I don't think vibe coders know the difference, but often when I ask AI to add a feature to a large code base, I already know how I'd do it myself, and the answer that Claude comes up with is more often the one I would have done. Codex and Gemini have burned me too many times, and I keep going back to Claude. I trust it's judgement. Anthropic models have always been a step above OpenAI and Google, even 2 years ago it was like that so it must be something fundamental.
For me, Codex does well at pure-coding based tasks, but the moment it involves product judgement, design, or writing – which a lot of my tasks do – I need to pull in Claude. It is like Claude is trade on product management and design, not just coding.
I've been using ChatGPT (Thinking). I like how it has learned how I do stuff, and keeps that in mind. Yesterday, I asked it to design an API, and it referenced a file I had sent in, for a different server, days earlier, in order to figure out what to do.
I'm not using it in the same way that many folks do. Maybe if I get to that point, I'll prefer Claude, but for my workflow, ChatGPT has been ideal.
I guess the best part, is that it seems to be the absolute best, at interpreting my requirements; including accounting for my human error.
I like this feature and rely on it too. I get that some people hate it and that it can make some pretty insidious mistakes when it uses it, but I’ve found it valuable for providing implicit context when I have multiple queries for the same project.
Worth noting that Claude also has a memory feature and uses it intelligently like this, sometimes more thoughtfully than cgpt does (fewer “out of left field” associations, smoother integration).
Oof. I turned the history referencing off. I use ChatGPT for wildly diverging topics and it will bring things up that have zero relevance to what I'm currently looking for if history is on.
Yup. I can see that being a problem. My use is pretty linear, so that isn't an issue. I think that you might be able to establish different "contexts," though I haven't tried.
I will see whether or not I can “wipe the slate clean,” between projects.
I would also NEVER use it for any confidential/proprietary stuff that can’t leak.
The project I’m working on is not open-source, but we don’t really care too much, if it leaks. I don’t send in any credentials; just source.
Right now, it’s helping me design tests in Postman, to validate the API.
There is also the very lame auto win category that i happen to fall into...
I dont trust openai, or google. google has beyond proven that they aren't trustworthy well before the LLM coding tool era. I am legitimately not even giving them a chance.
Sadly I am assuming anthropic will at some point lose my trust, but for now they just feel like the obvious choice for me.
So obviously i am a terrible overall observer, but i am sure i am not alone in the auto win portion of devs choosing anthropic.
That was exactly why I had been a paying Anthropic customer as well – I trusted them more than I trusted OpenAI or Google. But I canceled my subscription this morning after the news that they've ditched their core safety promise [†], and they look likely to fold to the Pentagon's demands on autonomous weapons/surveillance as well.
Model aside, the harness of Claude Code is just a much better experience. Agent teams, liberal use of tasks and small other ergonomics make it a better dev tool for me.
I've heard a lot of people prefer OpenCode to Claude Code, myself included. Having tried both, I find myself having a much better time in OpenCode. Have you tried it?
I'll admit it lacks on the agent teams side but I tend to use AI sparingly compared to others on my team.
I’ve been using Claude Code for about six months and evaluated OpenCode on my Windows work laptop a few weeks ago. Found 3 dealbreakers that sent me back:
1. No clipboard image paste. In Claude Code I constantly paste screenshots – a broken layout, an error dialog, a hand-drawn schema – and just say “fix this.” OpenCode on Windows Terminal can’t do that without hacky workarounds (save to file, drag-and-drop, helper scripts). I honestly don’t understand how people iterate on UI without this.
2. Ctrl+C kills the process instead of copying. And you can’t resume with --continue either, so an accidental Ctrl+C means losing your session context. Yes, I know about Ctrl+Ins/Shift+Ins, but muscle memory is muscle memory. I also frequently need to select a specific line from the output and say “this part is wrong, do it differently” – that workflow becomes painful.
3. No step-by-step approval for individual edits. Claude Code’s manual edit mode lets me review and approve each change before it’s applied. When I need tight control over implementation details, I can catch issues early and redirect on the spot. OpenCode doesn’t have an equivalent.
