Day 2 of AI Agent Hackathon: Building frontend and databases 🎯 Mission: Build the frontend and set up the database for my AI agent that helps employees find internal processes faster—no more hunting through Notion, Google Docs, or Confluence. Here’s what went down: 1️⃣ Frontend Foundations: Started sketching a clean, intuitive UI that feels more like a teammate than a tool. Thinking minimal clicks, smart suggestions, and contextual search. 2️⃣ Database Setup: Structured the backend to handle multi-source ingestion and semantic indexing. Early tests show promise in surfacing relevant info across platforms. 3️⃣ Agent Integration Prep: Laying the groundwork for agent orchestration—soon these agents will collaborate like a dream team. ⚡ Biggest win today? Seeing raw data turn into something usable. The moment when tech starts feeling like magic. Tomorrow's Task: Connecting the dots—agent logic, orchestration, and real-time responses. #AIHackathon #Day2 #FrontendDev #DatabaseDesign #MultiAgentSystems #LangChain #AutoGen #CrewAI #ProductSpace #HackathonJourney #AIForHumans

🌩️ 𝐀𝐦𝐛𝐢𝐞𝐧𝐭 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 𝐚𝐫𝐞 𝐥𝐢𝐯𝐞 , 𝐰𝐡𝐢𝐜𝐡 𝐬𝐭𝐚𝐜𝐤 𝐚𝐫𝐞 𝐲𝐨𝐮 𝐛𝐞𝐭𝐭𝐢𝐧𝐠 𝐲𝐨𝐮𝐫 𝐭𝐞𝐚𝐦 𝐨𝐧? if you’re exploring ambient-tuned agents that stay listening, remembering, and acting, so you know the frameworks keep evolving: LangGraph, LangChain (ambient flow), AutoGen, CrewAI, n8n, and more. They might look similar, but they serve very different ambient use cases. Here’s your breakdown: 🔁 𝗟𝗮𝗻𝗚𝗿𝗮𝗽𝗵/LangChain (by Harrison Chase & the LangChain team) Purpose-built for event‑stream agents. Manages long-term memory, event triggers, durable state checkpoints, and “time‑travel” for human-in-loop review. Ideal for agents that log, reflect, and respond over hours or days. 🔗 𝗟𝗮𝗻𝗴𝗖𝗵𝗮𝗶𝗻 (Ambient Agents Starter Kit) The OG LLM toolkit that powers ambient demos like email assistants on LangChain Academy. Best for single-stream agents, MVPs, and hybrid chat + ambient flows using LangGraph under the hood. 🟥 AutoGen (Microsoft) An event-driven, actor-model framework built for multi-agent ambient pipelines. Perfect when your workflows must scale asynchronously across parallel event handlers. 🤖 CrewAI Lightweight, open-source orchestration for role-based agents (“crews”) that work off event tasks. Simpler than LangGraph, yet strong in rapid prototyping and visualisation. 🎛 n8n  No-code/low-code rule-based tools that listen to basic triggers (e.g. new data, webhooks). Great for hooking ambient agents into SaaS platforms—but limited for rich memory and planning. 🧠 Bottom line which ambient stack is right for you? 🚀 Want to start building? I’d recommend: Try open-source CrewAI or LangChain for multi-agent architectures. 𝐈𝐧𝐭𝐞𝐫𝐞𝐬𝐭𝐞𝐝 𝐢𝐧 𝐡𝐚𝐧𝐝𝐬-𝐨𝐧 𝐜𝐨𝐝𝐞 𝐨𝐫 𝐭𝐮𝐭𝐨𝐫𝐢𝐚𝐥𝐬 𝐭𝐢𝐞𝐝 𝐭𝐨 𝐭𝐡𝐞𝐬𝐞 𝐬𝐭𝐚𝐜𝐤𝐬? 𝐃𝐫𝐨𝐩 𝐚 “𝐂𝐎𝐃𝐄” , 𝐚𝐧𝐝 𝐈’𝐥𝐥 𝐃𝐌 𝐲𝐨𝐮 𝐦𝐲 𝐀𝐦𝐛𝐢𝐞𝐧𝐭 𝐀𝐠𝐞𝐧𝐭 𝐬𝐭𝐚𝐫𝐭𝐞𝐫 𝐧𝐨𝐭𝐞𝐛𝐨𝐨𝐤𝐬. #AIEngineering #AmbientAgents #LangGraph #LangChain #HarrisonChase #AutoGen #CrewAI #n8n #LLM #EventDrivenAI

🚀 Day 2: Architecture & Tech Stack Decisions After framing the problem yesterday, today was all about designing how our Internal Docs Q&A Agent will actually work. 🔑 Key highlights: 1️⃣ Architecture Blueprint – Multi-agent workflow with Retriever → Context Builder → Answer Generator. 2️⃣ Tech Stack – Using LangChain + FAISS for semantic search, with connectors for Notion, Confluence & Google Docs. 3️⃣ Challenge – Ensuring speed while keeping answers contextually accurate. 💡 Biggest takeaway: Great AI agents aren’t just smart—they’re frictionless to use. 👉 Next step: Prototype the pipeline and test across sample docs. 🤔 Question for you: If you had an “AI teammate” for docs, what’s the first question you’d ask it? #AI #Hackathon #ProductSpace #AIAgents #FutureOfWork

The biggest mistake I see in tech projects? Jumping straight into building before understanding the people you’re building for. Whether it’s a front-end experience or an AI-powered feature, the technology is just the tool. The real magic happens when you first understand: - The people in front of you - Their needs, pain points, and workflow - How your expertise can remove friction and create real results That’s how I approach every project — whether I’m crafting a high-performance UI or integrating AI to make it smarter, faster, and more intuitive. Because when you truly “get” the person you’re helping, the solution almost builds itself. 💬 Here’s my challenge for you: In one word — what do you think most clients are really buying? Write that word in the comments, and I’ll reach out to schedule a free 30-minute call to explore how we can bring your next idea to life.

