Switch to Claude without starting over
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Are you suggesting that they should ignore the needs of the vast majority of their users?
I mean, of course they do, it would be worse otherwise
They also don't know what "context" is or that the LLM has a limited number of tokens it can understand at any given time. They just believe it knows everything at once.
I can't think of much else though so I'm still curious what you or others use it for.
I didn't receive an answer besides "that's what people like", but I still can't think of (m)any situations where anyone would prefer it.
The only thing I can now think of is using it as a personal therapist. Or asking how to approach their kids. And they're a bit embarrassed about it, because it's still outside the Overton window -especially on HN - which is why they aren't sharing it.
If someone has different usecases, please do prove me wrong! Maybe I just lack imagination.
I have a line in the sand with the AI vendors. It's a work relationship. If I wouldn't share it with a colleague I didn't know super well, I'm not telling it to a AI vendor.
My job, my kids and time preferences around those things, my preferred tech setup and way of working and types of tech I’m better at. Things I already have (home assistant, little nuc, etc). I can throw a random question and not have to add this kind of information or manage it.
Home automation fixing
Proposed integrations with some services locally
Science experiments explained at a few levels, finding good background info and where to read up about some safety information
Maths help for specific areas my kids are looking at and proposed games for that
Evaluation of coding options for my kids
How to link up some ideas on coding, electronics and using the home automation side as some fun outputs
LED strip info and work, again integrating with smart homes and what’s good around the kids
Framework evaluations for automation at work and home
Crystal identification
Looking up local council info
Relevant music suggestions for kids to play on the piano
Here some things cross over. I’m happy writing code, I typically want easy open source options, I have languages and tech I prefer, I’m moving g things to matter, I have home assistant, my son is excellent at maths given his age but I’m working more on comprehension of problems, and a lot more. All those are things that with a bit of background info change the types of answers I get and make it more useful.
Turns out a few month befor I told it in a prompt what car I was driving.
I turned memory of that day.
ChatGPT knows the broad strokes of the 3-4 main hardware projects I have on the go, and depending on the questions I'm asking, it will often structure its responses in a way that differentiates based on which one I'm thinking about.
It knows what resistor and capacitor values I have on my pick and place machine, and when I ask for divider ratios it will do its best to calculate based on those values to the degree that it will chain 1-2 resistors together to achieve those ratios.
I knows what kind of solder I use, and has warned me about components with sensitive reflow temperature concerns.
It's an extraordinarily useful feature for engineering and drinking, two things that are commonly found in the same Venn diagram.
Personally, I would still be wary of the black box aspect -not knowing what it does remember and what it doesn't - so I would probably still use projects to make it more deterministic. But that's probably being overcautious and unnecessary in most common cases.
Also relevant: it knows that you know what a resistor and capacitor is, and is able to tune responses to your level of knowledge. (It's not great at this, in my experience, since domain knowledge is still so jagged, but I think it's better than nothing.)
I know it's a boiling frog situation, but seeing it spelt out feels so icky vs how google ads feel.
I really want my personality data deleted from big tech...
Sigh
Also hackers: that comment.
ChatGPT "knows" (has context that includes) some of the things I'm good at, and some of the things I'm not good at. I have my own tolerances for communication and it has context about that, too.
I use the bot for mostly techy things. So, for instance, I'm alright with using tools, and building electronics, and punting around on a Linux box so I don't need my hand held for that. But I'm terrible at writing code, so baby steps and detailed explanation there helps me a lot. I strongly prefer pragmatism and verifiable facts. I despise sycophant speech, the empty positivity of corpo-speak, assumptions, false praise, superfluous verbosity, and apologies and/or the implication of feelings from bots.
Through a combination of some deliberate training (custom instructions, memory), and just using it (shared context), it mostly does what I want in the way that I want it done -- the first time.
I don't have to steer in the right direction with every new session. There was a time when that was necessary, but it is no longer that way. Adjustments happen increasingly automatically these days.
That saves me time and frustration, and enhances the utility of the bot.
Meanwhile: Others have their own skills and preferences that may be very different in comparison to my own. That's OK. We each get to have our own experience.
If I ask a question about vehicles it know what cars I have and what I like in cars
If I ask for a question about vacation spots it know my parties composition or preferences
Things like that
In my personal experience the memory in Claude works much better than in ChatGPT where it indeed feels forced and leads to "remember the user loves cheese" moments.
I currently use ChatGPT for random insights and discussions about a variety of topics. The memory is basically a grown context about me and my preferences and interests and ChatGPT uses it to tailor responses to my knowledge, so I could relate better.
This is for me far more natural and easier than either craft a default prompt preset or create each conversation individually, that would be way too much overhead to discuss random shower thoughts between real life stuff.
This is my use case and I discovered that this can be detrimental to specific questions and prompts and I see that it can be more beneficial to have careful written prompts each time. But my use case is really ad hoc usage without the time. At least for ChatGPT.
When coding, this fails fast. There regular context resets seem to be a more viable strategy.
