AI Agent Fundamentals - The document covers agent fundamentals, providing foundational knowledge for understanding AI agents [1] - It differentiates LLM, RAG, and Agents, clarifying their roles and relationships in AI systems [1] - Agentic design patterns are explored, offering insights into structuring and organizing AI agents [1] - Building blocks of agents are outlined, detailing the essential components for constructing AI agents [1] Practical Applications - The document includes 12 hands-on projects for AI Engineers, providing practical experience in building AI agents [1] - It covers building custom tools via MCP (likely referring to a specific methodology or platform), enabling customization and extension of AI agent capabilities [1] Resource Availability - A PDF containing all AI Agents posts is available for download, offering a consolidated resource for learning about AI agents [1]

AI Agent Fundamentals - The document covers AI Agent fundamentals [1] - It compares LLM, RAG, and Agents [1] - It discusses Agentic design patterns [1] - It outlines the Building Blocks of Agents [1] AI Agent Development - The document details building custom tools via MCP [1] - It includes 12 hands-on projects for AI Engineers [1]

AI Agent Development - The industry is focusing on building AI Agents in production [1] - The industry provides hands-on tutorials for learning AI Agent development [1]

That's a wrap!If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):I have been building AI Agents in production for over an year.If you want to learn too, here's a simple tutorial (hands-on): ...

I have been building AI Agents in production for over an year.If you want to learn too, here's a simple tutorial (hands-on): ...

RT Iason Gabriel (@IasonGabriel)Pleased to share our new piece @Nature titled: "We Need a New Ethics for a World of AI Agents".AI systems are undergoing an ‘agentic turn’ shifting from passive tools to active participants in our world.This moment demands a new ethical framework. https://t.co/JTbfaqOAzR ...

This MoonPay x Axal partnership makes no reference to AI Agents.“Automated Yield” is the term used.Agents will become the standard user interface for crypto, and the internet more broadly.UX is going to evolve exponentially in the next 12 months.https://t.co/SbXWQLWXAC ...

RT Shape (@Shape_L2)announcing shapecraft² - bringing ai agents to nfts1,000,000 $SHAPE & apple tech prize poolthe biggest nft hackathon returns august 23 - 24!sponsored by @opensea @Alchemy @manifoldxyz @TransientLabs @0xDecaArt @Collab_Currencysign up below ⬇️ https://t.co/VGIXRdo243 ...

AI Agents Are Coming For DeFiTwo standouts: Moonwell’s Mamo and the crowd-favorite Bankr. One automates yield farming. The other turns your chat box into a trading terminal.Both live inside the Base App and make your money work without you lifting a finger.Here’s how they’re reshaping DeFi’s interface.👇~~ Analysis by @davewardonline ~~Mamo@Mamo_agent, from lending protocol @MoonwellDeFi, shows the power of specialization. Its job: extract max yield from your USDC and cbBTC.You deposit, and Mamo moves your f ...

AI Fundamentals - Generative AI works by probabilistically filling in the blanks based on pre-trained data, essentially acting as an advanced autocomplete [5][6] - Pre-training involves feeding massive amounts of unstructured data into large language models (LLMs), requiring significant energy and resources for processing and refinement [7][8][9] - Reinforcement learning and reasoning enhance AI accuracy by implementing strategic action and assigning scores to generated results, reducing hallucinations [11][12] AI Applications in Business - AI agents can automate tasks across various tools and interfaces, acting as digital employees capable of understanding unstructured data and executing actions [13][14] - AI tools can significantly scale business operations, as demonstrated by a cosmetics brand using an AI agent to streamline influencer marketing, reducing the required team size and time [21][22] - AI agents are being used in sales to personalize outreach and automate follow-ups, leading to increased order rates and reduced campaign costs [24] - AI is being applied in operations to automate pricing and quotation processes, monitor safety incidents, and improve response times [25][26] - AI is aiding in financial analysis by enabling rapid screening of stocks based on specific criteria, leveraging open-source tools to retrieve data from millions of PDF files [28] AI's Impact and Future - AI is evolving beyond replacing existing processes to facilitating new inventions, such as a novel use case for magnetic ink in supply chain management [30][31][32][33] - The industry is rapidly advancing towards artificial generalized intelligence (AGI) and artificial super intelligence (ASI), with continuous improvements in AI models and capabilities [34] - The fundamental question is raised about the role of humans in a world where many jobs can be automated, emphasizing the importance of curiosity and relentless questioning [34][35]