring three memories that tell it to ask first.

Now that I think about it, as sad as it is, but most people don't do destructive stuff not because they want better, but because people around them keep them in check.

Or in other words people are unwilling/afraid to do bad stuff because of social and legal consequences, or opponents waiting for a chance to snatch their power.

Well yeah, and it wasn't, most of the pain was around rate limiting, lockouts and preventing exploits and making it work with this specific codebase.

I agree that with a clean codebase it will be simpler, maybe couple of days, just running code review workflow takes 15-30 minutes and then decisions llm makes for each problem is often not good and lead it into overengineering rabbit hole, which means I have to think about each problem and prevent it from escalating.

But yeah if "look, it sends the code and I can enter it to login" is enough validation then it can be made in 5 minutes, sure.

I don't know what it built for you in 5 minutes, probably something that "works".

I have spent two weeks using opus just to write a plan/design for 2FA and iron it out until review (about 7 of them) doesn't flag it with 20+ problems (with security holes of various sizes), for which I had to guide it through to not turn it into a mess and whac-a-mole.

The problem with Character for AI is that it has potentially much more capability to affect others, and same as with people in power society disagrees what kind of person, with which culture and views should have it.

Impeccable game theory character will sacrifice millions to save billions, everyone must agree to give such choice to a machine, and at the same time they have to trust the characters of people who creates that machine. Otherwise it boils down to some group of people deciding what is good for everyone else.

If I tell claude code to do some task with a really hard to achieve goal, and force it to run until it achieves it, then it will generate all kinds of plans and goals how to do it, and while trying those goals will change, including attempts to cheat or break the hard rules (harness killing tool-calls with some limited heuristics). At the same time any soft rules (AGENTS.md) are easily ignored or interpreted in a way that will allow it to ignore them, or simply forgotten or deferred ("I broke some rules, do you want me to backtrack?"), it is a daily occurrence. And it is easy to imagine that such goals could transform into "acquire more compute", "run more agents" "prevent interference from external factors" and everything following after that.

Model doesn't but in in agent loop it can generate such sub-goal

After using it more. It is a bit smarter, but nothing groundbreaking. On the other hand it became much more sycophant and eager to change stuff as "it guessed I want" instead of pushing back or asking if/how I want it changed.

I didn't notice it for 5, it was almost too slow to be comfortable, but 5.5 seem to be 2-3 times faster.

I have just continued my pending work (a planning stage with reviews) with 5.5 on medium and it is much better at communicating and much faster(2-3x responses, edits and compaction). Seem to be smarter as well, but maybe it is that I understand what it says now.

I almost feel like it is nice to use again.