🚀 Built and deployed an AI-powered Reflection Journal using Google Cloud! As part of the #AccelerateAIwithCloudRun challenge, I built an AI Reflection Journal—a full-stack application that helps users turn everyday thoughts into meaningful reflection and actionable insights. 🧠 Instead of treating AI as a simple chatbot, I designed Gemini to act as a conversational reflection partner — helping users reframe their thoughts and turn reflections into actionable insights. 🔐 Privacy was a key part of the architecture, with Firebase Authentication, user-bound Firestore data, Security Rules, and Google Cloud Secret Manager for secure API key management. ☁️ Built using React, Google AI Studio, Gemini, Firebase, Firestore & Cloud Run. 🎥 Here’s a quick 3-minute demo of me conversing with the application. 🔗 GitHub: https://lnkd.in/gwcuBvhf #AccelerateAIwithCloudRun #GoogleCloud #CloudRun #Gemini #GoogleAIStudio #GenerativeAI #Firebase #AI

The OpenClaw Foundation has released version 2.0 of its open-source AI platform, its largest release to date with over 16,000 pull requests. New features include cloud sessions on rented machines, real-time collaboration, and a browser app rebuilt from scratch. The software now automatically detects existing resources like API keys and AI subscriptions during setup. More: https://lnkd.in/emGdBr_G

After finishing Gen AI Academy Cohort 3 by Google Cloud and Hack2skill, I'm proud to introduce my final Ideathon Project, WriteFrankly. Journaling usually stuck between your paper or your notes app. I built this to put life into your daily entries, letting you talk with your own POV. Designed as a PWA, I wanted this app to bring a distraction-free experience of journaling, all adjusted to your tonal preference. There are a Geocoding to tie your entries to the place you write it, and a debriefing hub to check in on your entries' progress. Key features I put into this: ☁️ Google Cloud Run Hosts the Next.js container for serverless scaling and minimal cold starts during streaming, offering seamless production pipeline. 🧠 Gemini API (Google AI Studio) The brain behind the real-time debriefs across three personas (Warm Confidant, Objective Challenger, Socratic Inquirer) using a fallback ladder across widely accessible Gemini models. 🔐 Firebase & Firestore Gives direct sign-ins, full privacy data of journal entries, encrypted and accessible only to the users. Do try it out and let me know your thoughts on it! https://lnkd.in/gxuPSkfb #AccelerateAIwithCloudRun #GoogleCloud #GeminiAI #BuildWithAI #ProductManagement

🚀 Built and deployed ReflectAI — an AI-powered journaling and reflection app! What started as a basic Gemini journal prototype became something more personal and actionable. With ReflectAI, users can: 📝 Capture and organize personal reflections 🤖 Get personalized insights, summaries, and themes using Gemini 💬 Continue exploring thoughts through multi-turn AI conversations 🎯 Turn reflections into actionable AI-generated plans 📊 Understand reflection patterns over time Built using Gemini API, Firebase Authentication, Cloud Firestore, Google Cloud Secret Manager, and Cloud Run. One of my favorite parts of this project was exploring how AI can go beyond answering questions and instead help users reflect, identify patterns, and take meaningful action. 🔗 Live App: https://lnkd.in/dZw_V8Mi 💻 GitHub: https://lnkd.in/dHAcicfi Excited to keep building and learning with AI and Google Cloud! 🚀 #AccelerateAIWithCloudRun #GoogleCloud #GeminiAPI #Firebase #GenAI #BuildWithAI