All three might sound minor in isolation, but together they define my daily workflow. OpenCode is impressive for how fast it’s moving, but for my Windows-based workflow it’s just not there yet.
> Half their agentic usage is coding. When that's your reality, you train for it. You optimize the tool use, the file editing, the multi-step workflows - because that's what your paying users are actually doing. Google doesn't have that same pressure.
I wonder if this is a strategic choice — anthropic has decided to go after the developers, a motivated but limited market. Whereas the general populace might be more attracted to improved search tools, allowing Google/openai/etc to capture that larger market
They are heavily dogfooding. Coding is needed to orchestrate the training of the next Claude model, data processing, RL environments, evals, scaffolding, UI, APIs, automated experiments, cluster management, etc etc. This allows them to get the next model faster and then get the next one etc.
Making a model that's great at other kinds of knowledge/office work is coincidental, it doesn't feed back directly into improving the model.
It's more likely that anthropic feels that if they can crack just programming, then their agents can rapidly do the legwork of surpassing the other labs.
Hmm that makes some sense to me as well, like buying eco upgrades early in an rts game. But that assumes that better programming leads to more-generally-competent AI, which I think is tenuous. The thing that sparked this recent AI summer was not better programming, so why would better programming lead to the next/ongoing big improvements?
- limiting model access when not using claude code
- claude code is a poorly made product. inefficient, buggy, etc. it shows they don’t read the code
- thousands of open GitHub issues, regressions introduced constantly
- dev hostile changes like the recent change to hide what the agent is actually doing
However, they are very good at marketing and hype. I’d recommend everyone give pi or opencode a try. My guess is anthropic actually wants vibe coders (a much broader market).
I doubt it. Gemini is heavily used internally for coding with integrations across Google's developer tooling. gemini-cli is not meaningfully different from claude code.
Gemini is supposed to have this huge context; Gemini cli (paid) often forgets by the next prompt whatever the previous was about and starts doing something completely different , often switching natural or programming language. I use codex and with 5.3 it is better but not there compared to cc for us anyway; it just goes looking for stuff, draws the most bizarre conclusions and ends up lost quite often doing the wrong things. Mistral works quite well on smaller issues. Cerebras gml rocks on quick analysis; if it had more token allowance and less rate limiting , it would probably be what I would use all the time; unfortunately, on a large project, I hit a 24 hour block in less than an hour of coding. It does do a LOT in that time of course because of its bizarre speed.
1) I don't want to give OpenAI my money. I don't like how they are spending so much money to shape politics to benefit them. That seems to fly in the face of this being a public benefit. If you have to spend money like that because you're afraid of what the public will do, what does that say?
2) I like how Claude just gives me straight text on one side, examples on the other, and nothing else. ChatGPT and Gemini tend to go overboard with tables, lists, emojis, etc. I can't stand it.
3) A lot of technical online conversation seems to have been hollowed out in recent years. The amount of people making blog posts explaining how to use something new has basically tanked.
Could it be tooling like Claude Code? I just used Claude Code with qwen3.5:35b running locally to track down two obscure bugs in new Common Lisp code I wrote yesterday.
They are great, but they are expensive. I can run those against the cheaper ollama cloud models for things that are basically requirements gathering and review of a plan. The Product Designer Agent and the Product Manager basically argue for a few rounds and give an artifact that the coding agents pick up.
It could all easily be anthropic models and would work well, but running this swarm eats up all my anthropic tokens and these other models are good enough for the roles I've given them.
I also have always gone back to Claude after trying new models... until GPT-5.3-Codex, specifically with the new Codex Mac app. I've been pretty much full time with it for a few weeks now and have not missed Claude Code. It can over complicate things at times, but for the most part, it is providing working solutions on first go and following coding patterns that already exist in my app. With Claude, it would frequently knock out a feature with acceptable code quality, but be completely broken and require a round of debugging.
I'm even getting by without hitting limits on the $20/month plan, whereas I needed to be on the $100/month one with Claude.
This resonates with my experience. At Morph we use gemini for well specified point coding tasks, and it does very well across millions of lines of code every day. We also use claude code as an engineering tool for our own codebase and it does better at being adaptive and for working on open ended issues.
