We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale.
New AI models pop up every week. Some developer tools like @Cursor, @Zed, and @Kilo Code let you choose between different models, while more opinionated products like @Amp and @Tonkotsu default to 1 model.
Curious what the community recommends for coding tasks? Any preferences?
Claude by Anthropic draws strong praise for reasoning, coding, and long-context work, with many switching from rivals for more precise, human-like responses. Maker feedback is especially enthusiastic: the makers of
highlight reliable tool use via MCP across thousands of actions. Common wishes: fewer message limits, smoother artifacts/UX on desktop, and steadier revision behavior. Overall: reliable, thoughtful, and superb for code.
The one AI tool I use daily. Great for code, solid for writing, and it remembers what we're working on.
How well does Claude generate and debug complex codebases?
Claude is very good at understanding and reasoning about code. It’s most useful for debugging, refactoring, and reviewing complex logic, especially when you treat it as a coding partner.
How quickly does it respond under heavy workloads?
Fast enough that it doesn't break my flow, even with more complex prompts. Under heavier workloads it may slow down slightly, but it remains responsive and consistent enough.
How well does it maintain context across long multi-step sessions?
Holds context well within a session. I can reference earlier decisions, and it keeps up. I don't have to repeat myself, even in longer working sessions.
AI assistant (81)contextual understanding (33)reasoning capabilities (33)
Claude is super smart, easy to work with, and great at staying on track even with complicated questions. It writes really well and feels thoughtful compared to some other chatbots. Sometimes it’s a bit overly careful, but that also means I can trust its responses more. Definitely one of the best AI assistants out there.
What needs improvement
contextual understanding (2)
It also doesn’t always know the latest information, and its answers can occasionally feel wordy or generalized.
I picked Claude because it feels thoughtful, clear, and helpful in its responses. It handles complex tasks well without being overwhelming, and its emphasis on safety and reliability makes it easy to trust for everyday use.
Are there limits on daily messages or rate caps?
As a user, I haven’t run into strict daily message limits, but there are rate caps if I send a lot of messages very quickly. For normal use, it feels unlimited, but heavy or automated usage can hit throttles. Overall, limits aren’t a problem for regular conversations.
Does Claude work offline or require constant internet?
Claude requires an internet connection, so it doesn’t work offline. As long as my connection is stable, it’s reliable, but there’s no offline mode for times without internet.
What differences between Opus, Sonnet, and Haiku matter most?
The biggest differences that matter to me are reasoning quality, speed, and cost. Opus is the best when I need deep thinking or detailed writing, but it’s slower and more expensive. Sonnet is the best all-around choice for everyday tasks. Haiku is super fast and cheap, which is great for quick questions or simple summaries. I pick based on how much “brainpower” the task really needs.
While Claude Opus may be great for writing code, it's still not a perfect vibe coding solution. You may need to use a combination of LLMs to figure out what's best for the product you're trying to code. Although on its own, it still gets you 75% of the way.
vs Alternatives
Being the new kid on the block, I had to give it a go to see why everyone has been raving about it. Seems like the raving reviews were correct. It feels as though Claude's responses are more thorough in comparison to other solutions.
How quickly does it respond under heavy workloads?
It's pretty solid under heavy workloads.
Can it analyze large PDFs and CSVs without failing?
For the most part it analyzes large files pretty well.
How easy is setup on iOS, Android, web, and desktop?
It's as seamless as it gets, but this is the case for most LLMs nowadays.