Meanwhile, claude CLI has so many huge bugs that break the experience. Memory leaks, major cpu usage, tool call errors that require you to abandon a conversation, infinite loops, context leaks, flashing screens.. so many to list.
I love the feature set of Claude Code and my entire workflow has been fine tuned around it, but i had to to codex this month. Hopefully the Claude Code team spends some time to slow down and focus on bugs.
I doubt it. A large part of the performance problem with CC is constantly writing to a single shared JSON file across all instances, with no sharding or other mechanisms to keep it performant. It's spinning a shitload of CPU and blocking due to constant serialization/deserialization cycles and IO. When I was using CC a lot, my JSON file would hit >20mb quite quickly, and every instance would grind to a halt, sometimes taking >15s to respond to keyboard input. Seriously bullshit.
Everything Anthropic does from an engineering standpoint is bad, they're a decent research lab and that's it.
> Everything Anthropic does from an engineering standpoint is bad, they're a decent research lab and that's it.
This may be true, but then I wonder why it is still the case that no other agentic coding tool comes close to Claude Code.
Take Gemini Pro: excellent model let down by a horrible Gemini CLI. Why are the major AI companies not investing heavily in tooling? So far all the efforts I've seen from them are laughable. Every few weeks there is an announcement of a new tool, I go to try it, and soon drop it.
It seems to me that the current models are as good as they are goingto be for a long time, and a lot of the value to be had from LLMs going forward lies in the tooling
Gemini is a very powerful model, but it's tuned to be "oracular" rather than "agentic." The CLI isn't great but it's not the primary source of woe there. If you use Gemini with Aider in a more oracular fashion, it's still competitive with Claude using CC.
Claude is a very good model for "vibe coding" and content creation. It's got a highly collapsed distribution that causes it to produce good output with poor prompts. The problem is that collapsed distribution means it also tends to disobey more detailed prompts, and it also has a hard time with stuff that's slightly off manifold. Think of it like the car that test drives great but has no end of problems under atypical circumstances. It's also a naturally very agentic, autonomous model, so it does well in low information scenarios where it has to discover task details.
It is still slower than I'd like, at least with regards to UI input responsiveness, but I've never had it hard lock on me like CC. I can run 5-10 codex sessions and my system holds up fine (128GB RAM) but 8 CC instances would grind things to a halt after a few days of heavy usage.
I love the feature set of Claude Code and my entire workflow has been fine tuned around it, but i had to to codex this month. Hopefully the Claude Code team spends some time to slow down and focus on bugs.