Abdul Rahman Azam

🚀 Starting my public journey into Agentic AI & Python automation. 🔹 My goal: Build AI agents that think, act & execute tasks autonomously 🔹 Sharing everything I learn – code, concepts, real-world use cases 🔹 If you're interested in the future of AI, follow along.

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@elonmuskTN 48

🚀 Wrapped up my Class 05 assignment on the shift from software → Agentic AI. Sir @0xAsharib | Sir @itxx_naeem Covered: • 3 Waves: Predictive → Generative → Agentic • Agents = goal-driven digital workers • Tools, memory, autonomy • UX → Agentic Experience • LLM → LAM

Class 5: AI Native & AI-Driven Development🚀 Explored AI agents—autonomous, intelligent systems transforming coding, decision-making, and product design. Installed Gemini CLI for smarter, context-aware automation, taking workflows beyond Copilot & Cursor. @0xAsharib @itxx_naeem

@Python_Dv D

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Just wrapped up my AI Prompt Engineering assignment! 🎥 Explained: 🤖 Mixture of Experts (MoE) 🧩 The 6-Part Prompting Framework Learning to communicate with AI is the real future 🚀 #AI #PromptEngineering #MoE #GIAIC Sir @0xAsharib | Sir @itxx_naeem

🚀 Quarter 4 - Class 4 | GIAIC @0xAsharib @itxx_naeem Explored: • Advanced Prompt Engineering • Best Practices & Testing Frameworks • Avoiding prompt pitfalls • Mixture of Experts (MoE) in modern LLMs Crafting precise, expert-level AI communication ⚙️🤖 #AI #LLM #MoE #OpenAI

🎥 My GIAIC Assignment (Class 3 - Q4) Explaining 🔹What is LLM 🔹Prompt & Context Engineering 🔹Temperature, Top-p & Top-k in AI. Grateful to Sir @0xAsharib & Sir @itxx_naeem for guiding us through this amazing concept of how AI thinks! #GIAIC #AI #LLM #PromptEngineering

🧠 Quarter 4 - Class 3 | GIAIC | Taught by Sir @0xAsharib and Sir @itxx_naeem Dived deep into: • Prompt & Context Engineering • How LLMs think & predict • Tuning Temperature, Top-P, Top-K • Advanced prompting: CoT, ReAct, ToT #GIAIC #AI #OpenAI #LLM #PromptEngineering

🚀 Q4–Class 2 Recap Learned from Sir @0xAsharib & Sir @itxx_naeem about: ⚡ CLI – faster context & direct cloud access 🧠 MCP – data link b/w LLM & resources 📘 Prompt vs Context Engineering 🌐 LangChain, RAG, AI vs AGI 🎯 Model Weights, Tokens & Hallucination #AgenticAI #LLMs

🚀 Quarter 4 class 1 began with a powerful session by Sir @ziakhan & Sir Qasim on Agent Driven Development: Markdown | WSL | AI CLI | MCP | TDD | Spec-Driven | Scalable+CI/CD. Sir @0xAsharib & Sir Naeem explained LLM training: Pre-training, Fine-tuning & RLHF. Late = Value>speed