<a id="top"></a 特性 --- Engram™ --- 保持项目上下文 重新启动会话的成本并不是代币,而是你需要重新解释项目上下文,从而浪费时间。
<a id="top"></a 特性 --- Engram™ --- 保持项目上下文 重新启动会话的成本并不是代币,而是你需要重新解释项目上下文,从而浪费时间。
The cost of a fresh session is not the tokens — it is you, re-explaining the same decisions every morning. Engram removes that: your agent writes down what it learns as it goes and reaches for it before it reaches for you, so context accumulates instead of resetting.
Small changes should not need a planning pipeline, and larger work should not lose its context between sessions. Organic Driven Development (ODD) keeps understood changes lightweight and gives substantial, authorized work one recoverable feature document. The agent explores before changing code, checks the results, and keeps progress current so work can resume without rebuilding the plan. Formal SDD phases remain an explicit choice.
When you explicitly choose Spec-Driven Development, proposal, specification, design, and task artifacts make the plan reviewable before implementation. File-backed storage keeps them on disk; Engram-backed storage keeps them in memory. Apply follows the configured TDD mode. Research and Verify are optional: Verify can diagnose partial work and report practical findings, but it is not an archive gate. Archive records the actual state and history, including unfinished work when you explicitly archive it; it does not ship or approve the change, and SDD does not invoke RDD. TDD is also available in ODD; it does not require an SDD phase.
Receipt-Driven Development (RDD) is opt-in and stays off until you enable it. Its point is that a review cannot drift: the candidate is frozen before anything reads it, so the evidence belongs to the exact version you are about to rely on — not to whatever the worktree looked like a moment later. The depth comes from that frozen candidate rather than from the model's judgment, and the result is informational. Commit, push and release stay your call.
A model that guesses the next step guesses differently tomorrow, and differently again for your teammate. That is the gap between a workflow and a suggestion. The gentle-ai binary owns native SDD status and RDD review transitions, and because it reads state from files rather than from a context window, two people on two machines get the same answer — and so does the same person a month later.
The way Gentle-AI was intended. Gentle-AI brings our native Pi extensions together in one focused development environment: orchestrate specialized agents, monitor usage for supported provider accounts, and review code changes in a built-in diff.
Gentle-AI brings its shared workflow to Pi, OpenCode, Claude Code, Codex, and twelve more agents. Each integration uses that agent's native capabilities, so available features such as delegation and RDD review can differ.
~/.ssh, .env and credential files
Config backups
Snapshotted before every single write
Doctor
gentle-ai doctor — read-only health report
Personas
Optional personas; Gentleman is a caring but rigorous mentor who guides you toward your goal
Themes
Gentleman and Gentleman-Cute
Per-phase model assignment
Assign a model to each phase in Pi and OpenCode
Every component, skill and preset: Full breakdown →
# macOS (Homebrew)
brew install gentleman-programming/tap/gentle-ai
# macOS / Linux (curl)
curl -fsSL https://raw.githubusercontent.com/Gentleman-Programming/gentle-ai/main/scripts/install.sh | bash
# Windows (PowerShell) — source install, needs Go 1.25.10+
go install github.com/gentleman-programming/gentle-ai/v3/cmd/gentle-ai@latest
gentle-ai # pick your agents, components and persona
gentle-ai doctor # verify — read-only, changes nothing
Then use your agent normally. Your configs are snapshotted before every write, and Gentle-AI never installs an AI agent for you — it configures what you already have.
Beta channel, signature verification and per-distro prerequisites: Quickstart →
Everything labelled up-for-grabs is scoped, approved and unclaimed — pick one and it's yours.
Built by Alan Buscaglia (Gentleman Programming): 15 years of enterprise architecture, a community of thousands of developers testing these tools daily, and one rule for AI-assisted work — verifying beats generating.
Teams adopting AI and finding it isn't working — resistance, everyone prompting their own way, no shared quality bar — can reach out about engagements built on these same open-source tools →.
Trademark notice: The Gentle AI™ and Engram™ names and logos are trademarks of Alan Buscaglia. Both marks are used throughout this document; the symbol appears on the first prominent mention of each, and this notice covers the rest. The MIT License applies to the code; it does not permit implying endorsement or official affiliation. See TRADEMARKS.md.
暂无开放 Issues,或尚未同步最近议题。