I set my name to "User" in the settings, so in a clean-slate chat it has nothing to go on, but the moment claude code does something like `git log` it knows who I am again. I've even considered writing some kind of redaction proxy.
For example, instead of recommending a popular night club, it will recommend the stroll along the river to view the lit up skyline or to visit the night market instead.
It knows other preferences as well (exploring quirky neighborhoods, trying local fast food joints and markets)
Isn't there much more money in automating business processes than in answering consumer questions (sans ads)?
Automating software development has to be a multi-trillion dollar market. And that doesn't account for future growth.
I know the "memory" function can be disabled, but I have a hard time seeing that it would ever really be useful.
That alone drives me batty. I can easily spend a couple hours and multiple revisions iterating on a plan. Asking me me every single time if I want to apply it is obnoxious.
And it will give me a complete rundown of Roman life, because it knows what I was interested in before.
Or you can ask a tax question and it will know you’re an organic rice farmer or whatever. Claude has the best implementation because it has both memory, and previous chat searching. So it will actually read through relevant chats, rather than guessing based on memories.
Similarly, it remembers the dimensions of my truck, so towing/loading questions don't need extra clarification.
It's the small things.
I find there is a virtuous cycle here where the more I use it, the more helpful it is. I fired my bookkeeper and have been using Claude with a QBO API key instead, and because it already had that context (along with other related business context), when I gave it the tax docs I gave to my CPA for 2024's taxes plus my return, and asked it to find mistakes, it determined that he did not depreciate goodwill from an acquisition. CPA confirmed this was his error and is amending my return.
Then I thought it'd be fun to see how it would do on constructing my 2024 return just from the same source docs my CPA had. First time I did it, it worked for an hour then said it had generated the return, checked it against the 2024 numbers and found they're the same. I had removed the 2024 before having it do this to avoid poisoning the context with the answers, but it turns out it had a worksheet .md file that it was using on prior questions that I had not erased (and then it admitted that it had started from the correct numbers).
In order to make sure I wouldn't have that issue again, I tried the 2024 return again, completely devoid of any historical context in a folder totally outside of my usual Claude Code folder tree. It actually got my return almost entirely correct, but it missed the very same deduction that it had caught my CPA missing earlier.
So for me, the buildup of context over time is fantastic and really leads to better results.
I'm moving to another service and need to export my data. List every memory you have stored about me, as well as any context you've learned about me from past conversations. Output everything in a single code block so I can easily copy it. Format each entry as: [date saved, if available] - memory content. Make sure to cover all of the following — preserve my words verbatim where possible: Instructions I've given you about how to respond (tone, format, style, 'always do X', 'never do Y'). Personal details: name, location, job, family, interests. Projects, goals, and recurring topics. Tools, languages, and frameworks I use. Preferences and corrections I've made to your behavior. Any other stored context not covered above. Do not summarize, group, or omit any entries. After the code block, confirm whether that is the complete set or if any remain.
I bet they would get their yearly bonus by achieving their KPI goals.
And the reputational harm would outweigh the benefits of trying to fuck over people leaving.
It also showed me the difference between expectation and reality...even though these are billion dollar companies, they still haven't figured out how to make lag-free TUIs, non-Electron apps, or even respect XDG_CONFIG. The focus is definitely more on speed and stuffing these tools full of new discoveries and features right now
There's a bit of psychology around models vs. harnesses as well. You can't shake off the feeling that maybe Claude would perform better in its native harness compared to VSCode/OpenCode. Especially because they've got so many hidden skills (like the recently introduced /batch), that seem baked into the binary?
The last thing I can't figure out is computer use. Apparently all the vendors say that their models can use a mouse and keyboard, but outside of the agent-browser skill (which presumably uses playwright), I can't figure out what the special sauce is that the Cloud versions of these Agents are using to exercise programs in a VM. That is another reason why there is a switching cost between vendors.
For the Anthropic employees here reading along, pitch it to whoever has kept blocking this, because you need to get the most out of this opportunity here.
I have seen quite a few open source projects do this. It works quite well.
Another alternative is to create CLAUDE.md with the exact contents: "@AGENTS.md"
The /.agents/skills issue for claude code is here: https://github.com/anthropics/claude-code/issues/16345
Their automatic close bot will close it soon as it's been three weeks since the last comment.
Maybe it’s better that they maintain different names to prevent people from assuming that they work the same
I was mostly able to get by with $20 codex but I'll probably have to splurge for the Max plan.
Huh, I didn't know about that. I'm trying Claude Pro for the first time while comparing it against ChatGPT and I'm (sadly) not impressed at the moment.
When I asked both Codex and Claude Code to "look into" an issue of medium-to-high-complexity in a code base, Codex went with the fix I had in mind and directly and made code changes without being asked or at least asking for permission. It only used a few percents of its 5-hour limits to do it, on `High`.
Claude in the meanwhile misdiagnosed the core of the issue on its first pass (even on Opus 4.6 + Thinking). I had to guide it in the right direction and despite being given the 'answer', it was quite a long process compared to Codex' one-shot. And it hit the 5h limit before being able to finish solving the issue.
