I was burning ~$50/week on my Claudebot and had NO idea where it was going. 😳 Did a full cost audit and found that 85% of my spend was either pure waste (heartbeats, context bloat) or tasks routed to models way too expensive for the job. Three layers of fixes changed everything: → Moved background processes to a free local model → Smart model routing (Haiku for routine, Opus only when needed) → Prompt caching + lean context files Weekly cost went from $50 → under $10. Same agent. Same capabilities. Just configured right. I put together a free guide with the full audit framework, config templates, and a step-by-step checklist 👇 🔗 https://www.notion.so/The-Complete-Guide-to-Running-Your-AI-Agent-Without-Burning-Money-300679d53e048009bdf5ef65c44580f6 Drop your current Claudebot costs in the comments — curious what you guys are seeing.

Hey all, just uploaded a new video! 95% of companies implementing AI are failing - not because the technology sucks, but because they're building their AI stack completely wrong. The Problem: MIT studied 300+ AI deployments - 95% are failing. Companies spending $35-40B but only 5% see revenue growth. Your AI doesn't talk to other systems, forgets everything between conversations, and every new tool needs a separate integration. The Solution: MCP (Model Context Protocol) MCP is like USB-C for AI - one protocol, infinite connections. Before: 5 AI tools + 10 business systems = 50 separate integrations With MCP: One connection, everything talks, your AI actually remembers and learns your business. How to Build It: I show you step-by-step using Zapier's new MCP integration - access 8,000+ apps without coding. Connect your entire stack (Gmail, Calendar, ClickUp, Slack, Notion, Stripe) through one MCP server, AI answers questions across all systems instantly. Watch the full breakdown:

Gemini 3 Pro Instantly Builds Voice AI Agents (This Changes Everything) Hey all, just uploaded a new video! Google's Gemini 3 Pro can now build fully functional voice agents in under 2 minutes with a single prompt - no code required. What I Built: One prompt created an entire medical clinic appointment scheduler - voice system, web interface, backend logic, everything. Professional voice handling patient calls, booking appointments, answering insurance questions, all powered by Gemini 2.5 Live. Why This Matters: Instead of spending hours building custom demos for prospects, spin up working voice agents in minutes tailored to their exact industry and share a live URL. Deploy to Google Cloud for demos or export to VAPI/Retell for production phone systems. The Real Shift: Technical barrier is approaching zero - anyone can build demos now. The competitive advantage is understanding business problems, calculating ROI, and delivering measurable results, not just technical skills. Building is the easy part, strategic consulting is where real value lives. What industry are you targeting with voice agents? Watch me build a complete healthcare scheduling agent here

Anthropic just dropped something that changes everything about building AI agents in production. Read the full breakdown here: https://www.anthropic.com/engineering/code-execution-with-mcp If you've been using Model Context Protocol (MCP), you might've noticed: - Agents hallucinating more than they should - Token costs spiraling out of control - Workflows breaking when they hit context limits Here's the truth: It's not because MCP is broken. It's because everyone's using it wrong. The Problem with Traditional MCP: When you connect multiple MCP servers (Gmail, Slack, CRM, databases), ALL tool definitions dump into your agent's context window immediately. Example: 6 systems with 15-20 tools each = 100+ function definitions loaded before the agent even reads what you want it to do. What this causes: - Tens of thousands of tokens just sitting there - Higher costs, slower responses - Agent gets confused and makes mistakes - 40,000 token documents flowing through context multiple times The Solution: Code Execution with MCP 2.0 Instead of presenting MCP tools as function calls, present them as a file system the agent explores. How it works: - Each MCP server = a folder - Each tool = a TypeScript file - Agent searches, finds what it needs, writes code to use specific tools - Results stay in sandbox OUTSIDE agent's context - Only final processed results (500 tokens vs 40,000) go back to agent Why this is massive: AI models are trained on millions of lines of code during pre-training. Tool calling is learned during post-training with way less compute. When agents write code to interact with MCP servers, you're leaning into what they're naturally exceptional at. Bottom line: Stop obsessing over which tool is "best." Ask which approach solves your specific client's problem most efficiently. This is what separates people who make real money from people who just collect tools. What are you building with MCP? Drop it below.

Hey everyone! I want to make sure you're squeezing every bit of value out of being here. This isn't just another group where you watch content and disappear—it's a place where you can actually accelerate your growth. Here's what you should be taking advantage of: 📌 Personalized Feedback Stuck on a workflow? Can't figure out why your automation isn't working? Drop it in the community. I personally review posts and give direct feedback to help you break through blockers. 📌 Vote on Next Video Topics You get to decide what I build next. If there's an automation you need or a tutorial that would help your business, tell me. The community votes, and I create it. 📌 Access to Templates & Resources Everything I build gets shared here first—n8n workflows, prompts, scripts, client templates. You get the goods before anyone else. 📌 Real Client Project Insights I share what's working in real deployments with actual clients. You get to see behind the scenes of $10K+ projects and learn what actually converts. 📌 Accountability & Momentum Post your wins, share your progress, ask questions. This community moves fast, and being active keeps you moving forward instead of getting stuck in tutorial hell. 📌 Networking & Collaboration Connect with other builders, share leads, collaborate on projects. Some of the best opportunities come from the people in here. So here's my question for you: What else do you want to see here? What would make this community even more valuable for you? Drop your thoughts below. Let's make this the best place to build your AI agency. Let's go! 💪