I am too, and haven't really given Anthropic's stuff a fair shake as a result, and am so curious if I'm missing out or if it's the same shit different pile.
I prefer Googles. I can only afford the free models. I normally copy and paste my stuff into 4-5 models and compare the responses. Its probably a waste of time, but very mentally satisfying. I mostly program as a form of mental stimulation instead of trying to become a billionaire. Taking this perspective, using AI agents is not really the same experience, and less mentally stimulating than programming.
I don't understand quite how Anthropic have managed to get so much mind share for Claude Code given the UX is pretty bad compared to something like Cursor.
I started using Codex 5.3. Compare to Opus 4.6, it's more precise in pinning down bugs and more concise with code. Opus can be best described as distracted and easily agreeable. Codex actually digs deeper for root causes and push back when I'm wrong.
I am torn between Claude and GPT. Though it was recently brought to my attention that I use LLMs in an old-fashioned way [1]. I will say that based on my usages, both models seem very comparable in terms of accuracy and quality. Sometimes one might do things a bit different, but both tend to be more similar than different.
When I am using an LLM for JS, I can't really tell the difference between the two. For C#, I think GPT might produce slightly better quality code, but Claude produces code that seems more modern. I also feel like Claude makes slightly more minor mistakes like forgetting to negate a boolean conditional check.
With Swift, I have found both models to be surprisingly awful. I am not sure if it is because of some of the more recent changes with Swift versions greater than 6.0, but both seem to produce wild results for me.
[1] I do not use Codex CLI nor Claude Code nor any IDE plug-ins. I just type questions into the web app and rarely copy/paste anything back and forth.
Developers prefer Claude because that's their brand, a very intentional choice. If you have a very specific use in mind (like coding), you aren't going to go for the jack of all trades, master of none solution. You're going to go for the coding specialist, which Anthropic has squarely positioned themselves as. Props to them for it - they correctly predicted that LLMs can do many things, but perhaps the most valuable is coding as they're very well suited to it due to the rigidly defined syntax and high cost of engineers.
Use to love Grok Code Fast 1 because it was free on GHCP. I gave it context but just let it churn on a solution. Claude is far better but a finite resource. I think OpenCode plus GPT-4o might be my next step.
I think this is organic. I've observed the exact same thing over the last week: I tried Google Antigravity and really liked it when I was using my Claude quota. I ran out of Claude quota and tried Gemini 3.1 Pro and it was comparatively terrible at using the tools provided by the IDE. (but it's a useful model in the browser for chat)
I've been leaning more towards claude. A lot of the LLM tropes seem to be ChatGPT really? I feel like claude doesn't do as much of the overly intense "its this -- not that" pattern and isn't constantly acting like my hype man. Claude code has been nice 90% of the time. I haven't tried to many competitors though.
I keep using Claude over other models (through Cursor) because the answers it gives and the plans it creates align with how I would personally approach the same problem if I were doing it myself. The other models /might/ produce a better final result as benchmarked/tested, but how they get there feels like complete nonsense to me.
The complexity of a project vs. getting lost and confused metric, Claude does a lot better than every time I've tried something else, that's it.
I'm not using it in the same way that many folks do. Maybe if I get to that point, I'll prefer Claude, but for my workflow, ChatGPT has been ideal.
I guess the best part, is that it seems to be the absolute best, at interpreting my requirements; including accounting for my human error.
Worth noting that Claude also has a memory feature and uses it intelligently like this, sometimes more thoughtfully than cgpt does (fewer “out of left field” associations, smoother integration).
I will see whether or not I can “wipe the slate clean,” between projects.
I would also NEVER use it for any confidential/proprietary stuff that can’t leak.
The project I’m working on is not open-source, but we don’t really care too much, if it leaks. I don’t send in any credentials; just source.
Right now, it’s helping me design tests in Postman, to validate the API.
I dont trust openai, or google. google has beyond proven that they aren't trustworthy well before the LLM coding tool era. I am legitimately not even giving them a chance.
Sadly I am assuming anthropic will at some point lose my trust, but for now they just feel like the obvious choice for me.