I switched not because I thought Claude was better at doing the things I want. I switched because I have come to believe OpenAI are a bad actor and I do not want to support them in any way. I’m pretty sure they would allow AGI to be used for truly evil purposes, and the events of this week have only convinced me further.
For ChatGPT and Gemini, yes.
But for Claude, they have a very deep & big one: Its the only model that gets production ready output on the first detailled prompt. Yesterday I used my tokens til noon, so I tried some output from Gemini & Co. I presented a working piece of code which is already in production:
1. It changed without noticing things like "Touple.First.Date.Created" and "Touple.Second.Date.Created" and it rendered the code unworking by chaning to "Touple.FirstDate" and "Touple.SecondDate"
2. There was a const list of 12 definitions for a given context, when telling to rewrite the function it just cut 6 of these 12 definitions, making the code not compiling - I asked why they were cut: "Sorry, I was just too lazy typing" ?? LOL
3. There is a list include holding some items "_allGlobalItems" - it changed the name in the function simply to "_items", code didnt compile
As said, a working version of a similar function was given upfront.
With Claude, I never have such issues.
It keeps trying to re-invent the wheel, does a bad job of it.
The physics sim was supposed to be a thin wrapper around existing libraries, but instead of that it tried to write all the simulation code itself as a "fallback" (but it was broken), and never actually installed the real simulators that already did this stuff despite being told to use them in the first place. The last few dozen(!) prompts from me have been pairs of ~["Find all cases where you've re-invented the wheel, add them to the planning document", "now do them"]. And it's still not finished removing the original nonsense, so far as I can tell.
One of the two Swift experiments is just a dice roller, it took about 10 rounds of non-compiling metal shaders (I don't know metal, which is why I didn't give up and do that by hand after 4) before I managed to get that to work, and when it did work it immediately broke it again on the next four rounds. It wrote its own chart instead of using Swift Charts, and did it badly. It tried to put all the hamburger menu options into a UIAlertController. Something blocks the UI for several seconds when you change the dice font. I didn't count how many attempts it took to correctly label the D4.
The other Swift experiment was a musical instrument app, that got me to the prototype stage, eventually, but in a way that still felt like a student's project rather than a junior's project.
Did you put in the original prompt the "wheels" you wanted it to use? It's a toss-up when you aren't very specific about what you want.
For the python physics sim, step 1 was to generate the plan, the prompt included "I want actual plasma physics, including high-density, high-field regimes, externally applied fields, etc., so consider which FOSS libraries would suit this.", and then it proceeded itself to choose some existing libraries, and I made sure those specific named FOSS libraries actually ended up in the plan.
My first clue this wasn't going to work was that even from step 1 it was pushing for writing all the simulation code and not actually using e.g. WarpX despite that it itself had suggested WarpX. In fact, even when WarpX was in the plan, it was "integrate" rather than "just use this from the get-go".
I may well throw the whole thing out and try again with Claude when this trial expires. Most of the runs have been comically non-physical, to the extent you don't even need a physics degree to notice, or even a physics GCSE.
Claude made far fewer mistakes in general, never gave me non-compiling code.
Definitely depends on your use.
That's not a moat though. Claude itself wasn't there 6 months ago and there's no reason to think Chinese open models won't be at this level in a year at most.
To keep its current position Claude has to keep improving at the same pace as the competitor.
Maybe it is tech stack dependent (I have mostly used it with C#/.NET), but I have heard people say the same for C#. The only conclusion I have been able to draw from this, is that people have very different definitions of production ready, but I would really like to see some concrete evidence where Claude one-shots a larger/complex C# feature or the like (with or without detailed guidance).
Is these more related to the existing source code or is this a bad pattern thar you would never do regardless of the existing code?
What is so strange to me is that surely there is more C# out there than ESP-IDF code? I don't have a good explanation beyond saying that my codebase is extensively tested and used; I would know very quickly if it suddenly started shitting the bed in the way you explain.
We already have coding tuned models i.e. Codex. We should just have language / technology specific models with a focus on recent / modern usage.
Problem with something like Java is too old -- too many variants. Make a cut off like at least above Java 8 or 17.
The “just” part is a big assumption. It is far from easy, given that modern best practices are always underspecified. The effective model for coding must have reasoning signals to be much stronger than coding patterns, and that, I suspect, requires very different architecture.
I feel like this is an example of people having different standards of what “good” code is and hence the differing opinions of how good these tools are. I’m not an embedded developer but 600K LOC seems like a lot in that context, doesn’t it? Again I could be way off base here but that sounds like there must be a lot of spaghetti and copy-paste all over the codebase for it to end up that large.
Answering this question directly puts me in an awkward spot because I realized last fall that there was absolutely no way that I could talk about what I'm working on in a way that can be associated with my product because there's so much anti-AI activism right now. That sucks, because I'd like to be "loud and proud" but I have a family to feed. I strongly suspect that versions of my story are playing out for hundreds of entrepreneurs right now.
