I asked Claude to enhance my LinkedIn profile. He didn’t just improve it—he turned it into a recruiter magnet. Here are the 7 exact prompts I used: Save them.
PROMPT ENGINEERING
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Anthropic Ditches Agents for Powerful Agentic Skills
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Wow.
— Charly Wargnier (@DataChaz) 14 avril 2026
The team behind Anthropic's Agent tools just explained why they ditched agents to focus entirely on Skills, showing just how powerful agentic skills can be.
Also adding this rad article from @exploraX_ that shares 20 powerful skills you can plug into Claude or any model 🔥 https://t.co/Cl46YgixCF pic.twitter.com/cLUxL47krwWow. The team behind Anthropic's Agent tools just explained why they ditched agents to focus entirely on Skills, showing just how powerful agentic skills can be. Also adding this rad article from @exploraX_ that shares 20 powerful skills you can plug into Claude or any model
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Never Too Late for Cheeky Kimi K2.5 Fine-tuning
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It's never too late for a cheeky Kimi K2.5 fine-tune
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Ultimate Cheat Code for Claude Agents Discovered
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this guy casually dropped the ultimate cheat code for Claude agents like it's no big deal
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Grok Knows More About Me Than I Know Myself
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Grok knows more about me than I know about myself. Seriously it does. Rather than try to push around Grok I'm just going with the flow and trying to give it what it wants, which is great content that's original.
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AI Skills and Judgment: Tools Don’t Close the Gap
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Research, writing, and problem-solving with AI require taste and judgment to use well. Those skills aren't evenly distributed and the tools don't close that gap automatically.
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Antigravity Workflow with Claude Integration Works Well
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antigravity with claude in the loop is actually a nice workflow once you get past the alpha rough edges
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Training AI Correctly: The DATA Method Explained
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I've published an episode on @ivoox
: "#1110: You're training your AI wrong… and the DATA method fixes it #podcast -

GPT with LangGraph: Multi-Agent Systems and Advanced AI Applications
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GPT with LangGraph! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode The rapid advancement of large model technology is leading to an increasing application of agent technology across various fields and industries significantly transforming how people work and live. In complex and dynamic environments, multi-agent systems are able to tackle intricate tasks that would be challenging for a single agent, thanks to their collaborative and division-of-labor approaches. The following stack of research papers and hands on tutorials highlight the integrated use of GPT with LangGraph and CrewAI. LangGraph enhances information transmission efficiency through its graph-based structure, while CrewAI boosts team collaboration and system performance via intelligent task allocation and resource management. The key areas of this research include: The design of agent architectures based on LangGraph for precise control . The enhancement of agent capabilities through CrewAI to tackle a range of tasks. The goal of this study is to explore the combined potential of GPT and LangGraph and CrewAI in multi-agent systems, offering fresh insights for the ongoing evolution of agent technology and fostering innovation in the application of large model intelligent agents. References Duan, Z., & Wang, J. (2024, November 27). Exploration of LLM multi-agent application implementation based on LangGraph+CrewAI. arXiv. Retrieved March 9, 2025, from arxiv.org/abs/2411.18241 Horsey, J. (2025, March 9). Build a powerful Python chatbot in minutes with LangGraph. Geeky Gadgets. Retrieved March 9, 2025, from geeky-gadgets.com/build-a-po… Ong, R. (2024, July 10). GPT-4o and LangGraph tutorial: Build a TNT-LLM application. DataCamp. Retrieved March 9, 2025, from datacamp.com/tutorial/gpt-4o… Sivan, V. (2024). Building AI agent systems with LangGraph. Medium. Retrieved March 9, 2025, from medium.com/pythoneers/buildi… Wang, J., & Duan, Z. (2024, December 2). Intelligent Spark agents: A modular LangGraph framework for scalable, visualized, and enhanced big data machine learning workflows. arXiv. Retrieved March 9, 2025, from arxiv.org/abs/2412.01490
→ View original post on X — @gp_pulipaka, 2026-04-14 04:57 UTC
