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FDEOps

Your AI coding agent forgets your client every morning. fdeops remembers.

npm version CI License: MIT Node

One @fde skill over a local client notebook (the fieldbook under .fde/) - one folder per client. The system of record for embeds - Forward Deployed Engineers and anyone living on a client site from first meeting to handoff. Feels like a second brain; behaves like a defensible record (dated, sourced, yours). Works the same for consultants, agency developers, solutions architects, and fractional CTOs.

  land      discover      plan      build      ship      close
    |           |           |         |          |         |
    +-----------+-----------+---------+----------+---------+
          the fieldbook (.fde/) - one per engagement
             written as a side effect of the work

You talk in plain language with @fde. The agent (and an optional CLI) handles the boring memory work. You still confirm anything that goes into the record.


The week

Day to day you only need @fde and normal English. No command cheat sheet.

When What you say What you get
Start of week Open your AI coding agent (nothing to paste) It already knows where you left off - trust, phase, what's next
After a meeting @fde debrief these notes (paste or attach them) Proposed updates to the record - you review, then confirm
Before a stakeholder meeting @fde prep me for tomorrow's meeting with the sponsor A short brief from what you already logged - not a blank chat
Someone disputes scope @fde when did we agree to drop that feature? Dated answers from the record (or a clear gap if nothing was logged)
End of week @fde draft the sponsor update from the record Status grounded in what actually happened

Same client folder every time (~/fde-engagements/<client>/.fde/). Your AI coding agent reads it on every session.


Quickstart

1. Install (pick one)

npx skills add suboss87/fdeops          # Cursor, Codex, and skills-compatible agents
/plugin marketplace add suboss87/fdeops # Claude Code
/plugin install fdeops@fdeops

2. Bind once - inside the client workspace (setup only; not a daily habit):

npx fdeops resume --init garvey   # creates ~/fde-engagements/garvey engagement + binds workspace

Check it worked:

npx fdeops resume                 # prints a short "where we are" for this client

3. Work - talk normally:

@fde I just got the brief. New client, payments platform, they want it live before their Q3 audit.

@fde routes and updates the fieldbook - you confirm judgment. Full workflow: docs/USAGE.md.

Other install paths · scan · env
  • Cursor / Codex / Copilot / Gemini CLI: npx fdeops adapters . - adapters/
  • Local LLMs (Ollama, LM Studio, llama.cpp): load skills/fde/SKILL.md as the system prompt - guide
  • Manual / air-gapped: git clone https://github.com/suboss87/fdeops.git && cd fdeops && node bin/install.js
  • Try without install: npx fdeops scan - day-1 recon (heuristic leads, not findings)
  • Requires: Node.js >= 18 for the CLI and adapters
  • Advanced: FDEOPS_ENGAGEMENT overrides the workspace registry. Full matrix: docs/install.md

How it works

  • You describe the situation with @fde (or plain language once the skill is loaded)
  • Session start / end - small hooks load where you left off and capture what changed (no re-paste)
  • Local CLI - memory writes, search, and status with no model tokens; the agent runs it. You do not need to learn it for daily use (docs/USAGE.md)

fdeops complements repo memory: CLAUDE.md holds how the code works; the fieldbook holds how the client engagement works.

Works with Claude Code · Cursor · Copilot · Gemini CLI · Ollama · LM Studio - any model that reads markdown.

Phase verbs (land → close)
Verb When
land First days at a new client - interrogate the brief, map stakeholders, define success
discover The brief feels wrong - find the real problem, with evidence from the repo
plan Scope agreed - sequence it backwards from success, in PR-sized slices
build Ready to write code - declare blast radius, log deliveries as you ship
ship Going to production - pre-flight, canary, tested rollback
close Engagement ending - handoff doc, retrospective, receipts that survive you

Overlays for regulated domains (AI, fintech, healthcare, government) activate on signal. Full matrix: docs/skills.md.


Engagement memory (.fde/)

The fieldbook is the system of record for the embed - one folder per client, plain markdown you can read, grep, and take with you:

File Holds
context.md Where you are - loaded first every session
brief.md / success.md What they asked for; what "done" means and who signs it off
reality.md / terrain.md The real problem; the codebase map
stakeholders.md Champions, resistance, [signal:green|amber|red] trust tokens
trust-profile.md Sacred data, AI policy, approval chain
decisions.md / risks.md / delivery.md Choices with dates; live risk register; what shipped and its rollback

Every entry is dated and sourced, so you can defend it in front of skeptical stakeholders. Schema: docs/schema.md.


Fieldbook UI

Open the system of record in a browser - trust, phase, next action, and the full record in one local page. Ask @fde for the dashboard, or run npx fdeops dashboard (current engagement by default; --all for the portfolio).

fdeops Fieldbook in the browser


Who this is for

You are... What fdeops does for you
Forward Deployed Engineer The role this was built for - the full lifecycle, first meeting to final handoff
Consultant or contractor at a client site Remembers the engagement so you stop re-explaining it
Solutions architect / engineer Methods for the politics as well as the architecture
Agency developer running 3-5 clients One .fde/ per client - details stop blurring
Fractional CTO doing client work The fieldbook is your system of record for the embed - and your audit trail for billable work

Your data stays yours

  • Local only. Pure git + file reads - no network calls, no telemetry, no account. Works air-gapped.
  • Plain markdown. No database, no lock-in.
  • No new data path. The AI sees client code only when you point your agent at it; <private>-tagged data never enters the model's context.
  • Nothing enters the record unreviewed. The model drafts, you confirm (fde debrief --dry-run shows the routing first); the hooks record only git facts. Your fieldbook stays yours to defend.
  • Know your sync surface. ~/fde-engagements lives in your home directory - your backup and cloud-sync setup now covers client notes. fde resume --init warns if the folder sits in a synced path. Read PRIVACY.md before your first NDA'd engagement.

Details: PRIVACY.md · SECURITY.md


Principles

  • The artifact is the memory - producing work and recording it are one action
  • Methods, not autonomy - each skill tells you what to check; the judgment, the trust, and the consequences stay yours
  • Brief is a hypothesis - discover before building the wrong thing
  • Evidence on every claim - these files get defended in front of skeptical clients
  • One customer, one folder - context never bleeds

Updating

# Plugin / skills install: re-run the install command from Quickstart
# From a git clone:
cd fdeops && git pull && node bin/install.js

Contributing

Built and maintained by Subash Natarajan. Share your feedback via Issues - see CONTRIBUTING.md.

FDE Methodology - ATTRIBUTION.md - SECURITY.md - PRIVACY.md - Repo layout - Skills matrix - MIT

About

Second brain for Forward Deployed Engineers. Engagement memory + 35 skills across 6 domains, all behind one @fde... Works with any AI coding agent.

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