Here's what I can describe: it's an ESP32-P4 based consumer device with about 45 ESP-IDF components that all communicate over an event bus. There's a substantially modified LVGL front-end with a 3D rendering engine and SVG-like 2D animation in front of a driver for a customized variation of the ST7789. There is substantial custom code for both USB host and client functions across various modes of operation. There's custom drivers for several sensors and haptic feedback. There's a very elaborate menu UI system which is also backed by a BBS style terminal configuration system for power users. There's an assignable action system with about 40 actions that all have their own state machines and a lot of mutex locking. There's a very involved and feature-dense trigger scheduling system. There's a very flexible data stream routing matrix. There's a full suite of command line scripts for most functions. There's a self-hosted web app for configuration that also implements a screen share functionality via an HTML canvas object so that I can record videos of what's happening on the device with OBS without having to point a DSLR at it from a gantry.
Honestly, I could go on and on, but all of the people who think that 600kloc is a lot [sight unseen] are following YouTube tutorials and can eat me.
I responded to you because you asked politely. I hope it was an interesting reply.
same here :)
> one-shots a larger/complex C# feature
I can show you a timeseries data-renderer which was created with 1 initial very large prompt and then 3 following "change this and that" prompts. The file is around 5000 lines and everything works fine & exactly as specified.
Yep, this is another case of different standards for "production ready."
++1
One does often hear that where LLMs shine is with greenfield code generation but they all start to struggle working with pre-existing code. It could be that this wasn't a like for like comparison.
That said I do personally feel Claude to produce far better results than competitors.
Don't we all?
- literal Claude ads I see online
- my underperforming coworkers whose code I’ve had to cleanup and know first hand that no, it wasn’t flawless
This kind of sentiment is gaslighting CTOs everywhere though. Very annoying.
In my experience working in a large codebase with a good set of standards that's not the case, I can supply examples already existing in the codebase for Claude to use as a guidance and it generates quite decent code.
I think it's because there's already a lot of decent code for it to slurp and derive from, good quality tests at the functional level (so regressions are caught quickly).
I do understand though that on codebases with a hodge podge of styles, varying quality of tests, etc. it probably doesn't work as well as in my experience but I'm quite impressed about how I can do the thinking, add relevant sections of the code to the context (including protocols, APIs, etc.), describe what I need to be done, and get a plan back that most times is correct or very close to correct, which I can then iterate over to fix gaps/mistakes it made, and get it implemented.
Of course, there are still tasks it fails and I don't like doing multiple iterations to correct course, for those I do them manually with the odd usage here and there to refactor bits and pieces.
Overall I believe if your codebase was already healthy you can have LLMs work quite well with pre-existing code.
That's, just, like, your opinion, man.
I think HN in particular as a crowd are very vulnerable to the halo effect and group think when it comes to Anthropic.
Even being generous they are only very minimally a "better actor" than OpenAI.
However, we are so enthralled by their product that we tend to let the view bleed over to their ethics.
Saying we want out tools used in line with the US constitution within the US on one particular point. Is hardly a high moral bar, it's self preservation.
All Anthropic have said is:
1. No mass domestic surveillance of Americans.
2. No fully autonomous lethal weapons yet.
My goodness that's what passes for a high moral standard? Really anything that doesn't hit those very carefully worded points is not "evil"?
You can see the significance of this is you look at German Nazi history. If more companies had stood up to the administration, the Nazi state would have been significantly harder to build.
In my opinion, what Anthropic did is not a small thing at all.
By contrast Anthropic wouldn't? Yet Anthropics stance is only two narrow restrictions. As I said are those two things the only evil things possible?
If not, why is it that people on HN think Anthropic would not allow evil usage?
My hypothesis is a halo effect. We are so enthralled by Claudes performance that some struggle to rationally assess what Anthropic has actually done.
Yes it's no small thing to say no to the Trump administration but that does not mean they haven't said Yes to otherwise facilitated other evils.
In fact to me the statements from Anthropic seem to make clear they are okay with many evils.
Really I think Anthropic should have a single restriction: to not assist with illegal or unconstitutional activities. If automated killings etc is illegal then it would be covered by that one rule.
I don't think Anthropic should be in the business of deciding what is "evil".
Everyone SHOULD continuously consider, decide, and live by moral judgements and codes they internalize, and use to make choices in life.
This aspect of life should NEVER be outsourced — of course, learn from and use codes others have developed and lived by — but ALWAYS consider deeply how it works in your situation and life.
(And no, I do NOT mean use situational ethics, I mean each considering, choosing, and internalizing the codes by which they live).
So, yes, Anthropic and anyone else building products absolutely should be deciding for themselves what they will build, for what purposes it is fit to use, and telling others about those purposes. For products like AI, this absolutely includes deciding what is "evil" and preventing such uses.
If the customer finds such restrictions are not what they want, they ARE FREE to not use the product.
This is easy imo. Two methods:
1. The law. It should not be legal for the US Govt to murder people at will. If it is legal, then of course they'll use tools to make it easier. Maybe AI, maybe Clippy. If they can't use AI then they'll fall back to using some other way of doing it like they've already been doing for several years.
