joksan/joksan-test-repo

{
  "assistant": {
    "text": "Congratulations on considering integrating AI models into your existing automation workflows! The best approach depends on several factors, including the complexity of your automations, the type of AI models you want to integrate (e.g., machine learning, natural language processing), and the resources available for development. Here are some considerations to help you decide:\n\n**Option 1: Create a single AI app that leverages multiple tools**\n\nPros:\n\n* Centralized management and control\n* Easier integration with existing APIs and CLI execution\n* Potential for more efficient use of resources, as a single application can share knowledge and reuse code\n\nCons:\n\n* Complex development process, requiring expertise in AI, automation, and integration\n* May require significant retraining or rearchitecting of existing tools to accommodate AI needs\n* Can be overkill if only a subset of automations requires AI capabilities\n\n**Option 2: Create MCPs (Managed Control Platforms) with AI-enabled agents**\n\nPros:\n\n* Faster development and deployment, as you're building on top of existing infrastructure\n* Easier integration with existing workflows and tools, as you're working within the existing ecosystem\n* Allows for incremental adoption of AI capabilities, starting with specific use cases\n\nCons:\n\n* Requires multiple MCP instances or configurations to accommodate different automations and AI models\n* May lead to duplicated effort and complexity in managing and maintaining the infrastructure\n\n**Option 3: Hybrid approach**\n\nConsider a hybrid approach that combines elements of both options. For example:\n\n* Create a set of MCPs for specific use cases, each with an AI-enabled agent.\n* Use a central AI app (if necessary) or a secondary platform to handle complex AI tasks or integrate multiple tools.\n\n**Key considerations**\n\n1. **API and CLI execution**: Take advantage of existing APIs and CLI execution capabilities to minimize rework and leverage pre-built integration points.\n2. **Automation maturity**: Assess the maturity of your automations and workflows. If they're already well-established, using MCPs with AI-enabled agents might be a better fit.\n3. **Resource allocation**: Consider the resources available for development, testing, and maintenance. A single AI app may require more resources upfront, but an MCP-based approach can distribute these efforts across multiple projects.\n4. **AI model complexity**: Evaluate the complexity of your desired AI models. If they're relatively simple, a hybrid or MCP-based approach might be sufficient. More complex models may require a dedicated AI app.\n\n**Next steps**\n\n1. Identify specific use cases where you'd like to integrate AI capabilities and prioritize them based on business value and feasibility.\n2. Assess the existing infrastructure and tools, including APIs, CLI execution, and MCPs. Determine which ones can be leveraged or reworked for AI integration.\n3. Consider hiring external expertise (e.g., AI/ML engineers) or allocating internal resources to support the development of an AI app or multiple MCPs with AI-enabled agents.\n\nBy weighing these factors and considering your specific needs, you'll be able to choose the best approach for integrating AI models into your existing automation workflows.",
    "type": "message"
  },
  "context": {
    "endpoint": "127.0.0.1:11434",
    "provider": "ollama"
  },
  "created_at": "2025-12-26T10:57:03",
  "model": {
    "model": "llama3.2:3b",
    "provider": "ollama"
  },
  "schema": "gait.turn.v0",
  "tokens": {
    "by_role": {},
    "estimated": true,
    "input_total": 116,
    "output_total": 617
  },
  "tools": {},
  "user": {
    "text": "what is the best way to use AI models in conjunction with existing automations I have today? I have a bunch of scripts and workflows that could be accessed via API, CLI execution or perhaps via MCP that do various things like configure switch ports, provision cloud instances, modify routing policies, create new ipsec tunnels, send slack notifications, create change requests in servicenow, etc. What is the best approach for me to follow? Should I make a AI app that leverages all of them or should I just make them MCPs and create an agent with all those tools?",
    "type": "message"
  },
  "visibility": "private"
}