Stop reading. Brief me.
This page is a working Forward Deployed Engineer simulation. Give me your real, vague, messy problem. I'll perform the FDE "decomposition" interview on it live: scope it, draw the architecture, plan the sprint, and call out where it'll fail. Then map every phase back to projects I've actually shipped.
/02 · RECEIPTS
The simulation above isn't vibes. Here's the engineering substrate it runs on.
Four proofs of the engineering breadth FDE work actually needs: agents, protocols, upstream code, distributed substrate.
Vague spec -> working multi-agent in 10 days.
Five-agent LangGraph research system, built from a rough problem statement. Hexagonal architecture, verification loops, local + cloud LLM fallback.
Made my own site agent-queryable via W3C WebMCP.
8 tools in production. Early implementation on the exact surface OpenAI / Anthropic / Google FDE postings now call table-stakes.
Walked into unfamiliar code and left it better.
A merged PR into the Anthropic MCP Python SDK. Also navigated vLLM (200k+ LOC) for a separate investigation. The exact muscle FDEs use in customer code.
Services, data flows, contracts, failure boundaries.
Kayak: 3-tier distributed architecture. Node/Express services behind API gateway, polyglot persistence (MySQL/Mongo/Redis), Kafka, FastAPI AI layer. Airbnb on Kubernetes microservices.
/03 · CANDID
Notes on fit.
The version where I'm honest about what I can claim, and what I can't. Yet.
What I can credibly claim
The engineering substrate: agentic systems, protocols, upstream code, distributed services. The decomposition muscle the simulation above demonstrates.
Plus real stakeholder-facing delivery experience: requirements alignment, metric and SLA definition with finance and operations at Elite Hotel Group.
What I haven't yet
The full FDE customer lifecycle in an external environment. Internal stakeholder delivery isn't the same as external customer delivery. I won't pretend otherwise.
I'm actively closing this by shipping one small real deployment, publishing failure analyses, and converting an existing project into a deployment case study. Specifics on request.
If the simulation made you think, say so.
Fastest path: email. I read every one. If you ran the sim on a real problem and it sparked an idea, send me the brief and I'll show you what the next 30 minutes of work would look like.