Avi Chawla’s Post

Developer Updates - July 2024 Several updates to share with you as we get ready for Launch Week! https://lnkd.in/eRZtXET7 - Launch Week 12 Join us August 12-16 for our next Launch Week event. We will be announcing a number of new features and giving away some great swag! https://lnkd.in/guZ5hybC - Disable Data API for Your Project You can now disable the Data API when creating a new project with a setting under "Advanced Options". This option bolsters the security of your data by preventing unintentional access from clients. https://lnkd.in/eHu92itG - Custom Schema for Data API Your project's Data API exposes the public schema by default, the most commonly used schema, and can lead to unintentional access to your data. Now, you can dictate which custom schema to expose via the Data API for better security and granular control. https://lnkd.in/eHu92itG - Save Money With Hourly Storage Billing On August 20, 2024, Supabase is changing billing for Storage from daily to hourly for new customers and gradually rolling it out for existing customers shortly thereafter. There are no billing changes for projects who continue to use Storage for the entire month while projects using Branching or Storage for partial months will see a reduction in their bill. https://lnkd.in/ePAzWC2e - Deploy More Functions at No Extra Cost We have increased the number of Edge Functions across all plans at no extra cost and removed usage-based billing to simplify your bill. https://lnkd.in/eyQkcmp3 - Quick product announcements • [Database] Postgres 13 Deprecation Notice • [Auth] Migrate from Auth0 to Supabase Auth • [Branching] You can customize the public environment variable prefix to use any framework • [Docs] Supabase docs now feature global navigation bar - Made with Supabase Krea - Realtime and interactive image generation in the browser, the easiest way to generate with AI Cheat Layer - The most powerful no-code agent editor on the planet. Learn new RPA concepts to build future-proof agents that are impossible in other RPA tools Udio - Generative music, you can even edit segments of the tracks using AI Pika - The idea-to-video AI platform that sets your creativity in motion. MakePodcast - Effortlessly craft professional podcasts in minutes using AI - Community Highlights Using Pre-commit Hook to Upload Local Media to Supabase Bucket Build Library Management System Using React, Shadcn/ui, Supabase and React Query From Scratch Instagram Clone in React Native: Video, Backend with Supabase & Push Notifications It all starts with Postgres (Interview to Paul Copplestone) GraphQL Quickstart with Supabase 13min High Intensity Postgres Workout (NO REPEATS) Read here: https://lnkd.in/eRZtXET7

A sneak peek of what I had been working on last Sunday with AutoProject. I updated the UI interface and added a bunch of settings to control. I haven't pushed the changes yet. Doing some testing and cleanup. Will push everything sometime this week. #StayTuned But here's what's coming soon: 1. Support for Asana, Atlassian Jira, and Plane to automatically create a project with user stories based on your requirements. 2. More prompt engineering to steer how the PRD and User stories should look like and what format they should follow. 3. Extending AI inference support to Groq and LM Studio, apart from Gemini Pro. Groq is a cloud platform that runs fast AI inference on their custom hardware. I have provided Llama 3 70B and the latest Mixtral MoE model. Groq is by far the fastest inference service out there and also comes with a nice free tier to use. LM Studio is a desktop app to interact with open-weighted LLMs, locally on your system. It can also be used to run an AI inference server right on your computer. So, there are no rate limits, and it's completely free to use. Via the LM Studio server, you can run models like Phi-3 and Llama3-8B to run local inference. Here's what I learned while implementing these updates. 1. As we have more options and customized models to pick from, aggregation of options becomes important, especially when considering the costs of running inference. The combined rate limits of multiple models and inference platforms will increase usage within the free tiers. Beyond that, tools like LM Studio can help with unlimited inference (although slow and less efficient for now). Having a unified platform that aggregates and helps you toggle between all options can be of great use. Whatever I implemented here at AutoProject can be exported to any AI tool to give that optionality. It looks like an API service or an SDK that wraps on top of all AI platforms and models together into one is a good project idea. Instead of subscribing to multiple cloud platforms and services, you can use a unified one. Perhaps I will create this as a utility to use across projects. 2. AI models are getting fine-tuned into a special "JSON mode." Groq already provides this on their platform, and other AI companies are doing the same. This enables the AI model to act like a very fluid and dynamic API layer where the model will strictly respond in JSON strings, which can then be parsed into a JSON response. This is very useful for implementing agentic workflows where different agents must intricately communicate with each other in JSONs. JSON mode also increases AI agents' reliability, validation, and explainability. You can be very sure about the agentic behavior and control it precisely as you control the models with predefined JSON structures.

https://lnkd.in/eGH67Gvv #ApiLogicServer lets developers and low-code users define and deliver an application from an AI prompt using OpenAI configured locally in mere minutes.  This article is an easy read, and guides you through the steps to demonstrate a quick use case.  Once you’re setup, you’ll have the power of AI at your fingertips.   What, you want to start a new child care business or maybe you just bought a property on the canal and you’d like to start a boatyard storage business?  Any idea can be modeled to start your app.  What’s cool is that the process is iterative allowing you to all logic rules, and additional entities to your data model. try it!  It’s allot of fun. great job Val Huber

🚀 Excited to share insights from the "5 Pillars for a Hyper-Optimized AI Workflow"! 🧠 Here's a quick recap: 1️⃣ Metric-Based Optimization: Measure success with clear KPIs! 📊 2️⃣ Interactive Developer Experience: Foster innovation & collaboration! 🛠️ 3️⃣ Production-Ready Code: Focus on scalable, maintainable code from day one! 💻 4️⃣ Modular & Composable Architecture: Enhance flexibility with reusable components! 🔄 5️⃣ CI/CD Practices: Automate testing & deployment for reliability! ⚙️ These pillars can significantly boost efficiency, scalability, and innovation across industries like healthcare, finance, and retail. 🌟 Want to dive deeper? Connect with us for personalized insights! 💬 👉 [WhatsApp](https://lnkd.in/eXCvFp6H) | [LinkedIn](https://lnkd.in/efEUt3pR) Source: [Towards Data Science](https://lnkd.in/ehzihdVf)

