AI Agent Hackathon Day 1: Problem Deep-dive and Tech Stack Decision

💡 Ever wonder what separates average AI agents from truly game-changing ones? ARCHITECTURE. Day 2 at the AI Agent Hackathon by Product Space: Laying the Bricks for Next-Gen Support! 🏗️🤖 Today, Akshat Gupta and I dove into the blueprint for my Customer Sentiment Alert Agent — and I’m buzzing about how it’ll transform the support workflow. Here’s our architect’s sketch: 📝 Input Layer: Captures reviews, X (Twitter) mentions, and forum chatter LIVE. ⚡ Processing Engine (Multi-Agent): Sentiment Classifier Agent: Instantly analyzes tone (positive/neutral/negative) Prioritization Agent: Ranks issues by severity + viral potential Response Generator Agent: Drafts smart replies for support teams (no more blank screens) 🚀 Output Layer: Pushes tailored alerts and reply drafts straight to Slack and Email. Sneak peek: https://lnkd.in/dgmB_B7u Why this matters: Support doesn’t need more noise. They need high-signal, actionable alerts—plus the right words to respond fast. ✨ Today’s big win: The best agent architectures? They’re not defined by hype tech, but by smooth info flow: pain point → priority → solution. 🛠️ Up Next: Tomorrow = hands-on prototyping + our first real-world fire drill. Question for you: 👉 If you could add ONE superpower to this agent for support teams, what would it be? 👇 Drop your ideas—let’s co-create the future of #AgenticAI! #AI #CustomerExperience #SupportAutomation #Hackathon #ProductManagement #Innovation #LinkedInTrending

AI agents are everywhere right now — but making them actually useful in real-world chaos? That’s the real challenge. Day 1 of the AI Agent Hackathon with The Product Space 🚀 We kicked things off today, and I’m diving into a project on customer feedback overload for product teams. Here’s what’s exciting about my approach: 1️⃣ Feedback is everywhere (surveys, in-app, socials) — and teams spend way too much time figuring out what matters. 2️⃣ Instead of building “yet another chatbot,” I’m going agentic: a GenAI-powered multi-agent system that classifies feedback, scores urgency, understands sentiment, and automatically pushes prioritized updates — basically, it behaves like a team member. 3️⃣ MVP strategy: core logic runs in LangChain (scoring, LLM classification), while LangGraph will visualize the workflow/demo for judges — the pipeline looks like a flowchart, but the AI actually runs in the backend. Biggest aha moment: GenAI shouldn’t just automate — it should think alongside you and make smarter decisions in real time. Next up tomorrow → sketching the architecture and testing the agentic loop. Curious: what’s one repetitive task you’d happily hand over to a GenAI agent? Could steal your idea for the next feature 😉 #GenAI #AgenticAI #Hackathon #AIAgents #TheProductSpace #LangChain

Imagine an AI agent that never sleeps—catching negative feedback the moment it appears, before it even spreads. Day 1 of the AI Agent Hackathon by Product Space! 🤖 Just finished the kickoff call and I'm fired up to build an AI agent that tackles support teams missing early warning signs of negative sentiment online—alongside my amazing teammate Dhavan M 1️⃣ Problem Deep-dive: Realized that unnoticed negative customer feedback on social media and reviews affects way more businesses than I thought. 2️⃣ Agent Approach: Instead of building another chatbot, I'm thinking a multi-agent system with specialized roles, monitoring, analyzing, and alerting in real-time using n8n workflows. 3️⃣ Tech Stack Decision: Using n8n for automation, Supabase for database and storage, and planning to build a frontend dashboard in the next few days to visualize insights. Biggest insight from kickoff? The best AI agents don't just automate tasks—they augment human decision-making. Up Next : Agent and Model Integration and designing the frontend. We’re building an AI that spots problems before they explode. What’s one tedious or repetitive task in your workflow that you’d hand over to AI? Let’s crowdsource inspiration! #ProductSpace #AI #AIAgents #Automation #n8n #Supabase #Hackathon #ProductSpace #CustomerExperience #SentimentAnalysis #AIforBusiness #TechInnovation #AIWorkflow #RealTimeMonitoring

My AI agent just had its first conversation with a tweet. It was... surprisingly insightful. 🤖💬 Day 2 of the AI Agent Hackathon by Product Space - PROTOTYPE DAY! Our 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐒𝐞𝐧𝐭𝐢𝐦𝐞𝐧𝐭 𝐀𝐥𝐞𝐫𝐭 𝐀𝐠𝐞𝐧𝐭 is officially alive and tackling the problem of unnoticed negative feedback that support teams often miss until it snowballs. What it can do right now: -Takes tweets and reviews as input -Processes them through 3 specialized agents (collection, sentiment analysis, response drafting) -Outputs a structured JSON report + suggested response within seconds Early testing reveals: ✅ What works: The AI can reliably classify sentiment and urgency, and even draft empathetic replies that sound human. ⚠️ What needs work: Handling edge cases (sarcasm, mixed feedback) and avoiding too many "neutral" classifications. The agent occasionally misclassifies or outputs messy JSON, but those "mistakes" will help us design stronger error handling for tomorrow. Up next: Refining model consistency, connecting the agent with Slack, and starting the frontend dashboard to visualize insights. #AI #AIAgents #Hackathon #Automation #n8n #Supabase #SentimentAnalysis #CustomerExperience #ProductSpace #AIWorkflow #TechInnovation #Slack #MachineLearning #RealTimeMonitoring #DataAutomation #AIforBusiness #CustomerSupport #AIAlerts #BusinessIntelligence #AIinAction #AIApplications

