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.
I'm fine with charts, but ChatGPT is so long-winded and redundant. "When would I use such-and-such pattern?" "That's exactly the right question to ask! ... What you're really asking ... Why that's interesting ... Why some people find it critical ... Option 1 ... Option 2 ... Consideration ... Table comparing to so-and-so ... The deep reason ... What it all boils down to ... The one-line answer (tight!) ... The next thing you need to know ... I can also draw a useless picture for you. Would you like me to do that?"
I will say with Claude that I often have to make sure to give it the context of a question for it to give me answers I'm looking for. I find in general it does better when you include the why's behind a decision or question.
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'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 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.
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've been using the browser/desktop for planning sessions on pieces of a larger project I'm putting together and it's been connecting the dots in unexpected ways from the other conversations.
I think the one disappointment is that I can't seem to resume a conversation from the web/desktop interface to the code interface... I have to have it generate a zip I can extract then work from.
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).
product-designer ollama-cloud / qwen3.5:cloud
pm ollama-cloud / glm-5:cloud
test-writer claude-code / Sonnet 4.6
backend-builder claude-code / Opus 4.6
frontend-builder claude-code / Opus 4.6
code-reviewer codex-cli / gpt-5.1-codex-mini
git-committer ollama-cloud / minimax-m2.5:cloud
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.
Codex is awesome too. Opencode is awesome as well. It's so easy to transition from one tool to another especially when one command in project root is what it needs to get up to speed.
But I actually feel like asking Opus to review Codex and vice versa gives me best results. Opus does push back on some reviews comments, sometimes Codex is overselling a feature, but at least to me it feels like I have more points of control, and different perspective even if I could simulate it with two terminal sessions lol
Googles AI products suck hard though
Isn't it a bit like asking horses what car features they like best?
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).
On the other hand, isn't it clear that people will be more productive with whatever agent they have experience with? That's my reason for going with open source agents and the attempts of Big LLM to kill that workflow only reaffirm my decision.
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.
Every other AI add random opinionated and unwanted stuff
I keep using the analogy of working with a disconnected overseas dev team over email... since I've had to do this before. The difference is turn around in minutes instead of the next day.
On a current project, I just have it keep expanding on the TODO.md as working through the details... I'd say it's going well so far... Deno driver for MS-SQL using a Rust+FFI library. Still have some sanity checks around pooling, and need to test a couple windows only features (SSPI/Windows Auth and FILESTREAM) in a Windows environment, and I'll be ready to publish... About 3-4 hours of initial planning, 3 hours of initial iteration, then another 1:1:1:1 hours of planning/iteration working through features, etc.
Aside, I have noticed a few times a day, particularly west coast afternoon and early evening, the entire system seems to go 1/3 the speed... I'm guessing it's the biggest load on Anthropic's network as a whole.
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.