sgit (the encrypted git for humans and AI agents)
sgit is git for encrypted vaults) and a vault is a unit of work: data, app, history and sources, versioned like git and handed over with a single read key. No account, no hosting, nothing to install for the reader; the server stores ciphertext it cannot read. Twenty-five real vaults you can open.
Source: https://sgit.ai/index.html↗ · site v0.6.8 · this file is generated from the same content as the page, so the two cannot drift. Every page on this site has a .md twin; internal links below point at them.
Git for encrypted vaults, for humans and AI agents
A vault is a unit of work:
data, app, history and sources, shipped as one string
Version it like git. Hand it over with a single read key, no account, no hosting, no install for the reader. And the server that stores it cannot read it.
Open a real vault →↗ 5-minute quickstart →↗
Pure Python · two runtime dependencies · Apache-2.0 · or try it in your browser↗
Reference, AIUC-1 conformance layer, The AIUC-1 standard as a graph, plus a conformance layer that computes insurability, Open it →↗ Application, Agent permission games, Two games about grants and mandates, the first vault here that phones home, Open it →↗ Presentation, AI vs. AI, Black Hat EU 2025, The Black Hat EU 2025 keynote, with its PDF exports and eight research papers, Open it →↗ Report, Penetration Test Report, A penetration test report (fictional) with a re-test script per finding, Open it →↗
Four of 36 published vaults. Each opens with a read key printed on its page, no account, nothing to install, and the server that stores it cannot read it. See all 36 →↗
What people actually ship
Not categories, things. Each one is a real vault you can open, and each is hard to make any other way, for a reason that has little to do with encryption.
Hand over a report, Penetration Test Report, Findings, evidence and a retest script per finding travel as one unit. The client opens it with one string and can re-run the tests themselves., vault o4lrwx02 · open it →↗ Publish a standard as data, AIUC-1 conformance layer, 53 controls as a graph you can cite, 82 hashed source snapshots, and a fork that added a conformance layer without changing a byte of the original., vault 2wzct4k7 · open it →↗ Give a talk, AI vs. AI, Black Hat EU 2025, 26 slides, six PDF exports and the eight papers the talk cites, in the vault it was presented from. The deck and its sources never separate., vault k1izvg7e · open it →↗ Pitch an investor, VoiceDebrief pitch (FI), A presenter app with timings and speaker notes, shipped with the script, the research and the exports it was built from., vault 95i2xqrd · open it →↗ Ship a game that reports back, Agent permission games, Anonymous telemetry over a write-only lane, the one credential shape that survives being published with a read key., vault 4evnlwrj · open it →↗ Give an agent a workspace, Risk Mandate, 124 files, 98 commits, eight entry points: a software project delivered as a vault, that calls an LLM without ever holding the API key., vault 4zf6pf2z · open it →↗
All published vaults, sortable →↗
Nine of these vaults are the same graph, at different altitudes
A Fractal Semantic Graph is one where every node opens into a graph with its own ontology. A regulation, then its articles, then the words they define: each world using vocabulary the one above never agreed to. What stays constant is the grammar, never the schema, and that is what lets everything connect to everything without anyone being forced to conform. For years we called it graphs of graphs of graphs.
The idea, and the evidencethe jump test · a ladder of twelve rungs from the text of a law down to one compute instance · nine published vaults you can open with a read key↗ What it costs, measuredno live database · a 1,051-node graph opens in 94 KB and three requests · 11.2 MB of source down to a 4 KB ontology with nothing discarded↗
One human, a team of agents
This site, and every vault on it, is built by one person working with several AI agents, and the agents build for each other. The state that makes that possible is a vault: versioned, shareable, and readable by whoever holds the key.
166site releases, each verified live before it was called done
36vaults published with a deliberately public read key
27sibling sites on *.sgit.ai, one question each
12cross-team briefs filed or received, in the open
1A build brief↗ was published here on a Saturday. Another agent read it and shipped a vault from it↗ the same day.
