Context Engineering in AI: Optimizing Model Performance

Proud to have participated in workshop on Python Programming for Agentic AI by the Capabl India. Explored how intelligent agents are designed, orchestrated, and scaled using Python. This is just the beginning excited to build smarter AI Agents ahead! 🔥 #AgenticAI #AI #PythonDeveloper #TechGrowth #FutureTech

Using Python with financial datasets should feel intuitive. In this session, we explore how GenAI tools and LSEG Workspace can accelerate analysis, streamline coding and support faster iteration. Enrol here: https://lseg.group/4vCr3oj Learners will walk through Python workflows, AI‑assisted strategy testing and practical troubleshooting techniques that reduce friction and boost productivity. #Python #GenAI #FinancialData #LSEGWorkspace #Learning

🚀 Day 10 of My Generative & Agentic AI Journey! Today’s focus was on understanding Conditionals in Python — the foundation of decision-making in programming. Here’s what I learned: 🔀 Conditionals in Python: • if statement → Executes code when a condition is True • else statement → Executes when the condition is False • elif statement → Used to check multiple conditions 🧠 Why Conditionals matter: • Help programs make decisions • Control the flow of execution • Used in real-world applications like validations, user input handling, and logic building 👉 Key takeaway: Conditionals are the backbone of logic in programming — from simple checks to complex AI decision-making systems. Building strong fundamentals step by step 💪 #Day10 #Python #GenerativeAI #AgenticAI #LearningJourney #BuildInPublic

Andrej Karpathy has released MicroGPT, a remarkable ~200-line pure Python implementation of a full GPT model from scratch. Released on February 12, 2026, the script includes everything needed—dataset handling, tokenizer, autograd engine, GPT-2 architecture, Adam optimizer, and complete training plus inference loops—without any external libraries. This minimal codebase continues Karpathy’s tradition of educational “micro” projects like micrograd and nanoGPT, aimed at stripping away frameworks to reveal how large language models truly work. The release is expected to help developers and students gain deeper intuition into transformer fundamentals through hands-on coding rather than relying on black-box tools. 200 lines. No dependencies. From nothing. For anyone who has ever wanted to understand what a large language model actually is — not what it does, but what it is — this file is the answer. https://lnkd.in/dS6Epsn4

Tired of your AI agents crashing? 📉 Discover how Anti-Gravity agents use transparent logic and Gemini-powered error correction to handle failures without breaking the loop. Learn the difference between toy agents and production-ready architecture. #AIAgents #GeminiAI #Coding #SoftwareEngineering #TechTips #Automation #AIAgents #SoftwareArchitecture #GeminiAI #ErrorHandling #Coding #TechTips #Python #Automation

#AIPoweredVideoCreation What if video content creation could be 80% automated, without compromising quality? Using GPT-4 Turbo and Python scripting, Harbinger helped a technology institute achieve 4x faster turnaround, 75% reduced effort, and scalable content production. 👉 Read the success story: https://lnkd.in/dY68-dcR 👉 Want to build AI-powered learning ecosystems? Consult us at: contact@harbingergroup.com #AIContentCreation #DigitalLearning #eLearning #ContentAutomation #AIinEducation #LearningInnovation #AITransformation #FutureOfLearning

Built a RAG-based AI Chatbot for querying Infrastructure Documentation Worked on creating a chatbot that can answer operational questions directly from an IID (Infrastructure Information Document). The solution uses a Retrieval Augmented Generation (RAG) pipeline to convert documentation into an intelligent knowledge base. Key implementation steps: • Document loading and preprocessing • Intelligent chunking using LangChain • Embedding generation with Sentence Transformers • Vector storage using FAISS #GenAI #RAG #LangChain #AIChatbot #Python #ArtificialIntelligence

Every AI Agent can write a python script to reverse a linked list (I have no idea what that means). But how many AI Agents can order your Phở for tomorrow 👇

𝗔 𝗖𝗼𝗱𝗶𝗻𝗴 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗼𝗻 𝗗𝗲𝗲𝗽𝗴𝗿𝗮𝗺 𝗣𝘆𝘁𝗵𝗼𝗻 𝗦𝗗𝗞 𝗳𝗼𝗿 𝗧𝗿𝗮𝗻𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻, 𝗧𝗲𝘅𝘁-𝘁𝗼-𝗦𝗽𝗲𝗲𝗰𝗵, 𝗔𝘀𝘆𝗻𝗰 𝗔𝘂𝗱𝗶𝗼 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴, 𝗮𝗻𝗱 𝗧𝗲𝘅𝘁 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 In this tutorial, we build an advanced hands-on workflow with the Deepgram Python SDK and explore how modern voice AI capabilities come together in a single Python environment. We set up authentication, connect both synchronous and asynchronous Deepgram clients, and work directly with real audio data to understand how the SDK handles transcription, speech generation, […] The post A Coding Implementation on Deepgram Python SDK for Transcription, Text-to-Speech, Async Audio Processing, and Text Intelligence appeared first on MarkTechPost. https://lnkd.in/ePArsw6s

Python descriptors are more than just a technical detail — they’re the foundation of how attributes behave in your code. By defining __get__, __set__, and __delete__, descriptors give developers precise control over property access, method binding, and class-level behavior. Mastering descriptors means moving beyond syntax into true design power. Whether you’re building scalable systems or refining elegant code, understanding descriptors unlocks a deeper level of Python fluency. At IT Learning AI, we simplify complex concepts into actionable knowledge so you can accelerate your tech journey with confidence. 👉 Learn more and start mastering Python today at itlearning.ai #itlearningai #pythonprogramming #learnpython #codewithconfidence #pythontips #pythondescriptors #techjourney #developergrowth #codesmarter #aceyourtechjourney #codingmadesimple