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AI for Web Devs: Prompt Engineering https://bit.ly/48KNfAx Welcome back to this series where we are building web applications that incorporate AI tooling. The previous post covered what AI is, how it works, and some related terminology. Intro & Setup Your First AI Prompt Streaming Responses How Does AI Work Prompt Engineering AI-Generated Images Security & Reliability Deploying In this post, we will cover prompt engineering, which is a way to modify your application’s behavior without changing the code. Since it’s challenging to explain without seeing the code, let’s get to it. via DZone AI/ML Zone https://bit.ly/41qvfZp January 23, 2024 at 08:04AM

Just built a personal website without writing a single line of code myself—thanks to AI! I’ve been experimenting with tools like v0, Cursor, and Claude Sonnet 3.5, and I’m genuinely impressed by their capabilities. The free tier of Cursor, combined with Claude’s advanced debugging and iteration features, is a game changer for web design. If you have a clear design in mind, you can bring it to life just by describing it, and while it's not a one-click solution, continuous refinement through prompts gets you exactly where you need to be. Debugging errors has also become smoother than ever. Here’s a simple site I created using AI! 🌐 #AI #WebDesign #NoCode #Cursor #ClaudeSonnet #Innovation

🚀 Excited to share my latest project: SmartDoc! 🚀 SmartDoc is an advanced document search engine that combines *Retrieval-Augmented Generation (RAG)* with the *Qdrant vector database* to deliver highly relevant and contextually accurate search results. 🔍 Key Technologies: - RAG: Enhances search with intelligent document retrieval and generation. - Qdrant: Provides efficient, high-dimensional vector storage and similarity search. - FastAPI: Powers the backend with high performance and asynchronous capabilities. This project showcases how integrating cutting-edge AI techniques and modern web technologies can revolutionize search systems. Check it out and see how these innovations can elevate your data retrieval solutions! #AI #MachineLearning #FastAPI #VectorDatabases #RAG #TechInnovation #SmartDoc

👨💻 How accurate are GenAI models when recreating webpage from a single screenshot? 🖥️ Turning website designs into working code can be tough as it involves understanding how visual elements are arranged and then coding them in a structured way. However, multimodal LLMs (GPT-4, Gemini, etc.) show great promises in tackling this problem. 📲 A team of 5 AI experts has worked on research to find out how far we are from automating front-end engineering using the top GenAI model. 📌 Checkout their findings in the blogs here: https://lnkd.in/g2JdEGUm

Initial thoughts on OpenAIs new o1 model … 🤷♂️ Certainly a measurable improvement on certain classes of problems you might categorise under “reasoning”. But not really that much better than what I’ve seen with a few clever chain-of-thought implementations using existing models. I’ve got a coding task that I’ve used on Claude Opus and the GPT models that I work with all morning. And like the other models, as soon as you try to accomplish anything collaboratively, coding or other content creation … it is still the dumbest smart person you’ve ever met. The examples where you give it one line and it builds an app … ok, but that’s actually the least useful thing you can imagine in the real world. Somehow you are going to like the first version of anything so much you want no changes? Managing the context, memory, and UX is still super critical. And the current cost structure of the new model is significant. Given those factors, production systems will need composite AI system wrapped around the model, and you are going to be using multiple models in those composite systems anyway … so net-net .. not actually seeing how this release moved the needle. Let’s keep a close eye on how the costs come down or the efficacy grows. And I’ll keep playing with it. But let me know if you are seeing something on this model that I haven’t gotten to yet. #aiproductmanagement

If you’re a coder looking to dive into AI, start with Cursor and its Composer feature. The key is to remember: AI won’t write production-ready software for you, but it’s great at writing code, collaborating on architecture, and explaining complex code. I often ask Cursor to teach me, rather than just do the work for me—or have it do the work, and then explain it. Think just in time learning. Check out this demo from McKay Wrigley to see it in action: https://lnkd.in/ekdxhGdu #AI #CodingWithAI #SoftwareDevelopment #AIForDevelopers #CursorAI #CodingTips #AIInTech #CodeCollaboration #TechInnovation

Friend or foe? The AI revolution is upon us, but will AI become our coding comrade or steal the keyboard? Let's discuss the potential and challenges of AI in web development - from automation to creativity! #AIInWebDev #FutureOfWork #HumanVsMachine

Plastic Labs Unveils Honcho: Elevating User Context Management for AI Agents Honcho, a project by Plastic Labs, is a user context management solution designed for building AI Agents and Large Language Model (LLM) powered applications. It’s a monorepo containing a server/API for managing database interactions and storing application state, along with a Python SDK for interacting with the API. The API provides user context management routes and the project uses FastAPI and poetry for dependency management. It’s designed to facilitate the development of applications at the intersection of human and machine learning. #PlasticLabs #Honcho #UserContextManagement #AIAgents #LLM #FastAPI #PythonSDK #TechInnovation #TechNews #AIApplications

Ahh the patterns of production LLM applications… 🤖 First GPT 🏗️ First LLM App 🗃️ First RAG App 🕴️ First Agent App ⚖️ First Fine-Tuning 🔗 LangChain RAG 🦙 LlamaIndex RAG 📈 RAG Evaluation 🚀 Open-Source Production RAG 🔄 Agentic Production RAG 🌐 Domain-Adapted RAG with Fine-Tuning Get a handle on these concepts and code, start building, shipping, and sharing like a legend, and you’ll be creating real value for yourself, your company, and the world in no time! 🏗️ Start building for free, async: https://bit.ly/3UNimrg 🧑🤝🧑 Supercharge your AI Engineering journey with live cohort instruction, like-minded peers to meet you where you are and to show you where you’re going, accountability deadlines, and the most up-to-date curriculum you can find in the industry at the open-source edge: https://bit.ly/47GESVt #llms #production

Building with AI? Here's our engineering ins and outs for 2024: 👍 In: Running a pipeline by calling an API. 👎 Out: Manually implementing an AI pipeline with code. 👍 In: Step-level observability of pipelines. 👎 Out: Reading a wall of code that only engineers can understand. 👍 In: A visual WSYIWIG overview of the pipeline that *is* the pipeline. 👎 Out: Manually creating and maintaining a pipeline diagram to match with the code. 👍 In: Knowing that you won’t break a pipeline when making changes. 👎 Out: Breaking a pipeline every time you iterate on it. 👍 In: Building a pipeline at the same time as you’re designing it. 👎 Out: Designing a pipeline, then coding it separately.