If you’re trying to apply AI to observability and you haven’t checked out Causely, what are you waiting for?! I saw a recent Grafana Labs report that ~80% of enterprise tech leaders are actively exploring AI for observability but only ~3% have something meaningful in production. We have all seen slick AI demos, but they all rely on near perfect data and for the most part they all fall flat in the real world of enterprise tech. Whether you are building or buying in this category, your AI Agent/Copilot needs a way to receive real-time context about cause and effect to eliminate hallucinations and get to the right actions faster. That’s one of the critical gaps our system fills for customers, and it works with any observability solution out there (built, bought, or anywhere in between). If you want to learn more, drop me a note. You have nothing to lose by reaching out.

AI Agents can track everything online, but negative feedback still slips through the cracks..." Day 1 of the AI Agent Hackathon by Product Space! Product Space 🤖 Just finished the kickoff call and I'm fired up to build an AI agent that tackles detecting negative customer sentiment before it spirals into a PR issue. Here's what caught my attention today: 1️⃣ Problem Deep-dive: Realized that support teams miss early warning signs in scattered reviews, tweets, and forum posts, which often go viral before action is taken. 2️⃣ Agent Approach: Instead of building another monitoring tool, I'm thinking a real-time AI agent that tracks mentions, alerts the team instantly, and suggests the right response. 3️⃣ Tech Stack Decision: Leaning towards Gemini API for sentiment detection, PostgreSQL for storage, and Slack/Email for notifications. Biggest insight from kickoff? The best AI agents don't just automate tasks—they guide humans to turn frustrated users into loyal customers. Tomorrow: Architecture planning and connecting the first data sources. What's one customer issue you wish support teams could catch instantly? Drop ideas below—it might inspire my next feature! #AI #AiAgents #Hackathon

Every day, I come across at least 7 new AI products, and yes, I actually sign up for them, join the waitlists, and test them out. The pace of AI innovation is mind-blowing. We’re witnessing an explosion of new tools promising to redefine everything from design workflows to business automation. But here’s the honest truth: While the tech is exciting, I often find myself struggling to identify a strong, tangible #usecase for many of these products. So many AI tools look impressive in demos but don’t quite fit into my actual daily routines or solve deep, persistent problems. The gap between novelty and necessity has never been wider. My approach? Stay curious, keep experimenting, and focus on what truly adds value and not just what’s trending. For fellow explorers out there: how do you separate hype from genuinely useful innovation? Would love to hear your thoughts and discoveries! #AItools #Productivity #Innovation #UXDesign #Automation #AIexploration

🚀 Big milestone for the Everest platform. We’re excited to share AiSpecify v2, featuring the new AiDesign tool — a major step forward in how businesses design and build applications. AiSpecify already automated comprehensive specification generation. Now with AiDesign, users can go from concept to creation faster — visualizing, refining, and generating application designs directly within the platform. This is the next leap toward truly AI-driven business systems. https://lnkd.in/gRVUMxWv

Reposting this amazing announcement from Franz Faerber to my network. At Everest Systems, we have been focused on enabling AI to code unique and tailored software solutions. To achieve success in this endeavor, we recommend adhering to the following criteria: 1️⃣ Avoid iterative prompting that can mislead AI models (see https://lnkd.in/e2yY6Y5M). Instead, allow AI to generate professional specifications for your projects. Utilize a specification-generating tool to kickstart your Vibe Coding initiatives. See https://lnkd.in/efBy22Nn 2️⃣ Establish a solid foundation by reusing existing software that ensures auditability, security, compliance, and other essential functions. Integrate with other business systems through APIs that provide mission-critical guarantees. 3️⃣ Reduce risk by operating in an isolated environment that still has access to real production data. We refer to this approach as "Live Sandboxing." See also https://lnkd.in/e8gVU_QD

We’re excited to share #AiSpecify v2, featuring the new AiDesign tool — a major step forward in how businesses design and build applications. AiSpecify already automated comprehensive specification generation. Now with AiDesign, users can go from concept to creation faster visualizing, refining, and generating application designs directly within the platform. This is the next leap toward truly #AI-driven business systems. Everest Systems https://lnkd.in/gRVUMxWv