| openfde run --repo --agent claude|codex | 組織派遣: タスク自身の git ワークツリーのコーディングエージェントを引用したコンテキストパックで流し、その作業を監査コースに流し、終了マーカー ([DONE]) / [[BLOCKED]]]) からタスクを移動します。 [run ready]]]] ファンが出て、 [run followup]]] は、レビューで同じセッションを続けます | フィードバック | [openfde worktree list/open/remove | 作成したランナーのタスクワークツリー: ブランチ、ベース、汚れたファイルを先にコミットし、削除は、非合併作業をドロップすることを拒否 | | [openfde ontology | [openfde ontology | [openfde ontology | [[openfde ontology] | [[openfde ontology] |[openfde ontology] |[openfde ontology]]] |[[[openfde ontology]] |[[[[openfde ontology]]]] [[[openfde ontology]]]]] |[[[[[[[openfde ontology]]]]] |[[[[[[7]]]]]] 人工物としての腫瘍学:各タイプがどういう意味か、型ごとのインスタンス、孤児、スキーマの違反; [[--rdf]はRDF / OWL(クラス、関係、個人、実績のある事実)をエクスポートします | | [openfde path | 2つの事業体を接続する引用事実の最短鎖 - CFOが調整ワークフローに関連している方法 |

OpenFDE: FDEのAIワークスペース

日本語 | English

Deliver AIの解決100xより速く。 インタビューはメモリになり、メモリはトレース可能なトドとなり、トドはコーディングエージェントの作業になります。

OpenFDEは、先物デプロイされたエンジニアのためのローカルファーストのAIワークスペースです.

| openfde run --repo --agent claude|codex | Orchestrated dispatch: spawn a coding agent in the task’s own git worktree with the cited context pack, stream its work into the audit trail, and move the task on from its exit marker (DONE / BLOCKED / NEEDS_HUMAN); run ready fans out, run followup continues the same session with review feedback | | openfde worktree list/open/remove | Task worktrees the runner created: branch, commits ahead of base, dirty files; removal refuses to drop unmerged work | | openfde ontology | The ontology as an artifact: what each type means, instances per type, orphans, schema violations; --rdf exports RDF/OWL (classes, relations, individuals, facts with provenance) | | openfde path | Shortest chain of cited facts connecting two entities — how the CFO relates to the reconciliation workflow |

OpenFDE: AI workspace for FDEs

English | 简体中文 | 日本語 | Español

Deliver AI solutions 100x faster. Interviews become memory, memory becomes traceable todos, todos become coding-agent work — gated by evals.

OpenFDE is a local-first AI workspace for forward deployed engineers. Think of it as an enterprise brain built the ontology way: the customer organization — its goals, workflows, decisions, constraints, data sources, people and pains — captured as a typed, cited, time-aware graph that both humans and coding agents read from and write back to. It compiles engagement material — interviews, chat logs, documents, PDFs, images — into an ontology-backed operational memory, and closes the loop between humans and coding agents: agents pull tasks and context bundles from the ledger, execute, and write findings back — while the customer’s leadership watches progress live, with every claim citing its source.

Why

An FDE’s working state lives in three fragile places:

• Knowledge lives in conversations. Who trusts which data source, why a decision was made, which constraint blocks a workflow — said once in a meeting, lost two weeks later.
• Tasks live in heads. The gap between “heard it in an interview” and “dispatched it to a coding agent” has no system, no context, no trail back to the source.
• Verification lives in feelings. Agent output gets accepted by vibes instead of evals.

OpenFDE turns all three into one system, starting with memory.

What OpenFDE does

• Ontology-backed operational memory. A fixed FDE domain ontology — goals, workflows, decisions, constraints, data sources, pain points — constrains extraction, so what enters the ledger is operational knowledge, not prose. A dot-line-plane lens (value planes → business flows → decision points) organizes it the way leadership thinks.