I wanted to give you a heads-up on an exciting new tutorial I’ve got in the works. This video is all about building a full-stack SaaS application that pulls in YouTube comments, processes them with CrewAI enterprise, and generates actionable content ideas. If you’re interested in building full-stack AI applications, this is for you! 🛠️ Here’s What You’ll Learn In this tutorial, I’ll guide you through each part of the process of creating this full-stack application. Here’s a breakdown: 1️⃣ Building the Frontend and Backend: We’ll use Next.js to set up the app and deploy it on Vercel. Plus, you’ll get hands-on experience connecting to a Neon Postgres database to manage data. 2️⃣ Integrating with CrewAI Enterprise: Learn how to harness CrewAI’s enterprise features to analyze YouTube comments, filter out casual messages, and focus on meaningful feedback. You’ll see how to create a system that automates data analysis and transforms raw comments into structured, actionable insights. 3️⃣ Generating Video Titles and Descriptions: We’ll configure CrewAI to turn filtered comments into potential video titles and descriptions. You’ll build a workflow that streamlines idea generation and content planning, using CrewAI’s advanced capabilities. 💡 Why This Tutorial is Worth Your Time This tutorial doesn’t just cover building one app—it teaches you how to apply the synthesize pattern for data processing, a core skill in AI development. Here’s why this matters: ✅ Real-World Adaptability: The synthesize pattern goes beyond YouTube. After learning it, you can apply it to dozens of other applications where large datasets need to be turned into insights. Imagine using this pattern for customer feedback, product analysis, or trend monitoring—there are endless opportunities to build your own AI-powered apps! ✅ Hands-On Full-Stack Skills: Get practical experience with tools like Next.js, Vercel, and Neon, and learn how to bring everything together into a seamless app. 📅 How to Catch the Release I’ll be releasing this video on my YouTube channel. Head over there, subscribe, and turn on notifications to be the first to know when it drops! I’ll also have links to my YouTube, my free Skool community, and the Pro community down in the comments below. Drop any questions you have, and see you soon! 👋 CrewAI Neon Vercel

🚑 New blog post Looking to simplify building AI apps? Whether you're working with LLMs, managing workflows, or securing data, Griptape has you covered. 💡 Read my latest article to learn more:

🗓️ New Month, Newer Announcements. Don't miss WorqHat's Launch Week with a new slate of amazing and exciting features across both our WorqHat Playground (aka WorqBot) and our AI APIs. Here’s Day 1 of everything that we shipped over the last month. It was a lot of hard work from the WorqHat HQ!!!! You can try out all these amazing features by visiting https://lnkd.in/ddMD3QF2 1) Newer Revamped UI for WorqHat Playground: Design with boldness and speed at its heart. For us, it's all about embracing the fast lane 🚀 and making sure our design not only looks good but feels welcoming and easy to navigate, and that is why we wanted to make WorqBot feel simpler and easier to use. 2) Fine Grained Control over the AI’s Responses: Starting in English, you can now just select the portion of text you want to change, give some instruction, and get an output that’s closer to what you are looking for. 3) Edit, Run and Ask AI to Modify code within Playground: You can now edit and run most code snippets directly to see how changes affect the output, and verify that the code works as intended. 4) Making Live and More Recent Data accessible: WorqHat AI now uses Web Crawlers to return sources from Publicly Accessible YouTube and Web Links. Released earlier as an API, it is now available for everyone via Playground. We can’t wait to know about all the amazing things you can do with WorqHat AI, please do let us know and send us all your feedbacks, and stay updated for all the amazing announcements coming this week. Read more at: https://lnkd.in/dsk-M9b6

API + AI = Upgraded developer life quality? And that's possible because of... A new product from Treblle. Meet Alfred, your new AI assistant created to: - Make API integrations 10x faster. - Enhance developer experience by doing the heavy lifting for you. Setup and integration are done in two steps under 60 seconds: - Install SDK - Add 2 lines from the docs (HTML + JS) By adding Alfred, you'll get benefits like: - API discovery: Just ask Alfred what you're looking for, and he'll provide an answer in seconds - API integration: Generate code and models in seconds instead of spending hours or days - API adaptation: Easily navigate through all your APIs, enhancing adoption and developer experience. I've played around and was pretty surprised at how AI can help us with our everyday jobs. (And not taking our jobs!) So, don't wait any longer. Be like Batman. Get your Alfred here: https://shorturl.at/ukdfM Let me know in the comments what you think! ✍

Must-read if you're interested in creating AI agents. It will save you significant time building agent-based systems while maintaining simplicity and power. TLDR: Simple, composable patterns often work better than complex frameworks. Start with the simplest solution and only add complexity when needed. Two main types of agentic systems: -- Workflows: Systems with predefined code paths -- Agents: Systems where LLMs dynamically direct their own processes Common effective patterns include: -- Prompt chaining (sequential steps) -- Routing (classifying and directing inputs) -- Parallelization (simultaneous tasks) Key recommendations: -- Focus on simplicity -- Be transparent about planning steps -- Carefully design tool interfaces -- Consider frameworks for starting, but understand the underlying code -- Test extensively in sandboxed environments

“AI agents are going to drive demand for APIs through the roof.” Scott Brinker, explores the landscape of integration in the #martech stack (but with considerations that go much beyond that). A peek into a future where apps will have to expose APIs and get over the concern that this will “reduce the usage of their human-oriented UI.” As always, insightful stuff from Scott!