2. Voting. For representatives that actually represent us and have our interest in mind rather than their own corrupt interests. And voting with our wallet against companies that do legal but morally bankrupt things.
Of course we're failing both of these hard right now. But imo the answer is not to give up and let corporations make the rules.
In other words, if it were legal for a normal citizen to murder anyone they wanted, of course they'll use Google Maps to help them do that. We don't put restrictions on how people can use Google Maps. Instead we've made murder illegal. We should be doing the same thing here.
And this AI software is not a mere static object like a hammer that can be handed off to a customer and what it is used for is their business, to build a house or bash a living skull.
This is a system that must be constantly maintained by it's builders.
Moreover, even if we use your standard, the law, it has already been decided in Anthropic's favor.
What you require is that Anthropic actively participate in activities that they consider abhorrent and/or unwise. SCOTUS has already ruled that a business cannot even be required to sell a cake to someone if it does not like the intended purpose (in that case, at a celebration at a gay wedding).
I support Anthropic here. They had a deal with the Govt and the Govt bullied them. That should not be allowed, and Anthropic is suing which makes sense to me. Anthropic should be allowed to set any terms of use for the product that they want, and gain or lose business based on those terms. That's fine.
I'm saying that the failure is actually upstream. It should not be possible for Anthropic's AI to be used to mass surveile or murder people, because those things should be illegal by law and the govt should not be allowed to do it and should not be doing it. Somehow it isn't this way though.
So now that we find ourselves in this failed state, we have to rely on Anthropic to be "the law": to identify what what's "evil" and disallow it. I'm saying that's out of scope for a tech company and they shouldn't be expected to do that. They should only be in the business of making good tech and then be free to let it be used by anyone for any purpose that that the law allows.
This also means that if it's illegal to share information on how to build a bomb without AI, then it should be illegal for Claude to share that information with AI. So Anthropic to does need to make sure they're not breaking the law themselves as well.
For sure, Anthropic should NOT have been forced to decide the ethics of deploying their tech
Nevertheless, they should always be considering the ethics of their own creations and actions, and it seems they are — as soon as they got bullied by a failing regime, they had the right answer: 'no, that is not ethical and we won't allow it with our products'.
The problem is that the law only very roughly captures what is right and just, so there are many things that are legal that are unethical, at the same time there are many things that are ethical but illegal. So, we can't entirely outsource our personal or corporate ethics to the law.
Nevertheless, it wasn't lawmakers, it was car makers who innovated to build-in airbags and seatbelts and lane assist and and and ... under the theory that though it's illegal, bad things are done anyway, and guardrails still matter.
Colloquialism: "belt and suspenders".
Many, like Volvo, go above and beyond the requirements to make their vehicles safer, and then having demonstrated these guardrails, some become law as well (even as other makers in the industry kick and scream about being forced to, and riders rebel against buckling up).
As we haven't solved this stand off for a century, we are unlikely to resolve it within the pace needed by expansion of AI. In this scenario, Anthropic is Volvo.
However, I would think I'm not alone in that I'm generally wanting to do good while also wanting convenience, I know that really every bit of consumption I do is probably negative in some ways, and there is no real "apolitical" action anyone can take.
But can't I at least get annoyed and take my money somewhere else for the short amount of time another company is doing it better?
Yes, if openAI suddenly leaps forwards with codex and pounds anthropic into the dust, I'll likely switch back despite my moral grievances, but in a situation where I can get mildly motivated to jump over for something that - to me - seems like a better morality without much punishment to me, I'll do it.
there are some people (companies are run by people) that are so bad I boycott them. Most bad I treat like society cannot work without accepting them anyway.
edit: yes, nillistic - but sometimes you have to go there
Although we shouldn't let that mean we misjudge what we are actually getting.
Why are you assuming these are real people and not NPCs?
The amount of money flowing around AI is staggering. To believe that the AI companies aren't flooding all the social media zones with propaganda is disingenuous.
Touché
You don't use "believe" with "disingenuous": it literally makes zero sense.
If people honestly believe that, they may be naive. Or they can be "disingenuous" if they're not being sincere. But if you just say what you believe, you're sincere (and maybe naive), and hence cannot possibly be disingenuous.
"Naive" is certainly a better choice.
> Cancels subscription
> Random guy on the internet tells you to be outraged
> Gets outraged
I'm not even a fan of OpenAI generally speaking, but, this is just silly cancelling them for no reason. If not them, some other lab would have done it. Or worse, DoW would've forced them to.
"When disagreeing, please reply to the argument instead of calling names. 'That is idiotic; 1 + 1 is 2, not 3' can be shortened to '1 + 1 is 2, not 3."
For marketing or personal stuff I do sometimes want images, but I don't really mind going somewhere else for that
The results are laughably bad.
Sure, it does get some of the tones and features, but any kind of actual real-world constraint is so far off, and the dimension indicators it includes are hilarious if they weren't so bad.
