For years, automation meant dragging nodes in tools like n8n, Make, and Zapier. Connect this → map that → handle errors → pray nothing breaks. It worked.But it was fragile. One API change. One unexpected response. And your entire workflow collapses. That’s traditional automation. Now we’re entering something different: 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬 Instead of wiring every step manually, you define the goal and the agent figures out the steps. Recently, I built an autonomous AI News Agent using Antigravity, leveraging Claude Opus 4.6 for natural language agent control and Gemini 2.0 Flash for automated news summarization within structured pipelines.The difference was obvious. I didn’t: • Manually define every integration • Hard-code every edge case • Write defensive logic for every possible failure Instead, I defined the outcome: “Every morning at 9AM, fetch important AI news and send me a clean briefing to my Gmail inbox” The agent handled: Research Filtering Formatting Error handling 𝐖𝐡𝐲 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬 𝐖𝐢𝐧 Here’s what makes them fundamentally different: • Outcome-driven, not step-driven: You define what needs to happen. The system decides how. • Self-adaptive: If something changes (API, format, response), the agent can adjust instead of crashing. • Less manual debugging: The agent can interpret errors and fix issues without you rewriting the entire flow. • Faster to build: No more wiring 20 nodes. One directive can replace an entire visual workflow. • Scales better: As complexity grows, you don’t get a spaghetti mess of connections. • You focus on thinking, not plumbing: Your value shifts from wiring tools to designing intelligent systems. Traditional tools (n8n, Make, Zapier):You design the steps. Agentic workflows:You design the outcome. That shift changes everything. Instead of being a builder wiring nodes,you become an architect defining intent. Automation was about workflows. Agentic systems are about intelligence. And this shift is just getting started.

Hi everyone! I am Suzan. I just joined this community, and I am excited to learn so that I can utilize AI more to improve my Skool community.

After building multiple MVPs with Lovable, I realized something important: Building MVPs is no longer limited by coding skills. It’s limited by how clearly you define the product. AI can build almost anything. But only if you give it the right structure. Here’s the exact framework I follow: 1. Start with real problems I don’t start with ideas. I start with problems. I explore Reddit, Discord, and YouTube comments to see what people are struggling with. This helps ensure I’m building something useful and relevant, not just something interesting to me. When the problem is clear, everything else becomes easier. 2. Create a clear blueprint using a PRD prompt Before building, I use Lovable to generate a PRD (Product Requirements Document). This helps define: - Pages and routes - User flow - Core features - Product structure This step is critical. It acts like a roadmap and removes confusion during development. Without structure, AI produces inconsistent results. With structure, it produces production-ready output. 3. Build the skeleton first Next, I generate the basic UI structure: - Layout - Navigation - Pages I don’t worry about features yet. The goal is to create a clean foundation that can be extended easily. 4. Add features incrementally I add one feature at a time using focused prompts. This keeps the system stable and easier to debug. It also helps Lovable produce more accurate results. Trying to build everything at once usually creates messy output. Incremental building works much better. 5. Add authentication Once the core product works, I add authentication using Supabase. This includes: - Login and registration - Password reset - Email verification - Protected routes This makes the product ready for real users. 6. Deploy and iterate Finally, I deploy the product. You can deploy directly from Lovable or connect GitHub and deploy via Vercel or Netlify. Once live, I improve the product based on real usage and feedback.

Hey everyone 👋 I’ve been building something over the last few weeks and finally excited to share it here. Prolink is a simple way to showcase everything you do — projects, links, tools, and your professional story — all in one clean page. No clutter. No endless scrolling. Just what matters. Instead of sending multiple links (resume, GitHub, LinkedIn, projects), Prolink lets you share one clean, professional link. ✅ Projects with context ✅ Skills + tools ✅ Resume, GitHub, LinkedIn — all in one place ✅ Mobile-friendly & recruiter-ready 🔗 Try it here: https://oneprolink.lovable.app Built for job seekers, creators, and professionals who want a better first impression. Would love quick feedback from this community 👇Happy to share access if anyone wants to try it.

Honestly, this isn’t just a badge. It reflects the time spent learning how to actually work with AI, not just use it. We’re entering a phase where the skill isn’t about writing every line of code — it’s about: • Prompting clearly • Thinking in systems • Iterating fast • Shipping faster than ever This is what people are calling Vibe Coding — and it’s quickly becoming a core skill for builders, PMs, and engineers. I’ve personally seen how tools like Lovable, Claude, and Cursor can turn ideas into real products in hours instead of weeks. Curious to know — Are you vibe coding yet? And if yes, what’s your current level? 👇 Let’s discuss.