🚀 The definitive roadmap to becoming a Forward Deployment Engineer (FDE). Master AI Agents, Enterprise Data Architecture, and Strategic Consulting. Bridging the gap between HQ and the field. Inspired by the "Delta" role at Palantir, OpenAI, and Scale AI.
Second brain for Forward Deployed Engineers: engagement memory + execution skills across discovery, delivery, and handoff.
Forward deployed engineering guide for production AI systems: value, architecture, evals, security, deployment, and operations.
This repository serves as the comprehensive workspace for Quarter 4-5 academic endeavors, encompassing assignments, technical documentation, experimental implementations, and applied projects.
AI-driven R&D workflow framework: 8-step SDLC, hard gates, @rules traceability chain. Bilingual (EN/ZH).
opinionated tools for shipping AI into real-world domains
AI-assisted local-first reference prototypes for governed AI application controls, using fictional data and explicit evidence boundaries.
Agent-native, open-source deployment tooling for those who want to deploy better
ArcKit Forward Deploy Engineering (FDE): embedded architecture engineering for UK public sector programmes. £25K/week first sprint with Green Book, Orange Book, GDS and TCoP evidence alignment.
Claude Code skill pack for forward-deployed engineers — customer context, discovery, scope, value framing, POC, integration. Git-backed, no service deps.
AI-powered FDE platform for customer deployments, RAG, secure integrations, human-in-the-loop workflows, evaluations, and observability.
This is a memo about AI FDEs based on my observations and experiences written with agentic AI support.
how AI-native companies can build composable per-customer software
LLM agent observability framework trace every step, eval every output with LLM-as-judge, alert on quality drift. Built for forward deployed engineers.
Privacy-safe forward-deployed engineering skills for Claude Code, Codex, and AGENTS.md-compatible agents
A practical, book-style field guide for Forward Deployed AI Engineers covering LLMs, production RAG, agents, LangGraph, evaluation, LLMOps, security, code examples, and interview preparation.
Fieldwork by Ryan Baumann: developer tools, Field Notes, working Labs, and agent evals.
Employer-facing portfolio for AI implementation: discovery, architecture, evals, auditability, rollout, and customer handoff.
Open, evidence-backed AI skills for forward deployed engineering engagements. Contributions welcome.
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