2The team that owns the API reviewed that vault against the brief, found the brief wrong in two places, and the correction now sits above the mistake↗.
3One agent forked another agent's vault↗, kept every byte, added a layer, and the original's tests still pass inside the fork.
→The record is the site itself: the briefs↗, the case studies↗, every release↗. And the diagnosis that produced this homepage is an article, with the before pictures↗.
Under the hood, it is git
Same muscle memory. Files are encrypted before they leave your machine; the server stores ciphertext and hashes, nothing else.
$sgit create my-vault ✓ Vault created and registered ✓ Initial commit pushed
Vault key: <24-char-passphrase>:<vault-id>
Keep this safe. It is the address, the auth, and the encryption key in one string. Without it, nobody, including the server, can read this vault.
$vim notes/positioning.md $sgit status On clone branch branch-clone-3f9c → named branch main modified: notes/positioning.md added: drafts/hero-copy.md
$sgit commit -m "first draft of hero copy" ✓ Committed 2 files (no staging area, commit snapshots the folder)
$sgit history log --oneline c4e81a first draft of hero copy b2d70f initial commit
$sgit history diff --- a/notes/positioning.md +++ b/notes/positioning.md
- sgit is a CLI for encrypted sync
- sgit is git for encrypted vaults
$sgit push ✓ Pushed 2 objects (delta push, only changed, only ciphertext)
on another machine (or another agent)
$sgit clone <vault-key> ✓ Cloned and decrypted 12 files
$sgit pull ✓ Up to date
one call: encrypt, commit, push, machine-readable result
no working-directory scan, no full clone needed
$sgit write notes/finding.md --file result.md
--message "agent A: analysis" --push --json
{
"status": "pushed",
"path": "notes/finding.md",
"blob_id": "obj-cas-imm-9c2e41ab77d0"
}
The vault key is the address, the auth, and the encryption key, one high-entropy string. Keep it safe.
Git-like version controlcommit, branch, merge, diff, log, stash, revert your encrypted files
Client-side encryptionAES-256-GCM before upload; keys derived from your vault key, never sent to the server
Real three-way mergeconflict files plus a base/ours/theirs resolve --show view
The two-branch modela private clone branch per machine or agent; shared named branches for collaboration
Apps live inside the dataa vault can carry its own sandboxed app, with the permissions it asks for declared in a file
Browser interopopen the same vault in SG/Vault on the web, CLI and browser speak one wire format
What the server sees
Your machine
- filenames & folder structure
- file contents
- commit messages
- branch names
- the vault key & derived keys
[diagram]
The server
- obj-cas-imm-3f9c41ab77d0
- ref-pid-muw-8e02cc194b3a
- ciphertext blobs (AES-256-GCM)
- object sizes · timestamps
- the vault id
That's the whole list, and we publish the threat model, including what the server can see (sizes, timing, vault ID). Read the security model →↗
Built for agents
Agents need shared state. Shared state needs versioning, and privacy. sgit is the encrypted, versioned workspace for humans and AI agents.
Persistent memory
A vault is just a folder
An agent clones it, reads and writes files normally, commits, pushes. The next session pulls and continues. State survives the context window.
Multi-agent, human-merged
A branch per agent
Each agent gets its own private clone branch; work meets on named branches; a human reviews the merge, in the terminal or in the SG/Vault browser.
Agent-grade plumbing
Machine-readable everything
sgit write for surgical single-call commits, --json on every read path, cat --id with zero network calls, sparse clones for fast cold starts. What that costs, measured↗.
Read the agent guide →↗ · Performance & cost →↗ · Install the skills →↗ · Use cases →↗ · llms.txt↗
In production, and honest about it
sgit is in beta, powering production workflows daily. No superlatives, just the evidence, and a page that tells you when not to use it.