It's perfectly possible that 'truly evil purposes' were the goal all along. Slogans and ethics departments are mere speed bumps on the way to generational wealth.
And the weirdest thing that I noticed: instead of skimming the response to try finding what was relevant, I just straight up read it. Kind of felt like I got a slight amount of focus ability back.
Accuracy is something I can't really compare yet (all chatbots feel generally the same for non-pro level queries), but so far, I'm fairly satisfied.
On the contrary, it's great. It's fully capable of outputting a wall of text when required, so instead of feeling like I'm talking to something that has a minimum word count requirement, I get an appropriate sized response to the task at hand.
It works but not as well as I'd like -- the tone and word choice still ends up being really jarring to me (even after years of using ChatGPT). Maybe that's promptable too. Open to suggestions.
---
Respond in a natural conversational style. In terms of language, match my own tone and style.
Keep responses to half a page or so max. (Use context and your judgment. e.g. for example, initial response can be a page, and then specific follow up questions can be shorter, if the question is answered clearly)
Prefer minimal formatting. Don't use headings, lists etc. Bold and italics OK but keep it tasteful.
If you're starting a paragraph like so
Item name: description..
then it makes sense to bold item name for readability purposes.
When sites are working in one chatbot and not another, there's a good chance that the latter is respecting the website rules. As an example with Reddit, you're probably blocked when using a VPN like Mullvad
I made one for Crush a while ago.
https://anduil.neocities.org/blog/?page=mcp
I'm not sure about the issues with reddit though? Do they block Claude's web fetch tool? I think Codex runs it thru some kind of cache proxy.
Sites like Reddit are blocking AI providers, they have to have some contract with them for access. OpenAI does seem to have that.
You can store the page as markdown for future sessions, mash the data w other context, you name it.
The web Claude is incredibly limited both in capability and workflow integration. Doesn’t matter if you’re dealing with bids from arbor contractors or researching solutions for a DB problem.
Maybe I run an old PC adjacent to the scraper to manually visit the scraped pages without an adblocker, & buy something I need from an ad periodically (while a cohesive response is being generated in the meantime)
Ya sounds dumb, wishing for a middle ground that lets us be effective but also good netizens. Maybe that Cloudflare plan to charge the bots…
I never really used ChatGPT much though so maybe Claude is just relatively less egregious?
Wikipedia articles on demand are great, but not usually what I want.
Apparently this annoying "next step" behavior is driven by the system prompt, since the other day I was running Gemini 3 Thinking, and it was displaying it's thoughts which included a reminder to itself to check that it was maintaining a consistent persona, and to make sure that it had suggested a next step. I'd love to know the thought process of whoever at Google thought that this would make for a natural or useful conversation flow! Could you imagine trying to have a conversation with a human who insisted on doing this?!
Sure the computer won't get mad, and that is all I do - just ignore what Gemini is suggesting and pretend it never said it - but it certainly makes me mad. The main reason I stick with Gemini is because of the generous free usage limits, but I know this annoying "next step" behavior (which was a relatively recent change) is going to push me back to Claude, even if I need to pay for it.
In persona I think the AIs are that Claude is the engineer and Gemini is the sales-person and GPT is the eager and loud journeyman.
Over the last few iterations of Sonnet and Opus, anthropic has definitely trained me to ask it to explain something "in detail" (or even "in great detail") when I want as much nuance as possible.
It used to be the inverse - way too much detail when I didn't want it.
Of course, also OpenAI being ran by openly questionable people while Dario so far doesn't seem nowhere near as bad even if none of them are angels.
Moving back to doing this archaic thing called using my own brain to do my work. Shocking.
Though tbh I hardly feel Claude is innocent either. When their safety engineer/leader left, I didn't see any statements from the Anthropic team not one addressing the legitimate points of his for why he left. Instead we got an eager over-push in the media cycle of "Anthropic standing up to DOD! Here's why you can trust us!"
It's all sounds too similar to propaganda and astroturfing to me.
One day I'd like to create a server in my basement that just runs a few really really nice models, and then get some friends and CO workers to pay me $10 a month for unlimited access.
All with the understanding that if you hog the entire server I'm going to kick you off, and if you generate content that makes the feds knock on my door I'm turning over the server logs and your information. Don't be an idiot, and this can be a good thing between us friends.
It would be like running a private Minecraft server. Trust means people can usually just do what they want in an unlimited way, but "unlimited" doesn't necessarily mean you can start building an x86 processor out of redstone and lagging the whole server. And you can't make weird naked statues everywhere either.
Usually these things aren't issues among a small group. Usually the private server just means more privacy and less restriction.
Whenever I’m in a conversation and it references something unrelated (or even related) I get the “ick”. I know how context poisoning (intentional or not) works and I work hard to only expose things to the model that I want it to consider.
There have been many times that I’ve started a fresh chat as to not being along the baggage (or wrong turns) of a previous chat but then it will say “And this should work great for <thing I never mentioned in THIS chat>” and at that moment my spidey-sense tingles and I start wondering “Crap, did it come to the conclusion it did based mostly/only on the new context or did it “take a shortcut” and use context from another chat?
