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Claude Memory

anthropic.com

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Re: Claude Memory

#121
post #106
post #103

Earlier quoted context omitted.

> For every time that I'd get a better answer if the LLM had a bit more context on me If you already know what a good answer is why use a LLM? If the answer is "it'll just write the same thing quicker than I would have", then why not just use it as an autocomplete feature?

That might be exactly how they're using it. A lot of my LLM use is really just having it write something I would have spent a long time typing out and making a few edits to it. Once I get into stuff I haven't worked out how to do yet, the LLM often doesn't really know either unless I can work it out myself and explain it first.

That rubber duck is a valid workflow. Keep iterating at how you want to explain something until the LLM can echo back (and expand upon) whatever the hell you are trying to get out of your head.

Sometimes I’ll do five or six edits to a single prompt to get the LLM to echo back something that sounds right. That refinement really helps clarify my thinking.

…it’s also dangerous if you aren’t careful because you are basically trying to get the model to agree with you and go along with whatever you are saying. Gotta be careful to not let the model jerk you off too hard!

Re: Claude Memory

#123
post #68

Earlier quoted context omitted.

> I wish they’d stop with the anthropomorphizations You mean in how Claude interacts with you, right? If so, you can change the system prompt (under "styles") and explain what you want and don't want. > Claude doesn’t “think” anything Right. LLMs don't 'think' like people do, but they are doing something . At the very least, it can be called information processing.* Unless one believes in souls, that's a fair descrip…

When you type a calculation into a calculator and it gives you an answer, do you say the calculator thinks of the answer? An LLM is basically the same as a calculator, except instead of giving you answers to math formulas it gives you a response to any kind of text.

In what ways do humans differ when they think?

Re: Claude Memory

#124

I don't use any of these type of LLM tools which basically amount to just a prompt you leave in place. They make it harder to refine my prompts and keep track of what is causing what in the outputs. I write very precise prompts every time. Also, I try not work out a problem over the course of several prompts back and forth. The first response is always the best and I try to one shot it every time. If I don't get what…

Plan mode is the extent of it for me. It’s essentially prompting to produce a prompt, which is then used to actually execute the inference to produce code changes. It’s really upped the quality of the output IME. But I don’t have any habits around using subagents or lots of CLAUDE.md files etc. I do have some custom commands.

Cursor’s implementation of plan mode works better for me simply because it’s an editable markdown file. Claude code seems to really want to be the driver and you be the copilot. I really dislike that relationship and vastly prefer a workflow that lets me edit the LLM output rather than have it generate some plan and then piss away time and tokens fighting the model so it updates the plan how I want it. With cursor I just edit it myself and then edit its output super easy.

Re: Claude Memory

#125
post #100

I don't use any of these type of LLM tools which basically amount to just a prompt you leave in place. They make it harder to refine my prompts and keep track of what is causing what in the outputs. I write very precise prompts every time. Also, I try not work out a problem over the course of several prompts back and forth. The first response is always the best and I try to one shot it every time. If I don't get what…

> The first response is always the best and I try to one shot it every time. If I don't get what I want, I adjust the prompt and try again. I've really noticed this too and ended up taking your same strategy, especially with programming questions. For example if I ask for some code and the LLM initially makes an incorrect assumption, I notice the result tends to be better if I go back and provide that info in my init…

A wise mentor once said “fall in love with the problem, not the solution”

Re: Claude Memory

#126

This is not for Claude Code?

Claude code has had this for a while (seems old news anyway). In my limited world it really works well, Claude Code has made almost no mistakes for weeks now. It seems to 'get' our structure; we have our own framework which would be very badly received here because it's very opinionated; I am quite against freedom of tools because most people cannot actually really evaluate what is good and what is not for the proble…

It does seem like the main new thing is that, like ChatGPT, Claude will now occasionally decide for itself to "add" new memories based on the conversation. This did not (and I think does not) apply to Claude Code memories.

Re: Claude Memory

#127

I don't use any of these type of LLM tools which basically amount to just a prompt you leave in place. They make it harder to refine my prompts and keep track of what is causing what in the outputs. I write very precise prompts every time. Also, I try not work out a problem over the course of several prompts back and forth. The first response is always the best and I try to one shot it every time. If I don't get what…

but if we don't keep adding futuristic sounding wrappers to the same LLMs how can we convince investors to keep dumping money in?

Hard agree though, these token hungry context injectors and "thinking" models are all kind of annoying to me. It is a text predictor I will figure out how to make it spit out what I want.

Re: Claude Memory

#128
Dumb why don't say what it is really is, prompt injection. Why hide details from users? A better feature would be context editing and injection. Especially with chat hard to know what context from previous conversations are going in.

Re: Claude Memory

#130

I don't use any of these type of LLM tools which basically amount to just a prompt you leave in place. They make it harder to refine my prompts and keep track of what is causing what in the outputs. I write very precise prompts every time. Also, I try not work out a problem over the course of several prompts back and forth. The first response is always the best and I try to one shot it every time. If I don't get what…

Yes, your last paragraph is absolutely the key to great output: instead of entering a discussion, refine the original prompt. It is much more token efficient, and gets rid of a lot of noise. I often start out with “proceed by asking me 5 questions that reduce ambiguity” or something like that, and then refine the original prompt. It seems like we’re all discovering similar patterns on how to interact with LLMs the be…

> It is much more token efficient

Is it? Aren't input tokens are like 1000x cheaper than output tokens? That's why they can do this memory stuff in the first place.

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