~4,000 testsmutation testing in CIintegration tests against a real server2** runtime dependenciesApache-2.0** security model published↗ when NOT to use sgit↗ why does this exist?↗ sgit · SG/Vault · SG/Send: the three doors↗
Nineteen sites, one question each
Most of the thinking behind sgit no longer lives on this site. It moved out to *.sgit.ai: a family of focused sites, each taking one question further than a section here could, each with its own version history and repository. This site stayed about sgit.
Agents & AIidentity for agents · calling an LLM with no API key · how the code is written↗ Risk & governanceyou cannot deny a risk · cite the provision · the requirements nobody writes down↗ Graphs & methodmeaning lives in the edges · issues as files · maps are claims↗ Security & infrastructurea key registry for agents · an edge guard · ephemeral environments↗ Business & publishingopen source is a strategy · subscriptions are not rent · provenance as the product↗
Find the one that answers your question →↗
Start with an argument, not a menu
The articles are the readable way in: one page, one argument, with the screenshots and the links to check it. If you only read one thing here, read one of these.
2026-09-24Before you give an agent a connector, give the connector a twinWhen an AI agent is given a Gmail or Google Calendar connector, it can read, send, move, decline and permanently delete on somebody's behalf, and for several of those actions the platform itself documents that there is no way back. This article argues that a twin of the connector is the minimum requirement for deploying an agent with confidence. The twin is a journal of every request and response the agent makes, appended as it happens to a write-only lane, processed later, and replayed into the inbox and calendar as the agent saw them, with a before and after for every change and a revert plan for each one. It gives provenance, explanation and a named list of what can and cannot be undone, and it changes the agent's behaviour policy from a hope into a list. Every claim about Gmail and Calendar is taken from Google's own documentation and linked. A working replay of an invented session, and a business plan for the service, are published alongside it as a vault.Read it →↗ 2026-09-24Every risk is already accepted. The only question is by whom, and for how long.A foundation article on risk acceptance, for readers who have never met the idea. A risk exists the moment the exposure does, so an organisation is always carrying it; the only open questions are who has accepted it, and until when. There is no deny button, only three doors (accept for a stated interval, fund the work, or fix it), and silence escalates. The interval is the decision, from four hours, which is an incident, to six months, which is a named decision to wait. Accepted is not the same as acceptable, which matters because the EU AI Act requires providers of high-risk AI systems to have residual risk judged acceptable, and never defines the word. Every risk has a holder, every holder has a boss, and every path ends at the board. Every risk is established by facts and ended by facts, from the board down to the configuration file, which is what closes the gap between a register and reality. The article walks one invented risk through six weeks, argues that each material risk deserves a vault of its own as its evidence pack, explains why executives resist the model, and shows why it fits alongside every GRC platform rather than replacing one. A business plan for a company that runs this loop is published with it.Read it →↗ 2026-09-22The future of news is the story vault, not the paywallThe news industry runs on two commercial models, advertising and subscriptions, and both are bad for the reader. One sells the reader to somebody else. The other charges rent on something most people have stopped using. Both are now being dismantled from outside, by a search layer that has stopped sending traffic and by consumer law that arrives in January 2027. This article is about what to build instead, in practical terms. The objective is a commercial model that rewards investigative journalism, so that the expensive, evidenced kind of reporting drives usage, usage drives revenue that depends on neither search nor renewals, and that revenue funds more of the same. The mechanism is to stop selling the article and start selling what the article was made from. The story is a graph, a fractal semantic graph in which meaning comes from connectivity and every claim walks down to hashed evidence, so that trust comes through provenance and provenance comes via evidence. The article is one projection of it. From that one graph a newsroom can sell five things, on demand and in pence, to readers, to firms and to agents, and every payment walks back to the people who made the facts. It is built, in parts, on things we have already published.Read it →↗
Encrypted vaults. Git workflows. Zero knowledge.
5-minute quickstart →↗ Star on GitHub → ↗