Episode 6 of our new Series 'Code with AI the Right Way' is here! — and this time, we're vibe coding a Image & Video Studio LIVE from scratch! This is a LIVE build — mistakes, debugging, and all. That's the point. You learn more watching someone solve real problems in real-time than from a polished, pre-recorded tutorial.

Most products have data, but no real insights. Modern dashboards should: → track real-time metrics (MRR, churn, activity) → detect issues automatically → help you decide what to do next I build these systems end-to-end — backend, data models, AI insights, and UI. If your analytics feels messy or unclear, I can help fix it. DMs open.

Most AI agents don’t actually improve over time — they just repeat the same workflows, accumulate noisy memory, and slowly get worse unless you constantly step in to refine them. This video breaks down the real differences between OpenClaw and Hermes Agent, so you can decide whether it’s worth switching entirely, sticking with OpenClaw, or running both side by side. Hermes Agent is getting attention because of its built-in self-learning loop — it can observe repeated workflows, turn them into reusable skills, and iteratively improve them over time. OpenClaw, on the other hand, shines with its rich ecosystem, multi-agent communication, and more flexible orchestration setup. I’ll show you exactly how both systems differ when it comes to self-learning, memory, skills, tool usage, and multi-agent architecture — and then I’ll walk you step-by-step through setting up your own Hermes Agent on a VPS with Hostinger, including Telegram bot setup, running the gateway in the background, and testing the self-learning workflow for yourself. We’ll cover: ✅ The real difference between OpenClaw and Hermes Agent ✅ Why Hermes Agent's self-learning loop is the biggest differentiator ✅ How memory works differently in both systems ✅ Why OpenClaw still wins for true multi-agent communication ✅ How I’m personally using both agents together ✅ One-click Hermes Agent deployment with a Hostinger VPS ✅ Telegram bot setup, gateway config, and background execution ✅ Why running AI agents on a VPS is safer than your local machine If you’re serious about building AI agents that are always on, safer to run, and actually useful in the real world, this video will save you a ton of trial and error.

I’d like to share my experience building various automation systems and bots across different platforms. I have worked on developing and managing bots for platforms such as Discord, telegram, Slack, and email automation systems. These bots are designed to automate repetitive tasks, improve communication, and streamline workflows for communities and businesses. Automation can provide several advantages, including: • Reducing manual work through automated processes • Providing instant responses and support to users • Tracking activities and generating useful data • Integrating multiple platforms and services together • Improving efficiency and scalability for growing communities In my work, I use technologies such as API integrations, backend scripting, workflow automation, and AI-assisted logic to build reliable and scalable bot solutions. Examples of automation I’ve built include: • Discord bots for community management, moderation, and automation • Slack bots for internal team workflows and notifications • Email automation systems for marketing and user engagement • Integration bots that connect different platforms and services If you need my help plz let me know feel free time

Hello! everyone! I build AI & full-stack systems that solve real world problems in a clear, transparent, and seamless way. I don’t chase hype I focus on shipping software that delivers real value and improveas efficiency, accuracy, and user experience. AI & Machine Learning LLM integration + RAG pipelines (hybrid search + custom retrieval) Workflow automation with AI-driven tools (Slack, Notion, internal APIs) AI content detection & moderation (stylometry, embeddings, fine-tuned transformers) Image AI: tagging, moderation, object detection (CLIP + YOLOv8) Multi-agent systems (planning, tool use, reflection loops) Bot development: trading bots, Discord bots, intelligent task automation Full-Stack Development Web: React, Next.js, Node.js, Laravel, Django Mobile: Flutter, React Native, Swift Databases: relational + NoSQL design & management Backend: API design, microservices architecture, scalable services Frontend: UX/UI design + performance optimization Real-time systems: event-driven architecture + live data pipelines Cloud/DevOps:: AWS, Azure, Docker, Kubernetes Building clean, maintainaable, and secure systems that scale and perform under real-world conditions. If you want to ship something solid (not just a demo), feel free to reach out anytime.