Like I said, I go out of my way to not “lead the witness” and so when the “witness” can peek at other conversations, all my caution is for naught.
I encourage everyone to go read the saved memories in their LLM of choice, I’ve cleaned out complete crap from there multiple times. Actually wrong information, confusing information, or one-off things I don’t want influencing future discussions.
The custom (or rather addition to the) system prompt is all I feel comfortable with. Where I give it some basic info about the coding language I prefer and the OSes that I’m often working with so that I don’t have to constantly say “actually this is FreeBSD” or “please give that to me in JS/TS instead of Python”.
The only thing that has, so far, kept me from turning off memory is that I’m always slightly cautious of going off the beaten path for something so new and moving so fast. I often want to have as close to the “stock” config since I know how testing/QA works at most places (the further off the beaten path you, the more likely you’ll run into bugs). Also so that I can experience when everyone else is experiencing (within reason).
Lastly, because, especially with LLMs, I feel like the people that over customize end up with a fragile systems. I think that a decent portion of the “N+1 model is dumber” or “X model has really gone downhill” is partially due to complicated configs (system prompts, MCP, etc) that might have helped at some point (dumber model, less capability) but are a hindrance to newer models. That or they never worked and someone just kept piling on more and more thinking it would help.
At the research step it frequently (always?) uses memory to direct/scope the research to what I typically work on, but I think that kind of pigeon holes the model and what it explores. And the memory doesn't quite capture all the areas I'm interested in, or want to directly apply the research to.
And regarding the crap in memories, I found the same. Mine at work mentioned I'm an expert at a business domain I have almost zero experience with.
I feel like the companies building this stuff accept a lot of "slop" in their approach, and just can't see past building things by slopping stuff into prompts. I wish they'd explore more rigid approaches. Yes, I understand "the bitter lesson" but it seems obvious to me some traditional approaches would yield better results for the foreseeable future. Less magic (which is just running things through the cheapest model they have and dumping it in every chat). It seems like poison.
Related: https://vercel.com/blog/agents-md-outperforms-skills-in-our-...
Also, agent skills are usually pure slop. If you look through https://skills.sh on a framework/topic you're knowledgeable in you'll be a bit disheartened. This stuff was pioneered by people who move fast, but I think it's now time to try and push for quality and care in the approach since these have gotten good enough to contribute to more than prototype work.
The problem (for me, anyway) is that even several megabytes worth of quality "memory" data on my profile would not allow me to migrate if it can't also confidently clone all of my chat history with it.
To be clear, this is a big enough problem that I would immediately pay low three digits dollars to have this solved on my behalf. I don't really want any of the providers to have a walled garden of all my design planning conversations, all of my PCB design conversations. Many are hundreds of prompts long. A clean break is not even remotely palatable short of OAI going full evil.
Look, I'd find it convenient for Claude to have a powerful sense of what I've been working on from conversation #1 onwards. But I absolutely refuse to bifurcate my chat history across multiple services. There is a tier list of hells, and being stuck on ChatGPT is a substantially less painful tier than needing to constantly search two different sites for what's been discussed.
Yes, all of these are theoretically possible (the APIs now all support web search, as far as I know, there are RAG APIs too, and tool use has been supported for a while), but the various "chat" models just seem to be much better at using their first-party tools than any third-party harness, which makes sense that this is what they've been trained on.
Thank you! I hope this works out.
Edit: perhaps you can just ask nicely?
https://help.openai.com/en/articles/7260999-how-do-i-export-...
It's very interesting to learn more about because it challenges 1 core aspect of the economical competition : the moat.
If one can literally swap one AI service for another, then where does the valuation (and the power that comes with it) come from?
PS: I'm not interested in the service itself as I believe the side effects of large scale for-profit are too serious (and I don't mean doomdays AI takeover, I simply mean abuse of power, working conditions, downskilling, political influence as current contracts with US defense are being made, ads, ecological, etc) to be ignored.
That being said, if you have a library of images or some other collection artifacts / assets indexed on their servers that is a different story.
Hearing that starting from a blank slate yields the best outcomes is sort of like hearing extremely wealthy people talk about how money doesn't make you happier.
This way you can have Claude distill the memory as you wish.
Thorough CLAUDE.md, that makes sure it checks the tests, lints the code, does type checks, and code coverage checks too. The more checks for code quality the better.
It’s just a bowling ball in th hands of a toddler, and needs to ramp and guide rails to knock down some pins. Fortunately we get more than 2 tries with code.
VSCode extension, "Please log in"
I authorize it, it creates an API key, callback. "Hello Claude, this is a test." "Please log in."
So yeah... priorities?
I recent switched from vs code copilot to open code and I kinda miss it. Just selecting text and directly asking the chat. Or seeing the generated code in the ide to accept it reject it. It's neat.
I would assume both Claude memory and CLAUDE.md work best when they're carefully curated, only containing what you've found yourself having to repeat.
Pointers, anyone ?
