Hi Everyone, These past two weeks, I've been super busy figuring out a few things and testing the Chimera enhancements. I’ve also been working on starting to materialize a project I’ve been going back and forth on for months. Virtual Agents. I’ll explain more in the future, but basically, I’m trying to create a personalized set of agents—each of them working either individually or as part of a team—aimed at achieving specific business process automations. The idea is to build a catalog of virtual agents that you can almost template-ize and offer to businesses directly from a catalog. This will require quite a lot of work, but I believe the potential, once it’s done, is pretty high. My plan is to not only offer these myself, but also make them available to other AI practitioners like you—so you can re-sell these agents without having to build them yourself. They would have proven reliability and be tested in real business cases. Would this be something you’d be interested in? For example, being able to offer robust AI solutions and automations without having to build them from scratch?

How did I start with AI? What was my wake-up point (with no return)? Let me tell you my story and how I got where I am. The first time I started with GPT was around summer 2021. At first, I thought it was super cool, but really nothing more than Google search on steroids. I used it here and there for simple stuff, like "write me a song about XYZ" or "tell me where XYZ comes from" or "what can you tell me about XYZ", nothing life-changing, but you could already see some potential. Slowly, I started to push what you could do into more useful territory. I began using it within my work to help me write security scripts for vulnerability management and help me understand more technical concepts. It was brilliant at it, and back then it was already giving me an edge over all my colleagues who weren't using it. Gradually, I started using it more and more for my day-to-day activities – helping me write emails, develop security policies, define implementation roadmaps, etc. At this point, it was becoming a key tool for my daily work. I felt this tool was giving me superpowers. I could do the work of 5 different IT and Cybersecurity experts, all on my own. But still, this was not my breaking point. This was October 2023, and the moment of truth was around the corner. November 2023. This was it. OpenAI released something that changed me forever: GPTs. Until then, ChatGPT was an isolated tool for me, super useful, but I couldn't take it out of there to use it for my own specific needs. Not until then. With GPTs, OpenAI gave everyone the opportunity to take this amazing technology and transform it into something fit for their specific needs. From that day, you could create a team of specialist agents capable of being trained on any subject you wanted, with specific instructions to deliver specific outcomes. But why was this a game changer for me? Because this was the first time I realized the impact this technology was about to have on EVERY SINGLE BUSINESS out there. Now I could build teams of specialists, feed specific knowledge documents, specific to a company or even specific to a team within a company, and train them to deliver outcomes that would've taken hours or even days for a human to prepare.

Chimera architecture aligns remarkably well with what Anthropic has now built natively into Claude Code. Key Differences: What Chimera Has That Sub-Agents Don't (Yet) >Global persistent memory across projects via SQLite database >Cross-project learning and knowledge transfer >Automatic learning extraction and pattern synthesis >User preference tracking and adaptation over time >Complex orchestration with batch execution and parallel workflows What Sub-Agents Provide That Your System Lacks >Native integration with Claude Code's tool ecosystem >Automatic task delegation based on context matching >Separate context windows for each agent (prevents context pollution) >Built-in agent management via /agents command >MCP tool integration and granular permissions >Team sharing capabilities through version control My Migration Strategy: Hybrid Approach Rather than completely replacing Chimera, I will re-build a hybrid evolution that leverages the best of both approaches: Phase 1: Convert Specialist Agents to Sub-Agents format while preserving their memory capabilities. New File Structure: text .claude/├── backend.md # Native sub-agent format │ ├── designer.md # Native sub-agent format │ ├── datasci.md # Native sub-agent format │ ├── qa.md # Native sub-agent format │ ├── secure.md # Native sub-agent format │ ├── devops.md # Native sub-agent format │ └── ... (all specialists) ├── commands/ # Keep for orchestration │ ├── orchestrate.md │ ├── executor.md │ ├── learner.md │ └── memory_init.md Expected Benefits Immediate Gains: - Native tool integration and MCP compatibility - Automatic task delegation reduces manual orchestration - Separate context windows prevent context pollution - Built-in team sharing through .claude/agents/ versioning Long-term Advantages: - Hybrid intelligence combining native efficiency with learned wisdom - Cross-project knowledge transfer with modern delegation - Scalable architecture that grows with Claude Code's evolution - Future-proof design that adapts to new sub-agent capabilities

Firsts run with my new Chimera v2.0 Claude Code Swarm system. This thing is magic. Seeing how everything is orchestrated autonomously in front of your eyes is really mesmerizing. And powerful. I have a team of software developers working for me. I just ask them what I want to build and confirm executions. That's all. Everyone can have a team of developers working for yourself today, building ANYTHING you want. This is the present, not the future.

Does anyone have any good resources on understanding how to build our own MCPs? Where do I start? Are there specific tools, or is that something Claude Code can help with?