The deterministic engineering environment for the AI agent you already use.
Website • Quickstart • Docs • Wiki
Your agent writes code, then forgets everything. It has no opinion about your project, and no way to prove what it did beyond asking you to read every line. Gentle-AI gives it memory, a workflow, and evidence.
If Gentle-AI made your agent worth trusting, a star helps other people find it.
WORKS WITH THE AGENT YOU ALREADY HAVE
Pi ·
OpenCode ·
Claude Code ·
Codex ·
Cursor ·
VS Code Copilot ·
Gemini CLI ·
Kilo Code
Kimi Code ·
Kiro IDE ·
Qwen Code ·
Hermes ·
Antigravity ·
Windsurf ·
OpenClaw ·
Trae
16 integrations · native configuration · compare capabilities →
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.
Every phase leaves a file on disk you can open, argue with, and correct — so the plan is reviewable before a single line of code exists. TDD (test-driven development) belongs in Apply when it fits, because that is the first point where there is a spec to test against. Verify then runs as its own step against that spec, not as a self-report from whatever wrote the code, so you can see what was actually checked.
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.
| Component | What it does |
|---|---|
| Skills library | Loaded automatically when the task matches |
| Context7 MCP | Optional, selectable live framework and library documentation |
| CodeGraph | Read-only symbol graph of your codebase |
| Security deny-list | Blocks ~/.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/v2/cmd/gentle-ai@latestgentle-ai # pick your agents, components and persona
gentle-ai doctor # verify — read-only, changes nothingThen 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 →
| Where to go | What you'll find |
|---|---|
| Intended Usage | The mental model. If you read one page, read this one. |
| Quickstart · Usage | Install, prerequisites, every CLI command and flag |
| Agents | Feature matrix and per-agent notes for all 16 |
| Routing | How the agent picks direct, delegated or SDD |
| Review · Architecture | The RDD contract, lifecycle and threat model |
| Engram · Components | Memory commands, skills, presets and personas |
| Contributing · Codebase Guide | Extend or contribute |
| Telemetry | What we count, and how to turn it off |
Everything labelled up-for-grabs is scoped, approved and unclaimed — pick one and it's yours.
This project exists because of these people.
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.