A question we get from clients now, more than any technical question: should this feature run its AI on-device or in the cloud? For most of our Flutter builds at RulTech, the honest answer used to be "cloud, always" - easier to update the model, easier to monitor, no worries about device fragmentation. That default is getting harder to defend. On-device options like Core ML and TensorFlow Lite have gotten good enough that for a lot of features, sending every request to a server is just added latency and added cost for no real benefit. The trade-off nobody puts in the pitch deck: on-device means you ship a model inside the app binary, and updating it means shipping an app update, not a server deploy. For a feature that needs to improve weekly, that is a real constraint, not a footnote. Our rule of thumb has become fairly simple. If the feature needs to work with a flaky or absent connection, or if latency is part of the user experience, lean on-device. If the model needs to improve fast based on real usage data, keep it server-side, at least until it stabilizes. Neither answer is more sophisticated than the other. Matching the constraint to the actual feature is the whole job. For teams shipping AI features in mobile apps, how are you deciding where the inference actually runs? #ArtificialIntelligence #Flutter #MobileDevelopment #OnDeviceAI #RulTech

AI can generate thousands of lines of code in minutes. Understanding what it changed across your application, and whether it is ready to deploy, takes far longer. The Microsoft Azure Incubations team announced the public preview of Radius Canvas for the GitHub Copilot app. With Radius, developers can visualize the structure of their modern cloud-native applications, see where code changes impact their applications, and deploy applications across different cloud providers. It gives developers and agents a shared, consistent, visual definition of the application to work from instead of reconstructing it from scattered artifacts on every code change. https://lnkd.in/gep-TBvQ

🚀 Just shipped: Personal Gemini Journal! Built an AI-powered journaling app that goes beyond static notes to help users reflect, identify patterns, and find clarity. ⚡ Powered by Google AI Studio and Firebase for intelligent, context-aware conversations and secure cloud architecture. Tech Highlights: Gemini API: Context-aware, multi-turn conversational journaling. AI Journal Insights: Synthesizes thoughts into clear themes and actionable takeaways. Firebase & Firestore: Secure authentication and private, isolated user storage. Production-Ready Hygiene: Hardened repository security standards and structured documentation. 🔗 GitHub: https://lnkd.in/eCNfRJMN #AccelerateAIwithCloudRun #GoogleAIStudio #GoogleAI #GeminiAPI #Firebase #BuildInPublic#GoogleforDevelopers

Every SaaS company has the same graveyard: features nobody found. We keep solving it with onboarding tours, tooltips, help docs, a chatbot that links you to the help docs. All of it is still the user doing the work. What if they could just say what they want? Ringg AI Copilot, a voice agent that lives inside your web app and does the clicking for them. 🧭 Navigates on its own ✅ Asks before it acts ⚡ Finishes multi step flows end to end Here it is spinning up (and deleting) a VM on Google Cloud while my teammate just talks with it. Real audio, only the quiet bits sped up. If a user can talk to your product, your UI stops being the bottleneck. Curious whether you'd ship this on your own app and where you'd draw the line on what it's allowed to touch. 👇

Yesterday, I demoed Ringg Copilot to two clients, and their reaction was simply 🤯 What makes it exciting? It doesn’t just tell you what to do — it actually sees your browser and interacts with it. We showcased real-world use cases like assistance in buying health insurance and selling medicines, where the Copilot can navigate websites and assist users through the journey just like a human would. Seeing the clients experience this live and immediately understand the possibilities was amazing. This is where AI starts moving from conversation to action. 🚀 #AI #AgenticAI #ConversationalAI #Healthcare #AIInnovation #RinggAI

🚀 Just built my Personal Gemini Journal for the Google Cloud x Hack2skill Gen AI Ideathon! An authenticated AI journaling app where you can: 🔐 Sign in securely with Firebase Authentication 💬 Have real multi-turn conversations with Gemini 📝 Get your reflections auto-summarized and saved 🔒 Fully isolated per-user storage in Cloud Firestore — zero cross-user leakage 🏷️ Bonus: AI-generated tags + search across your journal entries Built with React, Firebase, Firestore, and the Gemini API, with Custom Instructions in Google AI Studio baked in from the start to enforce secure, production-grade code — no hardcoded secrets, strict auth checks, and per-user data isolation. Check out the (silent) demo below 👇 GitHub: https://lnkd.in/dxFCw7Xk #AccelerateAIwithCloudRun #GoogleCloud #GenAI #Hackathon #Firebase #Gemini