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.
This is the 23rd launch from Claude by Anthropic. View more
Claude Opus 4.6
Launched this week
Claude’s most advanced model for agentic tasks
Claude Opus 4.6 is Claude’s most capable model yet, built for deep reasoning, long-running agentic tasks, and large codebases. With a 1M token context window, adaptive thinking, and improved planning, it delivers state-of-the-art performance across coding, analysis, research, and real-world work.
1M context + actually plans before acting is the hook for me. My monorepo’s a tangle and agents drift by hour 2. If this keeps focus and finishes, not just chatters, that’s huge. I’ll throw it a week‑long cleanup and see if it stays on the rails.
Agent Teams sound incredible! How do you manage token costs when the lead agent synthesizes results from multiple sub-agents? Seems like coordination overhead could add up fast.
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 just launched Claude Opus 4.6 . This is Claude s newest and most capable model so far. It s designed for deep reasoning, long-running agent workflows, and large codebases, with a 1M token context window in beta and stronger planning and code understanding.
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.
Claude by Anthropic has taken a major leap for quant data applications with its new built-in analysis tool, allowing users to write and execute JavaScript code directly within the Claude.ai interface. This enables real-time, precise, and reproducible data analysis—think of it as having a code sandbox for advanced number crunching, data cleaning, and iterative exploration, all powered by Claude’s state-of-the-art language and coding capabilities. Users can now upload CSVs, process raw datasets, run complex mathematical computations, and generate visualizations, making Claude a powerful companion for tasks ranging from financial modeling and sales analytics to engineering dashboards and product insights. The tool is accessible to all users in feature preview, democratizing advanced data workflows and moving Claude beyond abstract reasoning into the realm of concrete, actionable quant analysis.
What's great
AI assistant (81)code generation (54)data analysis (18)
Claude is seriously impressive – it feels like chatting with a thoughtful, well-read friend who’s also a genius coder.
It handles long documents like a champ (think 200K+ tokens), gives nuanced answers, and doesn’t just summarize – it actually understands. I’ve used it for writing, editing, research, and even debugging code, and it rarely misses. What I really love is how calm and conversational it feels – less robotic, more human. Sometimes it can get a bit wordy, but I’d rather have that than dry, one-liner replies. If you care about clarity, reasoning, and a solid mix of creativity and logic, Claude is easily one of the best out there.
What's great
AI assistant (81)code generation (54)long context windows (7)contextual understanding (33)creative writing (16)nuanced responses (17)
Here's a strategic review of Claude 3 (latest version):
Claude 3 stands out with its exceptional context handling and analytical capabilities. Having used it extensively, here's what matters:
Key Strengths:
Superior code understanding: Remarkably accurate for debugging and development assistance
Data analysis prowess: Excels at complex visualization tasks and data-rich queries
Contextual awareness: Maintains conversation flow and relevance throughout long exchanges
Nuanced responses: Provides thoughtful, well-reasoned answers that demonstrate understanding
Performance improvements:
Enhanced reasoning capabilities over previous versions
More accurate technical analysis
Faster response times
Better handling of complex, multi-step tasks
Areas for consideration:
Message limits on Pro tier could be more flexible
Typography interface elements could be refined
Currently using it for code review, data analysis, and technical documentation. The accuracy and depth of responses consistently exceed expectations.
Notably efficient for developers and analysts who need precise, contextual assistance.
Upvoted for pushing AI capabilities forward. 🚀
Hi Team, congrats! What are the best use cases for financial teams you can see now?
Product Hunt Wrapped 2025
1M context + actually plans before acting is the hook for me. My monorepo’s a tangle and agents drift by hour 2. If this keeps focus and finishes, not just chatters, that’s huge. I’ll throw it a week‑long cleanup and see if it stays on the rails.
Migma AI
Agent Teams sound incredible! How do you manage token costs when the lead agent synthesizes results from multiple sub-agents? Seems like coordination overhead could add up fast.
Excited to try this!
Migma AI
WOOOW! Great work! I love how Anthropic is changing the world!
Nice! We already integrated Opus 4.6 in https://brew.new/ and it's working extremely well. Keep it up!
Dokably
wow congrats!