So obviously i am a terrible overall observer, but i am sure i am not alone in the auto win portion of devs choosing anthropic.
[†] https://www.cnn.com/2026/02/25/tech/anthropic-safety-policy-...
I'll admit it lacks on the agent teams side but I tend to use AI sparingly compared to others on my team.
1. No clipboard image paste. In Claude Code I constantly paste screenshots – a broken layout, an error dialog, a hand-drawn schema – and just say “fix this.” OpenCode on Windows Terminal can’t do that without hacky workarounds (save to file, drag-and-drop, helper scripts). I honestly don’t understand how people iterate on UI without this. 2. Ctrl+C kills the process instead of copying. And you can’t resume with --continue either, so an accidental Ctrl+C means losing your session context. Yes, I know about Ctrl+Ins/Shift+Ins, but muscle memory is muscle memory. I also frequently need to select a specific line from the output and say “this part is wrong, do it differently” – that workflow becomes painful. 3. No step-by-step approval for individual edits. Claude Code’s manual edit mode lets me review and approve each change before it’s applied. When I need tight control over implementation details, I can catch issues early and redirect on the spot. OpenCode doesn’t have an equivalent.
All three might sound minor in isolation, but together they define my daily workflow. OpenCode is impressive for how fast it’s moving, but for my Windows-based workflow it’s just not there yet.
I wonder if this is a strategic choice — anthropic has decided to go after the developers, a motivated but limited market. Whereas the general populace might be more attracted to improved search tools, allowing Google/openai/etc to capture that larger market
Making a model that's great at other kinds of knowledge/office work is coincidental, it doesn't feed back directly into improving the model.
- limiting model access when not using claude code
- claude code is a poorly made product. inefficient, buggy, etc. it shows they don’t read the code
- thousands of open GitHub issues, regressions introduced constantly
- dev hostile changes like the recent change to hide what the agent is actually doing
However, they are very good at marketing and hype. I’d recommend everyone give pi or opencode a try. My guess is anthropic actually wants vibe coders (a much broader market).
I doubt it. Gemini is heavily used internally for coding with integrations across Google's developer tooling. gemini-cli is not meaningfully different from claude code.
1) I don't want to give OpenAI my money. I don't like how they are spending so much money to shape politics to benefit them. That seems to fly in the face of this being a public benefit. If you have to spend money like that because you're afraid of what the public will do, what does that say?
2) I like how Claude just gives me straight text on one side, examples on the other, and nothing else. ChatGPT and Gemini tend to go overboard with tables, lists, emojis, etc. I can't stand it.
3) A lot of technical online conversation seems to have been hollowed out in recent years. The amount of people making blog posts explaining how to use something new has basically tanked.
It could all easily be anthropic models and would work well, but running this swarm eats up all my anthropic tokens and these other models are good enough for the roles I've given them.
I'm even getting by without hitting limits on the $20/month plan, whereas I needed to be on the $100/month one with Claude.
Every other AI add random opinionated and unwanted stuff
https://archive.org/details/1950-Tide-Detergent-Ad
Googles AI products suck hard though
$2B, best pork ever, it's not even theirs to begin with, so in a lot of senses, it's not a Google product
When I am using an LLM for JS, I can't really tell the difference between the two. For C#, I think GPT might produce slightly better quality code, but Claude produces code that seems more modern. I also feel like Claude makes slightly more minor mistakes like forgetting to negate a boolean conditional check.
With Swift, I have found both models to be surprisingly awful. I am not sure if it is because of some of the more recent changes with Swift versions greater than 6.0, but both seem to produce wild results for me.
[1] I do not use Codex CLI nor Claude Code nor any IDE plug-ins. I just type questions into the web app and rarely copy/paste anything back and forth.
Even for vacation questions or psychotherapy, claude is the best, despite complaining about not receiving a coding task (sometimes).
I've been leaning more towards claude. A lot of the LLM tropes seem to be ChatGPT really? I feel like claude doesn't do as much of the overly intense "its this -- not that" pattern and isn't constantly acting like my hype man. Claude code has been nice 90% of the time. I haven't tried to many competitors though.