the benchmarks aren't close. they're embarrassing. > humanity's last exam: kimi 44.9%, beats closed models
> browsecomp (agentic web search): kimi 60.2% vs gpt-5's 54.9%
> gpqa diamond: 85.7% vs gpt-5's 84.5%
> swe-bench verified: 71.3% (coding tasks)
> artificial analysis
AGENTS
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Kimi outperforms GPT-5 on key benchmarks like Humanity’s Last Exam
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Automated Cold Outreach with AI Personalization
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Workflow #3: Cold Outreach at Scale (Instantly + Make. com)
— God of Prompt (@godofprompt) 10 novembre 2025
Here's the full sequence:
→ Google Sheet with 100 prospects
→ AI researches each one
→ Gamma creates personalized deck
→ Claude writes custom email
→ Instantly sends it automatically
100 personalized outreach… pic.twitter.com/e9rLWflhBzWorkflow #3: Cold Outreach at Scale (Instantly + Make. com) Here's the full sequence: → Google Sheet with 100 prospects
→ AI researches each one
→ Gamma creates personalized deck
→ Claude writes custom email
→ Instantly sends it automatically 100 personalized outreach -
AI builds sales pitch, researches prospect, emails deck in 90 seconds
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I just watched an AI build a complete sales pitch, research the prospect, and email them a personalized deck.
— God of Prompt (@godofprompt) 10 novembre 2025
All in 90 seconds and its 100% automated.
Sales teams are about to get absolutely decimated.
Here's how to do it + comment "AI" and I'll DM you my automation guide: pic.twitter.com/WnkiWx3H8vI just watched an AI build a complete sales pitch, research the prospect, and email them a personalized deck. All in 90 seconds and its 100% automated. Sales teams are about to get absolutely decimated. Here's how to do it + comment "AI" and I'll DM you my automation guide:
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Fired 45 workers for AI, now begs them back as calls surge
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Commonwealth Bank fired 45 workers. replaced them with AI. bragged about cutting 2,000 calls per week. two weeks later they’re begging those same people to come back because the AI can’t do shit. calls didn’t go down. they went UP. managers working overtime. team leads
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Production-Ready AI Travel Agent with LangChain and Streamlit
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AI Travel Agent Guide A production-ready Streamlit travel assistant built with LangChain agents, featuring weather info, search capabilities, and video integration. The guide covers API setup, deployment options, and performance optimization. Explore the guide
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MontrealAI releases AGI-Alpha-Node-v0 GitHub repository
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GitHub: https://
github.com/MontrealAI/AGI
-Alpha-Node-v0
… $AGIALPHA #AGIALPHA -
Building AI Agents That Deliver Real Results with Leaders
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Join Databricks Co-founder and CEO @alighodsi and @OpenAI Co-founder and CEO @sama for an exclusive conversation on building AI agents that deliver real results. Learn how to:
– Tailor AI agents to your business goals
– Build, train, deploy and continuously improve them faster -
LangChain Deep Dive: Build AI Applications with Hands-On Tutorial
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LangChain Deep Dive Eric Burel shows developers how to build AI applications using the LangChain ecosystem in this hands-on tutorial. Key features:
– Chain & agent construction
– LangGraph orchestration
– LangSmith monitoring Watch now: https://
youtu.be/0ImjWIo5fyM
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Reachy Mini Hires AI Builder Coach for Development
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Reachy Mini heard about @REKrobot and hired an AI builder coach. We're not ready! pic.twitter.com/Q8Uexbr4yS
— clem 🤗 (@ClementDelangue) 9 novembre 2025Reachy Mini heard about @rek and hired an AI builder coach. We're not ready!
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Dr. MAMR: Solving Lazy Agent Problem in Multi-Agent LLM
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10. Unlocking the Power of Multi-Agent LLM for Reasoning Introduces Dr. MAMR, which addresses the “lazy agent” problem in multi-agent LLM reasoning through Shapley-inspired causal influence measurement and verifiable restart mechanisms.