FDEOps

Skills for forward deployed engineers, used through your AI coding agent.

FDEOps helps you turn a customer problem into a working system: clarify the goal, choose an architecture, build and integrate, then verify the result and prepare for rollout.

Use a task skill on its own, or let fde coordinate work across strategy, architecture and engineering. Customer memory keeps decisions, evidence and next steps available between sessions.

I built FDEOps around design thinking, first-principles thinking and systems thinking: understand the people doing the work, question assumptions, and examine how a change affects the whole system. I turned my field approach and experience into skills that help your AI coding agent investigate, build and verify, with customer memory to carry the work forward.

Get started · What it helps with · Choose a skill · Data boundaries · Docs

Quick start

Let fde coordinate a customer project

Install in the terminal where your AI coding agent runs, then select your agent:

npx skills add suboss87/fdeops --skill fde

Select fde in your agent, or use @fde where supported:

@fde this is client01. Their support team reads incoming requests,
checks internal documents, then assigns each request to another team.
Help me prepare for the first meeting. Here is the brief: ...

The coordinator selects the relevant method as the work changes. Customer context guides the plan, code changes and verification; the record carries it between sessions. You do not need to learn CLI commands.

Use one skill for one task

npx skills add suboss87/fdeops --skill build

Then ask your agent:

Use FDEOps build to add a manual-review fallback to this routing service.
Here are the agreed behavior, repository and checks: ...

Each task skill includes the instructions it needs. Use build with supplied project context without creating a customer record or installing the coordinator.

See it in action: npx fdeops demo turns fictional meeting notes into a review and a fieldbook, a browser view of the customer record. No AI model is called. The demo uses Node.js 18+ and Git; npx may download the package. It creates or resets its separate .demo workspace. Five-minute walkthrough.

Three things it helps with

1. Strategy: decide what is worth building

Turn the customer’s request into a problem to investigate, a measure of success and a bounded scope. Identify who decides and what evidence would change the plan.

Use discover, who-decides and scope.

2. Architecture: choose an approach that fits

Inspect the existing system, compare options against customer constraints and plan a small slice that tests the design. Make dependencies, tradeoffs and failure paths explicit.

Use options, plan and integrate.

3. Engineering: build, verify and hand over

Implement the change, debug failures and test the agreed behavior. Report what passed on which revision and environment, what remains unproven and what the operating team needs before rollout.

Use build, debug, review, ship and handoff. A passing local test does not establish deployment or customer acceptance. Verification and its limits.

For ongoing work, a local Markdown record at ~/fde-engagements/<customer>/.fde/ carries decisions, evidence and next steps between sessions. The coordinator retrieves relevant context and prepares consequential updates for your review. Use debrief after meetings and switch-clients when changing customers. How records work.

Choose a skill

35 task skills + one coordinator, fde. Each task skill works on its own; the coordinator includes all underlying methods.

Start with the task you need, or let fde select it. dashboard works with saved records; debrief can review supplied notes and return a draft. Each skill explains the context it needs. Full skill catalog.

npx fdeops dashboard --all --open

[!NOTE] Use FDEOps with the setup that fits your work. Try individual skills with sample data, or use a customer-approved local model or LLM provider for customer projects, including regulated and production work.

Customer records stay in local files. The FDEOps CLI makes no network calls; your AI coding agent’s settings determine what it sends to a model provider. Use data approved for that setup.

Setup guidance · Privacy and masking · Local-model results

Who this is for

Forward deployed engineers, consultants and delivery teams working across customer meetings, codebases and operating environments. Bring your existing tools, access and customer agreements. Start with one task or use fde throughout the engagement.

Go deeper

Install or upgrade · Daily use · Worked examples · Skill catalog · Source connections · Repository layout · Verification · Contribute

Built and maintained by Subash Natarajan. Issues · Discussions.

License

MIT. Use FDEOps in your customer work.