Lately, a big theme in my customer conversations has been future-proofing: creating a solid foundation for AI-assisted development and scaling engineering practices the right way. It’s been awesome to hear how teams are already thinking ahead and setting themselves up for what’s next. And right on cue, Forrester just dropped their latest Dev Mode report. If this is on your radar too, it’s worth a read - the impact is pretty eye-opening: ⏳ Developers saving 90+ minutes a week → 20–30% boost in efficiency 🚀 Faster design-to-code workflows → $2M in extra profit thanks to quicker time to market ✅ More consistency, accessibility, and brand alignment → lower business risk But here’s the fun part: it’s not just about the stats. Dev Mode is actually making life easier for developers, tightening the loop between design and engineering, and giving design systems way more punch. Exactly the kind of foundation that’ll make AI even more exciting (and useful!) for teams in the future. Access the report in comments below.

Don’t start with what’s possible . Start with what’s essential. In tech, possible is endless. You can build anything, 10 features, AI integrations, automation, analytics… But here’s the trap: Just because you can build it, doesn’t mean you should. When I work with founders, the first thing we do is strip the idea back to the core problem it’s solving. From there, we decide: → What’s essential for launch → What can wait → What’s not needed at all This does 3 things: ✅ Saves time and money ✅ Gives your team clarity ✅ Gets your product in front of users faster Because a focused launch isn’t just lean—it’s smart. If you’ve got 10 ideas and no clear starting point, we’ve opened one free consult slot a week to help founders and teams turn scattered ideas into an essential roadmap.

𝗡𝗲𝘄 𝗙𝗲𝗮𝘁𝘂𝗿𝗲 𝗮𝗹𝗲𝗿𝘁 𝗼𝗻 𝗙𝗶𝗻𝗱𝘆 𝗧𝗲𝗮𝗺+: 𝗚𝗶𝘁𝗛𝘂𝗯 𝗖𝗼𝗽𝗶𝗹𝗼𝘁 𝗥𝗲𝗽𝗼𝗿𝘁 AI tools like GitHub Copilot are everywhere, but most teams still lack visibility into how they’re actually being used across engineering orgs. With our new Copilot Report, engineering leaders can now: ✅See real usage across teams, not just license counts ✅Identify adoption gaps and understand where follow-up or training is needed ✅Spot internal champions driving usage and knowledge sharing ✅Track usage trends over time to measure the impact of enablement efforts Whether you're scaling AI adoption, planning renewals, or aligning your teams on tooling, this report gives you the clarity you’ve been missing. Start uncovering insights that drive smarter decisions. Want to know more? Reach out to us through the link in the comments!

🚀 Day 2 – Building SupportPulse Today, we made big progress on the frontend foundation of SupportPulse – our simple customer support dashboard. Here’s what we built: ✅ Sidebar Navigation – A clean menu to move between Dashboard, My Tickets, Search Tickets, and Create Ticket. ✅ Main Content Area – Different pages for ticket management: • Dashboard → See open, closed, and total ticket counts. • My Tickets → View assigned tickets at a glance. • Search Tickets → Quickly find tickets by ID, email, or subject. • Create Ticket → A form to log new issues with priority, type, and description. ✅ Single Page Application (SPA) – Pages switch smoothly without reloads. ✅ Mock Data Updates – Ticket stats update every few seconds to simulate real-time activity. Why this matters: Small businesses often struggle with clunky or expensive tools. With SupportPulse, we’re starting simple – giving teams a lightweight, easy-to-use support dashboard that makes their day easier. This is just the beginning – but every line of code takes us one step closer to reimagining customer support tools for small teams. ✨ Next up: Styling the UI and adding real backend integration. Stay tuned, more updates tomorrow! #SupportPulse #TechStartup #CustomerSupport #BuildingInPublic #StartupLife #AI

In construction, speed without accuracy leads to rework. But what if you could have both? With the right tools, your team can review code, catch issues, and move projects forward without second-guessing every sheet. That’s what working smarter looks like—fewer delays, more confidence, and time spent building, not backtracking. #LinkWaveAI #BuildSmarter #ConstructionTools #CodeCompliance #FasterReview #PlanCheck

🚀 30 days, one experiment: Could an AI browser actually boost my productivity as a PM? What surprised me most wasn’t just time saved, but how much smarter my workflow got. No bouncing between windows, no search fatigue. I got clearer insights, faster decisions, and real evidence at my fingertips—without losing focus or context. For anyone juggling research, docs, and constant feedback loops, this shift is a genuine game changer. #AIBrowser #Productivity #ProductManagement #CometBrowser #WorkSmarter #PMTools Perplexity #TechInnovation #AIWorkflow #DigitalTransformation #BrowserRevolution #EfficiencyHacks #ResearchTools #FutureOfWork #SaaSProductivity #AIForPMs #WorkplaceTech #comet #perplexity