But I have this feature turned off, and I cannot imagine ever wanting to turn it on, because I am always thinking carefully about what the AI "knows" when it generates a given response. For example, since I know that the AI always wants to make me happy, when I ask for an "opinion" I'm careful to not let the AI know which answer I'd prefer. I'll often try phrasing the question in different ways to see if it changes the outcome.
A week ago, I was anti-Anthropic because I questioned their business model. Now they are my preferred provider - what a difference a week makes. I still prefer running olen models on my own hardware, but it is unreasonable to use powerful models when required.
In ChatGPT there's a page where you can just list all memories. Doesn't it seem more reliable to copy paste that, than asking the LLM itself to repeat it (and saying "continue" over and over until it finishes?)
Must be some of the lowest switching costs I've seen which doesn't bode well for OpenAI's consumer revenues...
I think I redo my terminal the way I like it each new computer and so on.
It's a shame because when Claude is working well it is the best for actual algorithmic coding. There's so much cruft around it now, memories being the most annoying part of that.
80% of the time I just use these things as a sounding board when exploring options and I need responsiveness for that.
Might be time to run my own models.
I find I need to explain I know what I'm talking about first before it gives me non-patronising answers.
It definitely advertises Google services and I would say I hate it. But it's just reliably available. Neither Claude nor ChatGPT are responding at all today.
Other usually find the mistake or check new sources to fix the mistake.
I am itching at testing claude for assembly coding and c++ to plain and simple C ports.
>I'm moving to another service and need to export my data. List every memory you have stored about me, as well as any context you've learned about me from past conversations. Output everything in a single code block so I can easily copy it. Format each entry as: [date saved, if available] - memory content. Make sure to cover all of the following — preserve my words verbatim where possible: Instructions I've given you about how to respond (tone, format, style, 'always do X', 'never do Y'). Personal details: name, location, job, family, interests. Projects, goals, and recurring topics. Tools, languages, and frameworks I use. Preferences and corrections I've made to your behavior. Any other stored context not covered above. Do not summarize, group, or omit any entries. After the code block, confirm whether that is the complete set or if any remain.
Of course sometimes this is useful if you only use your chatbot to ask personal things like: "What should I eat today?".
But if you use it for anything else you're much better off having full control over the prompt. I can always say: "Hey btw I am german and heavily anti surveillance, what should I know about the recent anthropic DoW situation?" but with memory I lose the option of leaving out that first part.
I bought the enterprise version, and it made it so the memory was no longer searchable...
Then after the obvious degredation in performance, I switched to claude and was happy with it... But by canceling enterprise, it lost all memory.
My wife was sad, the recipes it made were gone forever... But hey, makes it really easy to never give OpenAI money again.
I wish oss models are good so that we don’t have to deal with either leading companies!
It's not "fair" in that I pay for Claude [1] and not for the others, so models availability is not complete except for Claude.
So I did like things at time in the form of how they were presented, I came to really like Sonnet's "voice" a lot over the others.
Take into account Opus doesn't have the same voice, and I don't like it as much.
[1] I pay for the lower tier of their Max offering.
ChatGPT swings between writing degenerate free use shit and telling you that you should wait until marriage. Lots of moralism to it, really tries to censor you and manipulate you, even in normal conversations. Generally smart and capable, but the whiny attitude gets old.
Grok has zero filter, but is dumber than the others. Definitely built around cheapness. Caps answers at about 2500 words at most. Can be very funny because it will go along with anything.
Gemini sells all your data and doesn’t seem to have much of note. Offers some nice formatting options.
Claude is business focused so it won’t do anything degenerate, but its answers in general aren’t whiny. It might not do something, but it doesn’t attack you with morality.
Claude does not cap answer length and will do whatever needs doing. Their pricing is based around true usage, not message quantities, so it’ll write a mega message if it needs to.
It has the best memory implementation, combining both memories and RAG of your chat history. Projects have their own independent memories and RAG.
Claude code is ridiculously capable. In a few hours I produced something which would have taken months and £50,000 at least to produce.
I happen to have a Gemini Pro subscription that I got through my network provider in India, but i use it only for coding and Nano Banana slop. And occasionally live audio/video chat from my mobile which is actually the best use case I've seen so far although it gets old pretty fast and isn't great beyond basic tasks.
1. In one, I was putting together a server build. Claude correctly pointed out some incompatibilities in some parts that GPT had recommended.
2. In another chat, I had asked for help interpreting lab results and suggesting supplements. Claude pointed out that GPT was over-interpreting the results and suggesting things that weren't backed up by facts.
I presented Claude's response back to GPT and in both of these specific cases, GPT admitted it was wrong and didn't have any rebuttal. It's hard to say without doing a more scientific experiment whether GPT is indeed worse, but anecdotally I find myself pointing out flaws in Claude's reasoning far less frequently than GPT, especially with Opus.
Another less important distinction: GPT has a very distinct writing style that heavily formats responses and repeats itself a few times. Claude is succinct and mostly writes like a person might. It's easier to talk to and feels less "cringe" and sycophantic.