Building at the intersection of market infrastructure, programmable finance, and AI systems

{
  "schema": "https://magro.dev/agent.json",
  "schemaVersion": "0.1",
  "site": {
    "name": "Daniel Magro | Market Infrastructure, Programmable Finance, AI Systems",
    "url": "https://magro.dev",
    "description": "Former institutional rates and macro trader and portfolio manager building systems at the intersection of market infrastructure, programmable finance, and AI agents. Thirteen years in liquidity, collateral, execution, and risk, paired with hands-on work in Go, Solidity, Ethereum infrastructure, APIs, and agent systems.",
    "owner": {
      "name": "Daniel Magro",
      "email": "dan@magro.dev",
      "role": "Former institutional rates and macro trader and portfolio manager building market infrastructure, programmable finance, and AI agent systems"
    }
  },
  "agentMode": {
    "endpoints": {
      "overview": "https://magro.dev/agent/",
      "manifest": "https://magro.dev/agent.json",
      "router": "https://magro.dev/llms.txt"
    },
    "principles": [
      "Canonical human context lives on magro.dev.",
      "Agent-facing context should be structured, stable, citation-aware, and low-noise.",
      "GitHub/code links are attached only when they make the argument stronger.",
      "The portfolio is positioned around market infrastructure, programmable finance, and AI agent systems, built on thirteen years of institutional trading and portfolio management experience."
    ]
  },
  "projects": [
    {
      "title": "Rollup Mechanics Lab",
      "slug": "eth-l2",
      "tier": "primary",
      "summary": "Interactive rollup mechanics lab comparing optimistic fraud proofs (/op) with a simplified, mock validity-verification path (/zk) that stands in for a succinct ZK proof. UI on Vercel at eth-l2.vercel.app; live simulation via a staging Go backend through Cloudflare Tunnel."
    },
    {
      "title": "Ethereum Transaction Lifecycle Visualizer",
      "slug": "eth-tx-lifecycle",
      "tier": "primary",
      "summary": "Full-stack visualization of what happens between clicking send and a transaction becoming irreversible: execution and consensus layers, MEV, builder auctions, and finality. UI on Vercel at eth-tx-lifecycle.vercel.app; live data via a staging Go backend through Cloudflare Tunnel."
    },
    {
      "title": "Agent Runtime",
      "slug": "agent-runtime",
      "tier": "primary",
      "summary": "An interactive single-page walkthrough of a tool-using agent runtime: platform input, session hydration, the agent loop, tool dispatch, and persistence, made observable step by step with ASCII art diagrams."
    },
    {
      "title": "AI Infrastructure Financing",
      "slug": "ai-physical-infra-debt",
      "tier": "primary",
      "summary": "Interactive research report on GPU-backed term loans, data-center securitization, and the funding channels that turn an AI capex slowdown into a credit event. Provenance-tagged figures, recovery model, and Agent Mode exports."
    },
    {
      "title": "Hermes X-Ray",
      "slug": "hermes-xray",
      "tier": "primary",
      "summary": "A standalone browser observability lab inspired by Agent Runtime: enter a simple prompt and inspect model-visible context, loop stages, tool events, token estimates, verification, and persistence boundaries."
    },
    {
      "title": "Portfolio Agent Mode",
      "slug": "portfolio-agent-mode",
      "tier": "primary",
      "summary": "A minimal agent-readable layer for magro.dev: /agent for humans, /agent.json for structured context, and /llms.txt as a low-noise router for AI systems."
    },
    {
      "title": "Ethereum RPC Monitor",
      "slug": "eth-rpc-monitor",
      "tier": "primary",
      "summary": "Ethereum JSON-RPC monitoring CLI with block inspection, mempool snapshots, and real-time transaction tracing."
    },
    {
      "title": "AMM Simulation Engine",
      "slug": "eth-amm-sim",
      "tier": "primary",
      "summary": "AMM and EVM mechanics lab: impermanent loss under volatility regimes, fee accrual, concentrated liquidity, and fixed-point math modeled the way a rates trader would run scenarios. UI on Vercel at eth-amm-sim.vercel.app; live simulation via a staging Go backend through Cloudflare Tunnel."
    }
  ],
  "writing": [
    {
      "title": "Is the AI Infrastructure Buildout a Bubble? A Fixed-Income Trader's Read",
      "slug": "ai-infrastructure-buildout-bubble"
    },
    {
      "title": "The Magic Box, Part I",
      "slug": "the-magic-box"
    },
    {
      "title": "Agent Mode and the Inference Tax",
      "slug": "agent-mode-and-the-inference-tax"
    }
  ],
  "research": [
    {
      "title": "AI Infrastructure Financing: State of the Market",
      "slug": "ai-infrastructure-financing"
    },
    {
      "title": "The 2050 Economy: A Structural Forecast",
      "slug": "the-2050-economy"
    },
    {
      "title": "The Octopus as an Architectural Model for AI, Agents, and Agentic Systems",
      "slug": "octopus-agentic-systems"
    }
  ]
}