{
  "identity": "https://rsnair.tech/#rohit-nair",
  "projects": [
    {
      "id": "codeguardians",
      "name": "CodeGuardians",
      "description": "Ford's multi-agent code-review platform.",
      "contribution": "Architecture, retrieval, tooling, and infrastructure, described at a confidentiality-safe level.",
      "evidenceClass": "sanitized-professional",
      "sourceUrl": "https://github.com/rnair98",
      "competencyIds": [
        "agentic-systems",
        "code-intelligence",
        "retrieval-context",
        "llm-evaluation-observability",
        "ai-infrastructure"
      ]
    },
    {
      "id": "swe-term",
      "name": "swe-term",
      "description": "A terminal SWE-agent harness whose Go core owns the agent loop while heavy engines run as sidecar binaries.",
      "contribution": "Designed and built the agent loop, protocol and event model, TUI, and policy-gated approval boundary.",
      "evidenceClass": "public-artifact",
      "sourceUrl": "https://github.com/cercova-studios/swe-term",
      "competencyIds": [
        "agentic-systems",
        "code-intelligence",
        "llm-evaluation-observability"
      ]
    },
    {
      "id": "kairos",
      "name": "Kairos",
      "description": "A contextual bandit for bookmark surfacing that learns when to interrupt, not only what matches.",
      "contribution": "Designed and built the retrieval, context, policy-learning, evaluation, observability, web, and MCP surfaces.",
      "evidenceClass": "public-artifact",
      "sourceUrl": "https://github.com/rnair98/kairos",
      "competencyIds": [
        "retrieval-context",
        "llm-evaluation-observability",
        "ai-infrastructure"
      ]
    },
    {
      "id": "obsidian-agent",
      "name": "Obsidian Agent",
      "description": "A LangGraph research pipeline that turns a topic into a report, atomic notes, and durable memories through sequential agents.",
      "contribution": "Designed and built the agent workflow, persistence boundary, API, container stack, and observability integration.",
      "evidenceClass": "public-artifact",
      "sourceUrl": "https://github.com/rnair98/obsidian-agent",
      "competencyIds": [
        "agentic-systems",
        "retrieval-context",
        "llm-evaluation-observability"
      ]
    },
    {
      "id": "antisomnus",
      "name": "Antisomnus",
      "description": "A real-time driver-fatigue detection pipeline using face landmarks and CNN embeddings, deployed on GCP with a Flutter client.",
      "contribution": "Built the detection pipeline, model, GCP deployment, and client described in the public repository.",
      "evidenceClass": "public-artifact",
      "sourceUrl": "https://github.com/The-Rockers/DriverDrowsinessDetection",
      "competencyIds": []
    }
  ]
}