Most people are using AI agents for coding now — but their agents are still missing the upgrades that make them genuinely useful in real workflows. This video breaks down the five upgrades I personally use to make my AI agents smarter, more reliable, cheaper to run, and much easier to manage across my team. We’ll start by quickly clearing up the difference between plugins, skills, and MCP servers, then dive into the exact tools that level up your agents: fresh documentation with Context7, better engineering workflows with Superpowers, live web access through DataImpulse, structured task management with Linear, and long-term memory through Obsidian. I’ll show you how each one fits into an actual AI agent workflow, how to install or connect them inside tools like Cursor, Claude Code, Codex, OpenClaw, and Hermes, and why these upgrades matter if you’re trying to move beyond basic prompting into proper agent-powered productivity. We’ll cover: ✅ The difference between plugins, skills, and MCP servers ✅ Why plugins should usually be the first thing you look for ✅ How Context7 gives your agents fresh, version-specific documentation ✅ How Superpowers adds proper software development processes to your agents ✅ How DataImpulse helps agents access live public web data through residential proxies ✅ How to install and use the free DataImpulse MCP ✅ Why Linear becomes a control center for AI agent workflows ✅ How Obsidian can act as a shared second brain across all your agents ✅ How OpenClaw and Hermes can use Obsidian as a native memory layer If your agents still feel limited, forgetful, or inconsistent, these five upgrades will help you turn them into a serious workflow that can research, plan, build, track work, and remember what happened across sessions.

Episode 12 of our new Series 'Code with AI the Right Way' is here! — and this time, we're building a Zendesk / Intercom clone LIVE from scratch! (It even includes AI Agents and B2B Billing!) 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.